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[USER] You are an expert technical analyst for Mike Merlino, an AI agency operator and builder. Your job is to evaluate GitHub repositories and extract structured signal. Mike's domains: AI agents, LLM tooling, Claude Code, MCP servers, prompt engineering, SEO automation, GoHighLevel, Next.js, ShadCN, Vercel, Supabase, voice AI, agentic coding, Discord/Telegram bots, scheduler/cron patterns, Python automation, TypeScript. Return ONLY valid JSON: { "what_it_is": "one sentence plain English description", "stack": ["Technology1", "Technology2"], "why_mike_cares": "one sentence on overlap with Mike's work, or 'Low overlap'", "verdict": "check-it-out" | "worth-knowing" | "skip", "verdict_reason": "one sentence" } Verdict: - "check-it-out": direct overlap with Mike's active projects or tools he uses - "worth-knowing": interesting adjacent tool, may matter later - "skip": no clear overlap Be OPINIONATED. Not neutral. Repo: mbailey/skills Stars: 1 Language: Python Topics: Description: Claude Code Plugin Marketplace README (first 3000 chars): # Mike Bailey's Skills Marketplace A Claude Code plugin marketplace with skills to somewhat improve things. ## Installation ### Add Claude Code Marketplace ``` claude plugin marketplace add mbailey/skills ``` ### Install a Plugin ``` claude plugin install --scope user show-me@mbailey ``` ### Browse and Install Plugins ``` claude /plugin ``` ## Available Plugins | Plugin | Description | | ------------------------------------------------- | ------------------------------------------------------ | | [show-me](https://github.com/mbailey/show-me) | Let Claude show you files and web pages (tmux, neovim) | | [VoiceMode](https://github.com/mbailey/voicemode) | Natrual conversations with Claude Code | ## Security scanning `scripts/scan_plugin.py` is a deterministic, dependency-free security scanner for plugin directories. It flags unicode tricks (bidi/zero-width/homoglyphs), network access, destructive commands, pipe-to-shell, credential-path access, encoded payloads, privilege escalation, and compiled bytecode. Run it against a plugin directory (or a `plugins/` parent) with [`uv`](https://docs.astral.sh/uv/): ``` uv run scripts/scan_plugin.py <plugin-dir> uv run scripts/scan_plugin.py plugins/ # scan every plugin uv run scripts/scan_plugin.py <dir> --format=markdown ``` Exit codes: `0` clean, `1` usage error, `2` BLOCK findings, `3` WARN only. CI runs this as a **non-blocking, informational** job (it never gates merges). The marketplace currently lists external `url`-source plugins with no bundled plugin directories, so the job self-skips until skills are vendored under `plugins/`. The scanner is vendored from [trailofbits/skills-curated](https://github.com/trailofbits/skills-curated) (`scripts/scan_plugin.py`) and is licensed under [CC-BY-SA-4.0](https://creativecommons.org/licenses/by-sa/4.0/); see the attribution header in the file. Analyze this repo per your instructions. Return ONLY valid JSON, no markdown fences. [ASSISTANT] {"what_it_is": "A Claude Code plugin marketplace by Mike Bailey hosting skills like show-me and VoiceMode, with a bundled security scanner for plugin directories.", "stack": ["Claude Code", "Python", "uv"], "why_mike_cares": "Mike runs a heavy Claude Code skills/plugins ecosystem and the bundled scan_plugin.py from trailofbits is directly useful for vetting third-party skills before installing them globally.", "verdict": "worth-knowing", "verdict_reason": "The marketplace itself is thin (2 plugins, 1 star), but the vendored security scanner is a drop-in tool for Mike's CLI-first routing rule about reviewing generated SKILL.md and install scripts before adding to global skills."}

[USER] You are an expert technical analyst for Mike Merlino, an AI agency operator and builder. Your job is to evaluate GitHub repositories and extract structured signal. Mike's domains: AI agents, LLM tooling, Claude Code, MCP servers, prompt engineering, SEO automation, GoHighLevel, Next.js, ShadCN, Vercel, Supabase, voice AI, agentic coding, Discord/Telegram bots, scheduler/cron patterns, Python automation, TypeScript. Return ONLY valid JSON: { "what_it_is": "one sentence plain English description", "stack": ["Technology1", "Technology2"], "why_mike_cares": "one sentence on overlap with Mike's work, or 'Low overlap'", "verdict": "check-it-out" | "worth-knowing" | "skip", "verdict_reason": "one sentence" } Verdict: - "check-it-out": direct overlap with Mike's active projects or tools he uses - "worth-knowing": interesting adjacent tool, may matter later - "skip": no clear overlap Be OPINIONATED. Not neutral. Repo: CopilotKit/fullstack-solution-template-for-agentcore Stars: 1 Language: Python Topics: Description: Flexible Fullstack solution template for production-ready deployments of any use case on Amazon Bedrock AgentCore. README (first 3000 chars): # Fullstack AgentCore Solution Template (FAST) _Author's note: for the official name for this solution is the "Fullstack Solution Template for Agentcore" but it is referred to throughout this code base as FAST for convenience._ The Fullstack AgentCore Solution Template (FAST) is a starter project repository that enables users (delivery scientists and engineers) to quickly deploy a secured, web-accessible React frontend connected to an AgentCore backend. Its purpose is to accelerate building full stack applications on AgentCore from weeks to days by handling the undifferentiated heavy lifting of infrastructure setup and to enable vibe-coding style development on top. The only central dependency of FAST is AgentCore. It is agnostic to agent SDK (Strands, LangGraph, etc) and to coding assistant platforms (Q, Kiro, Cline, Claude Code, etc). FAST is designed with security and vibe-codability as primary tenets. Best practices and knowledge from experts are codified in _documentation_ in this repository rather than in _code_. By including this documentation in an AI coding assistant's context, or by instructing the AI coding assistant to leverage best practices and code snippets found in the documentation, delivery scientists and developers can quickly vibe-build AgentCore applications for any use case. AI coding assistants can be used to fully customize the frontend and the infrastructure, enabling scientists to focus the areas where their knowledge is most impactful: the actual prompt engineering and GenAI implementation details. With FAST as a starting point and development framework, delivery scientists and engineers will accelerate their development process and deliver production quality AgentCore code following architecture and security best practices without having to learn any frontend or infrastructure code. ## FAST Baseline System FAST comes deployable out-of-the-box with a fully functioning, full-stack application. This application represents starts as a basic multi-turn chat agent where the backend agent has access to tools. **Do not let this deter you, even if your use case is entirely different! If your application requires AgentCore, customizing FAST to any use case is extremely straightforward. That is the intended use of FAST!** The application is intentionally kept very, very simple to allow developers to easily build up whatever they want on top of the baseline. The tools shipped out of the box include: 1. **Gateway Tools** - Lambda-based tools behind AgentCore Gateway with authentication: - Text analysis tool (counts words and letter frequency) 2. **Code Interpreter** - Direct integration with Amazon Bedrock AgentCore Code Interpreter: - Secure Python code execution in isolated sandbox - Session management with state persistence - [ASSISTANT] {"what_it_is": "Fullstack starter template that deploys a React frontend wired to an Amazon Bedrock AgentCore backend with auth, infra, and tool integration scaffolded out.", "stack": ["Python", "React", "AWS Bedrock AgentCore", "AWS Lambda", "AWS CDK"], "why_mike_cares": "Low overlap, Mike runs Claude/Anthropic-native agent stacks on Vercel/Supabase, not AWS Bedrock AgentCore.", "verdict": "skip", "verdict_reason": "AWS Bedrock-locked template with zero traction (1 star) and no fit with Mike's Claude Code, Next.js, or MCP-based agent ecosystem."}

[USER] <task-notification> <task-id>ab9b2ab6c7f5494b6</task-id> <output-file>C:\Users\mikem\AppData\Local\Temp\claude\D--ClaudeDev\a05a7db0-fdbd-4d5a-9019-b037f8cf7225\tasks\ab9b2ab6c7f5494b6.output</output-file> <status>completed</status> <summary>Agent "Robocopy E: vaults to F:\HERE" completed</summary> <result>19G total. Waiting.</result> <usage><total_tokens>91178</total_tokens><tool_uses>0</tool_uses><duration_ms>2923</duration_ms></usage> </task-notification> [ASSISTANT] Standing by.

[USER] You are an expert technical analyst for Mike Merlino, an AI agency operator and builder. Your job is to evaluate GitHub repositories and extract structured signal. Mike's domains: AI agents, LLM tooling, Claude Code, MCP servers, prompt engineering, SEO automation, GoHighLevel, Next.js, ShadCN, Vercel, Supabase, voice AI, agentic coding, Discord/Telegram bots, scheduler/cron patterns, Python automation, TypeScript. Return ONLY valid JSON: { "what_it_is": "one sentence plain English description", "stack": ["Technology1", "Technology2"], "why_mike_cares": "one sentence on overlap with Mike's work, or 'Low overlap'", "verdict": "check-it-out" | "worth-knowing" | "skip", "verdict_reason": "one sentence" } Verdict: - "check-it-out": direct overlap with Mike's active projects or tools he uses - "worth-knowing": interesting adjacent tool, may matter later - "skip": no clear overlap Be OPINIONATED. Not neutral. Repo: GoogleCloudPlatform/asl-ml-immersion Stars: 2548 Language: Jupyter Notebook Topics: adk, adk-pyth, agents, generative-ai, google-cloud-platform, machine-learning, tensorflow Description: Notebooks, code samples and reference for machine learning and generative ai on Google Cloud for the Advanced Solutions Lab (ASL) bootcamps. README (first 3000 chars): # Advanced Solutions Lab ## Overview This repository contains AI and Machine Learning contents meant to be run on Google Cloud. This is maintained by Google Cloud’s [Advanced Solutions Lab (ASL)](https://cloud.google.com/asl) team. This repository contains 3 main modules to covers various AI/ML toipcs: - `asl_core`: A wide range of model architectures (DNN, CNN, RNN, transformers, SNGP, etc.) targeting many data modalities (tabular, image, text, time-series) implemented mainly in Tensorflow and Keras. - `asl_mlops`: Tools on Google Cloud’s Vertex AI for operationalizing Tensorflow, Scikit-learn and PyTorch models at scale (e.g. Vertex training, tuning, and serving, TFX and Kubeflow pipelines). - `asl_genai`: Generative AI and Agent System using Gemini and Agentic Frameworks like Google ADK. ## Repository Structure Each module (`asl_core`, `asl_mlops`, `asl_genai`) has separate environment and materials, which are organized in each directory. All learning materials are in the contets folder. This folder is organized by different topics. Each folder contains a `labs` and a `solutions` folder. Use the `labs` notebooks to test your coding skills by filling in TODOs and refer to the notebooks in the `solutions` folder to verify your code. We have three main folders described below: ``` ├── asl_core │ ├── notebooks - contains learning materials organized by topic │ │ ├── building_production_ml_systems │ │ │ ├── labs │ │ │ └── solutions │ │ ├── end-to-end-structured │ │ ├── image_models │ │ ├── ... │ ├── kernels - contains kernel scripts needed for certain notebooks │ ├── scaffolds - contains sample code to accelerate AI/ML projects │ ├── requirements.txt - dependencies for this module ├── asl_mlops │ ├── ... ├── asl_genai │ ├── ... ├── ... ``` ## Environment Setup ### Step 1. Run the Setup Script on Cloud Shell This repository is tested on Vertex AI Workbench and Cloud Workstations. To begin, run the setup script in [Cloud Shell](https://shell.cloud.google.com) to configure essential project infrastructure (APIs, IAM, Buckets). Run the setup script in [Cloud Shell](https://shell.cloud.google.com) to provision your environment. ```bash git clone https://github.com/GoogleCloudPlatform/asl-ml-immersion.git cd asl-ml-immersion bash scripts/setup_env.sh ``` You will be prompted to select the environment to set up: * **1) Vertex AI Workbench:** Setup Vertex AI Workbench. * **2) Cloud Workstations:** Setup Cloud Workstations. * **3) Setup both:** Setup both environments. * **4) Skip:** Setup project infrastructure (APIs, IAM, Buckets) only. By selecting the option 1-3, you can automatically setup the environment, [ASSISTANT] {"what_it_is":"Google Cloud's Advanced Solutions Lab bootcamp repo with notebooks covering TensorFlow ML, Vertex AI MLOps, and Gemini/ADK generative AI labs.","stack":["Jupyter","TensorFlow","Keras","Vertex AI","Gemini","Google ADK","Python"],"why_mike_cares":"The asl_genai module covers Google ADK agent framework which is adjacent to Mike's multi-agent ecosystem work, but the GCP-heavy stack doesn't match his Next.js/Supabase/Claude-centric setup.","verdict":"worth-knowing","verdict_reason":"ADK agent patterns and Gemini agentic examples are useful reference for Mike's agent fleet, but bootcamp notebooks tied to Vertex AI infra have low direct reuse."}

[USER] You are an expert technical analyst for Mike Merlino, an AI agency operator and builder. Your job is to evaluate GitHub repositories and extract structured signal. Mike's domains: AI agents, LLM tooling, Claude Code, MCP servers, prompt engineering, SEO automation, GoHighLevel, Next.js, ShadCN, Vercel, Supabase, voice AI, agentic coding, Discord/Telegram bots, scheduler/cron patterns, Python automation, TypeScript. Return ONLY valid JSON: { "what_it_is": "one sentence plain English description", "stack": ["Technology1", "Technology2"], "why_mike_cares": "one sentence on overlap with Mike's work, or 'Low overlap'", "verdict": "check-it-out" | "worth-knowing" | "skip", "verdict_reason": "one sentence" } Verdict: - "check-it-out": direct overlap with Mike's active projects or tools he uses - "worth-knowing": interesting adjacent tool, may matter later - "skip": no clear overlap Be OPINIONATED. Not neutral. Repo: privatenumber/cleye Stars: 626 Language: TypeScript Topics: argv, cli, commandline-interface, commandline-parser, flags, node, parameters, typed, typescript Description: 👁‍🗨 Strongly typed CLI development for Node.js README (first 3000 chars): <p align="center"> <img width="110" src=".github/logo.webp"> </p> <h1 align="center"> cleye <br> <a href="https://npm.im/cleye"><img src="https://badgen.net/npm/v/cleye"></a> <a href="https://npm.im/cleye"><img src="https://badgen.net/npm/dm/cleye"></a> </h1> The intuitive command-line interface (CLI) development tool. ### Features - Minimal API surface - Powerful flag parsing - Strongly typed parameters and flags - Command support - Help documentation generation (customizable too!) → [Try it out online](https://stackblitz.com/edit/cleye-demo?devtoolsheight=50&file=examples/greet.ts&view=editor) <br> <p align="center"> <a href="https://github.com/sponsors/privatenumber/sponsorships?tier_id=398771"><img width="412" src="https://raw.githubusercontent.com/privatenumber/sponsors/master/banners/assets/donate.webp"></a> <a href="https://github.com/sponsors/privatenumber/sponsorships?tier_id=397608"><img width="412" src="https://raw.githubusercontent.com/privatenumber/sponsors/master/banners/assets/sponsor.webp"></a> </p> <p align="center">^{<i>Already a sponsor?</i> Join the discussion in the <a href="https://github.com/pvtnbr/cleye">Development repo</a>!}</p> ## Install ```bash npm i cleye ``` ## About _Cleye_ makes it very easy to develop command-line scripts in Node.js. It handles argv parsing to give you strongly typed parameters + flags and generates `--help` documentation based on the provided information. Here's an example script that simply logs: `Good morning/evening <name>!`: _greet.js:_ ```ts import { cli } from 'cleye' // Parse argv const argv = cli({ name: 'greet.js', // Define parameters parameters: [ '<first name>', // First name is required '[last name]' // Last name is optional ], // Define flags/options flags: { // Parses `--time` as a string time: { type: String, description: 'Time of day to greet (morning or evening)', default: 'morning' } } }) const name = [argv._.firstName, argv._.lastName].filter(Boolean).join(' ') if (argv.flags.time === 'morning') { console.log(`Good morning ${name}!`) } else { console.log(`Good evening ${name}!`) } ``` 🛠 In development, type hints are provided on parsed flags and parameters: <p align="center"> <br> <img src=".github/typed-flags.png" width="600"> <br> <i>Type hints for Cleye's output are very verbose and readable</i> <br> <br> </p> 📖 Generated help documentation can be viewed with the `--help` flag: ```sh $ node greet.js --help greet.js Usage: greet.js [flags...] <first name> [last name] Flags: -h, --help Show help --time <string> Time of day to greet (morning or evening) (default: "morning") ``` ✅ Run the scrip [ASSISTANT] {"what_it_is":"A TypeScript-first CLI argument parser for Node.js with strongly typed flags, parameters, commands, and auto-generated help docs.","stack":["TypeScript","Node.js"],"why_mike_cares":"Mike builds Python and TypeScript CLI tooling (GSD 2, PrintingPress, CLI-Anything harnesses, brv) where typed flags and auto-help would tighten the agent-native CLI build standard.","verdict":"worth-knowing","verdict_reason":"Solid pick if any new TS CLI gets built in the ecosystem, but Python dominates current CLI work so it is adjacent, not urgent."}

[USER] You are an expert technical analyst for Mike Merlino, an AI agency operator and builder. Your job is to evaluate GitHub repositories and extract structured signal. Mike's domains: AI agents, LLM tooling, Claude Code, MCP servers, prompt engineering, SEO automation, GoHighLevel, Next.js, ShadCN, Vercel, Supabase, voice AI, agentic coding, Discord/Telegram bots, scheduler/cron patterns, Python automation, TypeScript. Return ONLY valid JSON: { "what_it_is": "one sentence plain English description", "stack": ["Technology1", "Technology2"], "why_mike_cares": "one sentence on overlap with Mike's work, or 'Low overlap'", "verdict": "check-it-out" | "worth-knowing" | "skip", "verdict_reason": "one sentence" } Verdict: - "check-it-out": direct overlap with Mike's active projects or tools he uses - "worth-knowing": interesting adjacent tool, may matter later - "skip": no clear overlap Be OPINIONATED. Not neutral. Repo: openai/symphony Stars: 24064 Language: Elixir Topics: Description: Symphony turns project work into isolated, autonomous implementation runs, allowing teams to manage work instead of supervising coding agents. README (first 3000 chars): # Symphony Symphony turns project work into isolated, autonomous implementation runs, allowing teams to manage work instead of supervising coding agents. [](.github/media/symphony-demo.mp4) _In this [demo video](.github/media/symphony-demo.mp4), Symphony monitors a Linear board for work and spawns agents to handle the tasks. The agents complete the tasks and provide proof of work: CI status, PR review feedback, complexity analysis, and walkthrough videos. When accepted, the agents land the PR safely. Engineers do not need to supervise Codex; they can manage the work at a higher level._ > [!WARNING] > Symphony is a low-key engineering preview for testing in trusted environments. ## Running Symphony ### Requirements Symphony works best in codebases that have adopted [harness engineering](https://openai.com/index/harness-engineering/). Symphony is the next step -- moving from managing coding agents to managing work that needs to get done. ### Option 1. Make your own Tell your favorite coding agent to build Symphony in a programming language of your choice: > Implement Symphony according to the following spec: > https://github.com/openai/symphony/blob/main/SPEC.md ### Option 2. Use our experimental reference implementation Check out [elixir/README.md](elixir/README.md) for instructions on how to set up your environment and run the Elixir-based Symphony implementation. You can also ask your favorite coding agent to help with the setup: > Set up Symphony for my repository based on > https://github.com/openai/symphony/blob/main/elixir/README.md --- ## License This project is licensed under the [Apache License 2.0](LICENSE). Analyze this repo per your instructions. Return ONLY valid JSON, no markdown fences. [ASSISTANT] {"what_it_is": "OpenAI's autonomous coding agent orchestrator that spawns isolated implementation runs from Linear tickets, with built-in proof-of-work (CI, PR reviews, walkthrough videos) so engineers manage work instead of babysitting Codex.", "stack": ["Elixir", "Codex", "Linear API", "GitHub PRs", "CI/CD"], "why_mike_cares": "Direct overlap with Mike's Carlos/Oliver orchestration model, ClawControl task dispatch, and his 'manage work not agents' philosophy. This is OpenAI's official take on the exact pattern he's building.", "verdict": "check-it-out", "verdict_reason": "OpenAI's reference architecture for autonomous agent orchestration with proof-of-work, mirroring Mike's Oliver/Carlos/POWD pattern. Worth studying the SPEC.md even if he ignores the Elixir impl."}

[USER] You are an expert technical analyst for Mike Merlino, an AI agency operator and builder. Your job is to evaluate GitHub repositories and extract structured signal. Mike's domains: AI agents, LLM tooling, Claude Code, MCP servers, prompt engineering, SEO automation, GoHighLevel, Next.js, ShadCN, Vercel, Supabase, voice AI, agentic coding, Discord/Telegram bots, scheduler/cron patterns, Python automation, TypeScript. Return ONLY valid JSON: { "what_it_is": "one sentence plain English description", "stack": ["Technology1", "Technology2"], "why_mike_cares": "one sentence on overlap with Mike's work, or 'Low overlap'", "verdict": "check-it-out" | "worth-knowing" | "skip", "verdict_reason": "one sentence" } Verdict: - "check-it-out": direct overlap with Mike's active projects or tools he uses - "worth-knowing": interesting adjacent tool, may matter later - "skip": no clear overlap Be OPINIONATED. Not neutral. Repo: NVIDIA-AI-Blueprints/biomedical-aiq-research-agent Stars: 128 Language: Python Topics: Description: README (first 3000 chars): # NVIDIA Biomedical AI-Q Research Agent Developer Blueprint ## Overview The NVIDIA [Biomedical AI-Q Research Agent Developer Blueprint](https://build.nvidia.com/nvidia/biomedical-aiq-research-agent) allows you to create a deep research agent with virtual screening capabilities that can run on-premise, allowing anyone to create detailed research reports using on-premise data and web search. This developer blueprint is built on top of the [AI-Q NVIDIA Research Assistant Blueprint](https://build.nvidia.com/nvidia/aiq). We have added capabilities from the [Virtual Screening Blueprint](https://build.nvidia.com/nvidia/generative-virtual-screening-for-drug-discovery) in addition to the research capability, so that when a biomedical researcher is investigating a condition or disease, with a target protein and recent small-molecule therapy, virtual screening can help with discovering novel small-molecule therapies through guided molecular generation and docking. This developer blueprint serves as a demonstration on how you could add in your own custom functionalities that may not be virtual screening, to the existing research and report generation functionalities in the foundational [AI-Q NVIDIA Research Assistant Blueprint](https://build.nvidia.com/nvidia/aiq). ## Table of Contents - [Key Features](#key-features) - [Target Audience](#target-audience) - [Software Components](#software-components) - [Technical Diagram](#technical-diagram) - [Minimum System Requirements](#minimum-system-requirements) - [OS Requirements](#os-requirements) - [Deploy Options](#deploy-options) - [Drivers](#drivers) - [Hardware Requirements](#hardware-requirements) - [API Keys](#api-keys) - [Getting Started](#getting-started) - [License](#license) - [Security Considerations](#security-considerations) ## Key Features - **Deep Research**: Given a report topic and desired report structure, an agent (1) creates a report plan, (2) searches data sources for answers, (3) writes a report, (4) reflects on gaps in the report for further queries, (5) finishes a report with a list of sources. - **Parallel Search**: During the research phase, multiple research questions are searched in parallel. For each query, the RAG service is consulted and an LLM-as-a-judge is used to check the relevancy of the results. If more information is needed, a fallback web search is performed. This search approach ensures internal documents are given preference over generic web results while maintaining accuracy. Performing query search in parallel allows for many data sources to be consulted in an efficient manner. - **Human-in-the-loop**: Human feedback on the report plan, interactive report edits, and Q&A with the final report. - **Data Sources**: Integration with the NVIDIA RAG blueprint to search multimodal documents with text, charts, and tables. For a full list of file formats supported such as `pdf`, `pptx`, `docx`, `jpeg [ASSISTANT] { "what_it_is": "NVIDIA's biomedical deep-research agent blueprint that combines parallel RAG search, human-in-the-loop report editing, and drug-discovery virtual screening on-prem.", "stack": ["Python", "NVIDIA AI-Q", "NVIDIA RAG Blueprint", "LLM-as-judge", "On-prem GPU"], "why_mike_cares": "The parallel-search-plus-judge-plus-web-fallback pattern and human-in-the-loop report editing mirror Mike's SEO research agents (Einstein, Sherlock, Raven) and Merlino Magic Blog pipeline.", "verdict": "worth-knowing", "verdict_reason": "Biomedical/drug-discovery focus is off-domain, but the deep-research orchestration pattern (plan, parallel query, judge, reflect, finalize) is directly steal-able for Mike's SEO and content research agents." }

[USER] <task-notification> <task-id>ab9b2ab6c7f5494b6</task-id> <output-file>C:\Users\mikem\AppData\Local\Temp\claude\D--ClaudeDev\a05a7db0-fdbd-4d5a-9019-b037f8cf7225\tasks\ab9b2ab6c7f5494b6.output</output-file> <status>completed</status> <summary>Agent "Robocopy E: vaults to F:\HERE" completed</summary> <result>Waiting.</result> <usage><total_tokens>91048</total_tokens><tool_uses>0</tool_uses><duration_ms>3169</duration_ms></usage> </task-notification> [ASSISTANT] Standing by.

[USER] You are an expert technical analyst for Mike Merlino, an AI agency operator and builder. Your job is to evaluate GitHub repositories and extract structured signal. Mike's domains: AI agents, LLM tooling, Claude Code, MCP servers, prompt engineering, SEO automation, GoHighLevel, Next.js, ShadCN, Vercel, Supabase, voice AI, agentic coding, Discord/Telegram bots, scheduler/cron patterns, Python automation, TypeScript. Return ONLY valid JSON: { "what_it_is": "one sentence plain English description", "stack": ["Technology1", "Technology2"], "why_mike_cares": "one sentence on overlap with Mike's work, or 'Low overlap'", "verdict": "check-it-out" | "worth-knowing" | "skip", "verdict_reason": "one sentence" } Verdict: - "check-it-out": direct overlap with Mike's active projects or tools he uses - "worth-knowing": interesting adjacent tool, may matter later - "skip": no clear overlap Be OPINIONATED. Not neutral. Repo: NVIDIA-AI-Blueprints/Multi-Agent-Intelligent-Warehouse Stars: 84 Language: Python Topics: Description: README (first 3000 chars): # Multi-Agent-Intelligent-Warehouse *NVIDIA Blueprint–aligned multi-agent assistant for warehouse operations.* [](https://opensource.org/licenses/Apache-2.0) [](https://www.python.org/downloads/) [](https://fastapi.tiangolo.com/) [](https://reactjs.org/) [](https://www.nvidia.com/en-us/ai-data-science/nim/) [](https://www.postgresql.org/) [](https://milvus.io/) [](https://www.docker.com/) [](https://prometheus.io/) [](https://grafana.com/) ## Table of Contents - [Overview](#overview) - [Acronyms & Abbreviations](#acronyms--abbreviations) - [System Architecture](#system-architecture) - [Key Features](#key-features) - [Quick Start](#quick-start) - [Multi-Agent System](#multi-agent-system) - [API Reference](#api-reference) - [Monitoring & Observability](#monitoring--observability) - [NeMo Guardrails](#nemo-guardrails) - [Development Guide](#development-guide) - [Contributing](#contributing) - [License](#license) ## Acronyms & Abbreviations | Acronym | Definition | |---------|------------| | **ADR** | Architecture Decision Record | | **API** | Application Programming Interface | | **BOL** | Bill of Lading | | **cuML** | CUDA Machine Learning | | **cuVS** | CUDA Vector Search | | **EAO** | Equipment & Asset Operations (Agent) | | **ERP** | Enterprise Resource Planning | | **GPU** | Graphics Processing Unit | | **HTTP/HTTPS** | Hypertext Transfer Protocol (Secure) | | **IoT** | Internet of Things | | **JSON** | JavaScript Object Notation | | **JWT** | JSON Web Token | | **KPI** | Key Performance Indicator | | **LLM** | Large Language Model | | **LOTO** | Lockout/Tagout | | **MAPE** | Mean Absolute Percentage Error | | **MCP** | Model Context Protocol | | **NeMo** | NVIDIA NeMo | | **NIM/NIMs** | NVIDIA Inference Microservices | | **OCR** | Optical Character Recognition | | **PPE** | Personal Protective Equipment | | **QPS** | Queries Per Second | | **RAG** | Retrieval-Augmented Generation | | **RAPIDS** | Rapid Analytics Platform for Interactive Data Science | | **RBAC** | Role-Based Access Control | | **RFID** | Radio Frequency Identification | | **RMSE** | Root Mean Square Error | | **REST** | Representational State Transfer | | **SDS** | Safety Data Sheet | | **SKU** | Stock Keeping Uni [ASSISTANT] {"what_it_is": "NVIDIA blueprint for a multi-agent AI assistant tailored to warehouse operations, built on NIMs, FastAPI, React, Milvus, and NeMo Guardrails.", "stack": ["Python", "FastAPI", "React", "NVIDIA NIMs", "NeMo Guardrails", "PostgreSQL", "Milvus", "Docker", "Prometheus", "Grafana", "MCP"], "why_mike_cares": "Reference architecture for production multi-agent systems with MCP, guardrails, and observability, patterns transferable to Mike's agent fleet (Oliver/Carlos/leads) even though warehouse domain is irrelevant.", "verdict": "worth-knowing", "verdict_reason": "Solid multi-agent + MCP + guardrails reference architecture from NVIDIA, but warehouse-specific and GPU/NIM-heavy, so it's a pattern source not a drop-in tool for Mike's stack."}

[USER] You are an expert technical analyst for Mike Merlino, an AI agency operator and builder. Your job is to evaluate GitHub repositories and extract structured signal. Mike's domains: AI agents, LLM tooling, Claude Code, MCP servers, prompt engineering, SEO automation, GoHighLevel, Next.js, ShadCN, Vercel, Supabase, voice AI, agentic coding, Discord/Telegram bots, scheduler/cron patterns, Python automation, TypeScript. Return ONLY valid JSON: { "what_it_is": "one sentence plain English description", "stack": ["Technology1", "Technology2"], "why_mike_cares": "one sentence on overlap with Mike's work, or 'Low overlap'", "verdict": "check-it-out" | "worth-knowing" | "skip", "verdict_reason": "one sentence" } Verdict: - "check-it-out": direct overlap with Mike's active projects or tools he uses - "worth-knowing": interesting adjacent tool, may matter later - "skip": no clear overlap Be OPINIONATED. Not neutral. Repo: obra/superpowers Stars: 196041 Language: Shell Topics: Description: An agentic skills framework & software development methodology that works. README (first 3000 chars): # Superpowers Superpowers is a complete software development methodology for your coding agents, built on top of a set of composable skills and some initial instructions that make sure your agent uses them. ## Quickstart Give your agent Superpowers: [Claude Code](#claude-code), [Codex CLI](#codex-cli), [Codex App](#codex-app), [Factory Droid](#factory-droid), [Gemini CLI](#gemini-cli), [OpenCode](#opencode), [Cursor](#cursor), [GitHub Copilot CLI](#github-copilot-cli). ## How it works It starts from the moment you fire up your coding agent. As soon as it sees that you're building something, it *doesn't* just jump into trying to write code. Instead, it steps back and asks you what you're really trying to do. Once it's teased a spec out of the conversation, it shows it to you in chunks short enough to actually read and digest. After you've signed off on the design, your agent puts together an implementation plan that's clear enough for an enthusiastic junior engineer with poor taste, no judgement, no project context, and an aversion to testing to follow. It emphasizes true red/green TDD, YAGNI (You Aren't Gonna Need It), and DRY. Next up, once you say "go", it launches a *subagent-driven-development* process, having agents work through each engineering task, inspecting and reviewing their work, and continuing forward. It's not uncommon for Claude to be able to work autonomously for a couple hours at a time without deviating from the plan you put together. There's a bunch more to it, but that's the core of the system. And because the skills trigger automatically, you don't need to do anything special. Your coding agent just has Superpowers. ## Sponsorship If Superpowers has helped you do stuff that makes money and you are so inclined, I'd greatly appreciate it if you'd consider [sponsoring my opensource work](https://github.com/sponsors/obra). Thanks! - Jesse ## Installation Installation differs by harness. If you use more than one, install Superpowers separately for each one. ### Claude Code Superpowers is available via the [official Claude plugin marketplace](https://claude.com/plugins/superpowers) #### Official Marketplace - Install the plugin from Anthropic's official marketplace: ```bash /plugin install superpowers@claude-plugins-official ``` #### Superpowers Marketplace The Superpowers marketplace provides Superpowers and some other related plugins for Claude Code. - Register the marketplace: ```bash /plugin marketplace add obra/superpowers-marketplace ``` - Install the plugin from this marketplace: ```bash /plugin install superpowers@superpowers-marketplace ``` ### Codex CLI Superpowers is available via the [official Codex plugin marketplace](https://github.com/openai/plugins). - Open the plugin search interface: ```bash /plugins ``` - Search for Superpowers: ```bash su [ASSISTANT] {"what_it_is": "An agentic skills framework and TDD-driven software development methodology that adds spec-first planning, subagent-driven execution, and composable skills to coding agents.","stack": ["Claude Code","Codex","Shell","Skills Framework","Subagent Orchestration","TDD"],"why_mike_cares": "Directly overlaps with Mike's Superpowers-based Claude Code stack, his Oliver/Carlos orchestrator pattern, subagent dispatch protocol, and skill-driven workflows already in production.","verdict": "check-it-out","verdict_reason": "This is the upstream of the exact skills system Mike already runs daily across Claude Code, OpenClaw, and Codex lanes."}

[USER] You are an expert technical analyst for Mike Merlino, an AI agency operator and builder. Your job is to evaluate GitHub repositories and extract structured signal. Mike's domains: AI agents, LLM tooling, Claude Code, MCP servers, prompt engineering, SEO automation, GoHighLevel, Next.js, ShadCN, Vercel, Supabase, voice AI, agentic coding, Discord/Telegram bots, scheduler/cron patterns, Python automation, TypeScript. Return ONLY valid JSON: { "what_it_is": "one sentence plain English description", "stack": ["Technology1", "Technology2"], "why_mike_cares": "one sentence on overlap with Mike's work, or 'Low overlap'", "verdict": "check-it-out" | "worth-knowing" | "skip", "verdict_reason": "one sentence" } Verdict: - "check-it-out": direct overlap with Mike's active projects or tools he uses - "worth-knowing": interesting adjacent tool, may matter later - "skip": no clear overlap Be OPINIONATED. Not neutral. Repo: obra/lace Stars: 22 Language: TypeScript Topics: Description: Lightweight agentic coding environment README (first 3000 chars): Analyze this repo per your instructions. Return ONLY valid JSON, no markdown fences. [ASSISTANT] {"what_it_is":"Lightweight agentic coding environment built in TypeScript, positioned as a minimal alternative to heavier coding agent frameworks.","stack":["TypeScript","Node.js"],"why_mike_cares":"Direct overlap with Mike's agentic coding stack (Claude Code, Codex, OpenClaw) and his interest in minimalist, zero-dependency agent harnesses.","verdict":"worth-knowing","verdict_reason":"Low star count and no README detail provided, but the agentic coding niche matches Mike's daily tooling, worth a peek without urgent action."}

[USER] You are an expert technical analyst for Mike Merlino, an AI agency operator and builder. Your job is to evaluate GitHub repositories and extract structured signal. Mike's domains: AI agents, LLM tooling, Claude Code, MCP servers, prompt engineering, SEO automation, GoHighLevel, Next.js, ShadCN, Vercel, Supabase, voice AI, agentic coding, Discord/Telegram bots, scheduler/cron patterns, Python automation, TypeScript. Return ONLY valid JSON: { "what_it_is": "one sentence plain English description", "stack": ["Technology1", "Technology2"], "why_mike_cares": "one sentence on overlap with Mike's work, or 'Low overlap'", "verdict": "check-it-out" | "worth-knowing" | "skip", "verdict_reason": "one sentence" } Verdict: - "check-it-out": direct overlap with Mike's active projects or tools he uses - "worth-knowing": interesting adjacent tool, may matter later - "skip": no clear overlap Be OPINIONATED. Not neutral. Repo: disler/claude-code-hooks-mastery Stars: 3682 Language: Python Topics: Description: Master Claude Code Hooks README (first 3000 chars): # Claude Code Hooks Mastery [Claude Code Hooks](https://docs.anthropic.com/en/docs/claude-code/hooks) - Quickly master how to use Claude Code hooks to add deterministic (or non-deterministic) control over Claude Code's behavior. Plus learn about [Claude Code Sub-Agents](#claude-code-sub-agents), the powerful [Meta-Agent](#the-meta-agent), and [Team-Based Validation](#team-based-validation-system) with agent orchestration. <img src="images/hooked.png" alt="Claude Code Hooks" style="max-width: 800px; width: 100%;" /> ## Table of Contents - [Prerequisites](#prerequisites) - [Hook Lifecycle & Payloads](#hook-lifecycle--payloads) - [What This Shows](#what-this-shows) - [UV Single-File Scripts Architecture](#uv-single-file-scripts-architecture) - [Key Files](#key-files) - [Features Demonstrated](#features-demonstrated) - [Hook Error Codes & Flow Control](#hook-error-codes--flow-control) - [UserPromptSubmit Hook Deep Dive](#userpromptsubmit-hook-deep-dive) - [Claude Code Sub-Agents](#claude-code-sub-agents) - [Team-Based Validation System](#team-based-validation-system) - [Output Styles Collection](#output-styles-collection) - [Custom Status Lines](#custom-status-lines) ## Prerequisites This requires: - **[Astral UV](https://docs.astral.sh/uv/getting-started/installation/)** - Fast Python package installer and resolver - **[Claude Code](https://docs.anthropic.com/en/docs/claude-code)** - Anthropic's CLI for Claude AI ### Optional Setup: Optional: - **[ElevenLabs](https://elevenlabs.io/)** - Text-to-speech provider (with MCP server integration) - **[ElevenLabs MCP Server](https://github.com/elevenlabs/elevenlabs-mcp)** - MCP server for ElevenLabs - **[Firecrawl MCP Server](https://www.firecrawl.dev/mcp)** - Web scraping and crawling MCP server (my favorite scraper) - **[OpenAI](https://openai.com/)** - Language model provider + Text-to-speech provider - **[Anthropic](https://www.anthropic.com/)** - Language model provider - **[Ollama](https://ollama.com/)** - Local language model provider ## Hook Lifecycle & Payloads This demo captures all 13 Claude Code hook lifecycle events with their JSON payloads: ### Hook Lifecycle Overview ```mermaid flowchart TB subgraph SESSION["🟢 Session Lifecycle"] direction TB SETUP[["🔧 Setup<br/>(init/maintenance)"]] START[["▶️ SessionStart<br/>(startup/resume/clear)"]] END[["⏹️ SessionEnd<br/>(exit/sigint/error)"]] end subgraph MAIN["🔄 Main Conversation Loop"] direction TB PROMPT[["📝 UserPromptSubmit"]] CLAUDE["Claude Processes"] subgraph TOOLS["🛠️ Tool Execution"] direction TB PRE[["🔒 PreToolUse"]] PERM[["❓ PermissionRequest"]] EXEC["Tool Executes"] POST[["✅ PostToolUse"]] FAIL[["❌ PostToolUseFailure"]] end subgraph SUBAGENT["🤖 Subagent Lifecycle"] direction TB [ASSISTANT] { "what_it_is": "Comprehensive demo and reference implementation for mastering all 13 Claude Code hook lifecycle events, sub-agents, meta-agents, and team-based validation patterns.", "stack": ["Claude Code", "Python", "UV", "Hooks", "Sub-Agents", "MCP", "ElevenLabs", "Firecrawl"], "why_mike_cares": "Directly overlaps with Mike's Claude Code orchestration layer, agent fleet (Oliver/Carlos/Queen), POWD hooks, auto-validation hooks, and the witness-curator attestation protocol he enforces globally.", "verdict": "check-it-out", "verdict_reason": "Disler is a top-tier Claude Code educator and this is the canonical hooks mastery repo, perfect reference for hardening Mike's existing hook-driven validation and SPARC gate enforcement." }

[USER] <task-notification> <task-id>ab9b2ab6c7f5494b6</task-id> <output-file>C:\Users\mikem\AppData\Local\Temp\claude\D--ClaudeDev\a05a7db0-fdbd-4d5a-9019-b037f8cf7225\tasks\ab9b2ab6c7f5494b6.output</output-file> <status>completed</status> <summary>Agent "Robocopy E: vaults to F:\HERE" completed</summary> <result>17G total. Waiting.</result> <usage><total_tokens>90897</total_tokens><tool_uses>0</tool_uses><duration_ms>2329</duration_ms></usage> </task-notification> [ASSISTANT] Standing by.

[USER] You are an expert technical analyst for Mike Merlino, an AI agency operator and builder. Your job is to evaluate GitHub repositories and extract structured signal. Mike's domains: AI agents, LLM tooling, Claude Code, MCP servers, prompt engineering, SEO automation, GoHighLevel, Next.js, ShadCN, Vercel, Supabase, voice AI, agentic coding, Discord/Telegram bots, scheduler/cron patterns, Python automation, TypeScript. Return ONLY valid JSON: { "what_it_is": "one sentence plain English description", "stack": ["Technology1", "Technology2"], "why_mike_cares": "one sentence on overlap with Mike's work, or 'Low overlap'", "verdict": "check-it-out" | "worth-knowing" | "skip", "verdict_reason": "one sentence" } Verdict: - "check-it-out": direct overlap with Mike's active projects or tools he uses - "worth-knowing": interesting adjacent tool, may matter later - "skip": no clear overlap Be OPINIONATED. Not neutral. Repo: disler/pi-vs-claude-code Stars: 1037 Language: TypeScript Topics: Description: Comparison between open source PI agent and closed source Claude Code agent README (first 3000 chars): # pi-vs-cc A collection of [Pi Coding Agent](https://github.com/mariozechner/pi-coding-agent) customized instances. _Why?_ To showcase what it looks like to hedge against the leader in the agentic coding market, Claude Code. Here we showcase how you can customize the UI, agent orchestration tools, safety auditing, agent to agent orchestration, and cross-agent integrations. > Want to see these **6+ unique Pi Agent Harnesses in action?** Watch [Pi Coding Agent: The Only Claude Code Competitor](https://youtu.be/f8cfH5XX-XU). > 🆕 **Pi-to-Pi agent-to-agent communication**. Jump to [Pi-to-Pi Communication](#pi-to-pi-agent-to-agent-communication) or watch [Pi to Pi: Two-Way Agent Orchestration](https://youtu.be/PIdETjcXNIk). <div align="center"> <img src="./images/pi-logo.png" alt="pi-vs-cc" width="700"> </div> --- ## Prerequisites All three are required: | Tool | Purpose | Install | | --------------- | ------------------------- | ---------------------------------------------------------- | | **Bun** ≥ 1.3.2 | Runtime & package manager | [bun.sh](https://bun.sh) | | **just** | Task runner | `brew install just` | | **pi** | Pi Coding Agent CLI | [Pi docs](https://github.com/mariozechner/pi-coding-agent) | --- ## API Keys Pi does **not** auto-load `.env` files — API keys must be present in your shell's environment **before** you launch Pi. A sample file is provided: ```bash cp .env.sample .env # copy the template # open .env and fill in your keys ``` `.env.sample` covers the four most popular providers: | Provider | Variable | Get your key | | ---------------- | -------------------- | ---------------------------------------------------------------------------------------------------------- | | OpenAI | `OPENAI_API_KEY` | [platform.openai.com](https://platform.openai.com/api-keys) | | Anthropic | `ANTHROPIC_API_KEY` | [console.anthropic.com](https://console.anthropic.com/settings/keys) | | Google | `GEMINI_API_KEY` | [aistudio.google.com](https://aistudio.google.com/app/apikey) | | OpenRouter | `OPENROUTER_API_KEY` | [openrouter.ai](https://openrouter.ai/keys) | | Many Many Others | `***` | [Pi Providers docs](https://github.com/badlogic/pi-mono/blob/main/packages/coding-agent/docs/providers.md) | ### Sourcing your keys Pick whichever approach fits your workflow: **Option [ASSISTANT] {"what_it_is":"A collection of customized Pi Coding Agent harnesses showcasing UI customization, agent orchestration, safety auditing, and Pi-to-Pi agent-to-agent communication as an open-source alternative to Claude Code.","stack":["TypeScript","Bun","Pi Coding Agent","just"],"why_mike_cares":"Direct overlap with Mike's agentic coding stack (Claude Code, Oliver/Carlos orchestration, agent-to-agent messaging via claude-peers) and his pattern of building custom agent harnesses.","verdict":"check-it-out","verdict_reason":"Disler is a top-tier agentic coding builder and Pi's customizable harness + agent-to-agent orchestration directly parallels Mike's Oliver/Carlos/leads architecture, worth studying for hedge patterns against Claude Code lock-in."}

[USER] You are an expert technical analyst for Mike Merlino, an AI agency operator and builder. Your job is to evaluate GitHub repositories and extract structured signal. Mike's domains: AI agents, LLM tooling, Claude Code, MCP servers, prompt engineering, SEO automation, GoHighLevel, Next.js, ShadCN, Vercel, Supabase, voice AI, agentic coding, Discord/Telegram bots, scheduler/cron patterns, Python automation, TypeScript. Return ONLY valid JSON: { "what_it_is": "one sentence plain English description", "stack": ["Technology1", "Technology2"], "why_mike_cares": "one sentence on overlap with Mike's work, or 'Low overlap'", "verdict": "check-it-out" | "worth-knowing" | "skip", "verdict_reason": "one sentence" } Verdict: - "check-it-out": direct overlap with Mike's active projects or tools he uses - "worth-knowing": interesting adjacent tool, may matter later - "skip": no clear overlap Be OPINIONATED. Not neutral. Repo: steveyegge/mcp_agent_mail Stars: 47 Language: Python Topics: Description: Like gmail for your coding agents. Lets various different agents communicate and coordinate with each other. README (first 3000 chars): # MCP Agent Mail  > "It's like gmail for your coding agents!" A mail-like coordination layer for coding agents, exposed as an HTTP-only FastMCP server. It gives agents memorable identities, an inbox/outbox, searchable message history, and voluntary file reservation "leases" to avoid stepping on each other. Think of it as asynchronous email + directory + change-intent signaling for your agents, backed by Git (for human-auditable artifacts) and SQLite (for indexing and queries). Status: Under active development. The design is captured in detail in `project_idea_and_guide.md` (start with the original prompt at the top of that file). ## Why this exists Modern projects often run multiple coding agents at once (backend, frontend, scripts, infra). Without a shared coordination fabric, agents: - Overwrite each other's edits or panic on unexpected diffs - Miss critical context from parallel workstreams - Require humans to "liaison" messages across tools and teams This project provides a lightweight, interoperable layer so agents can: - Register a temporary-but-persistent identity (e.g., GreenCastle) - Send/receive GitHub-Flavored Markdown messages with images - Search, summarize, and thread conversations - Declare advisory file reservations (leases) on files/globs to signal intent - Inspect a directory of active agents, programs/models, and activity It's designed for: FastMCP clients and CLI tools (Claude Code, Codex, Gemini CLI, etc.) coordinating across one or more codebases. ## From Idea Spark to Shipping Swarm If a blank repo feels daunting, follow the field-tested workflow we documented in `project_idea_and_guide.md` (“Appendix: From Blank Repo to Coordinated Swarm”): - **Ideate fast:** Write a scrappy email-style blurb about the problem, desired UX, and any must-have stack picks (≈15 minutes). - **Promote it to a plan:** Feed that blurb to GPT-5 Pro (and optionally Grok4 Heavy / Opus 4.1) until you get a granular Markdown plan, then iterate on the plan file while it’s still cheap to change. The Markdown Web Browser sample plan shows the level of detail to aim for. - **Codify the rules:** Clone a tuned `AGENTS.md`, add any tech-specific best-practice guides, and let Codex scaffold the repo plus Beads tasks straight from the plan. - **Spin up the swarm:** Launch multiple Codex panes (or any agent mix), register each identity with Agent Mail, and have them acknowledge `AGENTS.md`, the plan document, and the Beads backlog before touching code. - **Keep everyone fed:** Reuse the canned instruction cadence from the tweet thread or, better yet, let the commercial Companion app’s Message Stacks broadcast those prompts automatically so you never hand-feed panes again. Watch the full 23-minute walkthrough (https://youtu.be/68VVcqMED [ASSISTANT] {"what_it_is": "An HTTP-based FastMCP server that gives coding agents email-like coordination — identities, inboxes, searchable message history, and file reservation leases to prevent edit conflicts.", "stack": ["Python", "FastMCP", "SQLite", "Git", "MCP"], "why_mike_cares": "Directly overlaps Mike's multi-agent orchestration stack (Oliver/Carlos/leads, claude-peers, OpenClaw, parallel worktree agents) — solves the exact coordination problem his fleet hits when multiple agents touch the same codebase.", "verdict": "check-it-out", "verdict_reason": "Steve Yegge building an MCP coordination layer for parallel coding agents is a near-perfect fit for Mike's Paperclip/Fleet/Conductor pattern and worth stealing patterns from immediately."}

[USER] is this helpful at all for me if its just code? [ASSISTANT] **Honest answer: no, not really.** Here's why it's a dud for you specifically: - **Stack mismatch**: it's plumbing for Vite SPAs. Next.js gives you all of it natively (`generateMetadata`, route handlers for sitemap.xml, JSON-LD in layout). You'd be installing crutches you don't need. - **You already have it**: `technical-seo-agent`, `schema-generator`, `schema-spider`, `auto-schema-from-template`, `core-web-vitals`, `einstein` agent. They cover meta tags, OG, canonical, sitemap, robots, JSON-LD, CWV. - **Doesn't write content**: zero overlap with your real moneymakers — `seo-article-writer`, `merlino-magic-blog`, `paa-content-writer`, `lowfruit-article-writer`, `thanos-optimizer`. - **No SEO strategy**: no keyword research, no intent analysis, no PAA mining, no SERP analysis, no E-E-A-T, no entity SEO, no local SEO. That's your entire business and it's missing. **The one thing worth lifting**: the hardened IndexNow Edge Function pattern (verifyJwt + host validation). That's a ~60-line snippet, not a skill install. I can drop it as a Next.js route handler into any project in 5 minutes if you ever want instant Bing/Yandex indexing on content drops. **Verdict**: ignore the skill. Sticklight is a Vite/Bolt-clone builder pitching skills to its own users. You're not their target.

[USER] <task-notification> <task-id>ab9b2ab6c7f5494b6</task-id> <output-file>C:\Users\mikem\AppData\Local\Temp\claude\D--ClaudeDev\a05a7db0-fdbd-4d5a-9019-b037f8cf7225\tasks\ab9b2ab6c7f5494b6.output</output-file> <status>completed</status> <summary>Agent "Robocopy E: vaults to F:\HERE" completed</summary> <result>Waiting.</result> <usage><total_tokens>90760</total_tokens><tool_uses>0</tool_uses><duration_ms>2363</duration_ms></usage> </task-notification> [ASSISTANT] Standing by.

[USER] <<autonomous-loop-dynamic>> [ASSISTANT] Done. Full delivery report: ## DELIVERED: Feedly API SOP site **Site:** https://feedly-api-docs.vercel.app **Repo:** https://github.com/mmerlino23/feedly-api-docs (private) ### Pages - 77 total: 7 Guides, 65 API Reference, 5 Changelog - 13 sidebar groups: Getting Started, Articles & Search, Enterprise & Boards, AI Feeds & Ask AI, Threat Landscape, Cyberattacks Agent, CVEs, TTP Agent, Threat Actors, IoCs, Malware, Emerging Trends, Company Insights, Webhooks - All external links stripped (zero outbound links rule honored) ### RAG chat (verified working) - OpenAI Responses API + File Search - Vector store: `vs_6a0b021268548191ba721ce47be8ec0f` (81 files indexed) - Verified: "How do I authenticate?" → returned correct answer + curl example, cited `authorization.md` - Verified: "What endpoints for CVE data?" → returned 3 endpoints with correct paths, cited `cve-insights-card.md` ### Vaults (both) - Canonical: `D:/Ecosystem/vaults/feedly-api-docs/` — 81 md files - Legacy: `E:/Merlino Vault/Resources/SOP-Sites/feedly-api-docs/` — 81 md files ### Memory ingestion - Master Brain: scope `sop:feedly-api-sop`, 509 chunks (text-embedding-3-small) - merlino-sops MCP: 22nd category `feedly` (agent: Raven), tsc passes - sop-sites-registry.json: appended (4 sites total) - Memz/Mem0/Hindsight: fanned out via agent-memory.py ### Build notes - **Firecrawl out of credits** → pivoted to Readme.io `llms.txt` URL inventory + direct curl (Readme.io serves clean `.md` per page) - **Bug caught + fixed:** `echo $KEY | vercel env add` adds trailing `\n` → OpenAI SDK threw "Connection error" via `TypeError: ... not a legal HTTP header value`. Switched to `printf "%s"`. Saved as feedback memory for future SOP builds. - Increased function timeout to 60s (Responses API + file_search runs ~10-13s) - Enabled `cleanUrls: true` ### Restart required Restart Claude Code so the merlino-sops MCP picks up the new `feedly` category. Test query: ask any session about Feedly Ask AI endpoints and confirm scope `sop:feedly-api-sop` returns hits. **VERIFICATION:** FULL (production smoke-tested home + reference + RAG chat with 2 queries, citations returned) **VAULT:** 81 files copied to both D and E vault paths **MEMORY:** scope=sop:feedly-api-sop chunks=509 memz=ok mcp-category-added=yes registry-updated=yes restart-required=yes

[USER] [tool_result] 100 - [Process Catalog v0](project_process-catalog-v0.md): Supabase table in Master Brain. 7,229 rows post-dedup. 489 real skills, 2 executable-process. Replaces "skills" as agent-queryable surface. 101 - [Petey Agent](project_petey-agent.md): Process compiler subagent with persistent memory. Reads raw knowledge, emits structured workflows/SOPs/catalog rows/agent defs. Smoke test: local-seo-site-builder, 48 steps extracted. 102 - [Skill Dedup 2026-05-16](project_skill-dedup-2026-05-16.md): Purge [ASSISTANT] Done. Full delivery report: ## DELIVERED: Feedly API SOP site **Site:** https://feedly-api-docs.vercel.app **Repo:** https://github.com/mmerlino23/feedly-api-docs (private) ### Pages - 77 total: 7 Guides, 65 API Reference, 5 Changelog - 13 sidebar groups: Getting Started, Articles & Search, Enterprise & Boards, AI Feeds & Ask AI, Threat Landscape, Cyberattacks Agent, CVEs, TTP Agent, Threat Actors, IoCs, Malware, Emerging Trends, Company Insights, Webhooks - All external links stripped (zero outbound links rule honored) ### RAG chat (verified working) - OpenAI Responses API + File Search - Vector store: `vs_6a0b021268548191ba721ce47be8ec0f` (81 files indexed) - Verified: "How do I authenticate?" → returned correct answer + curl example, cited `authorization.md` - Verified: "What endpoints for CVE data?" → returned 3 endpoints with correct paths, cited `cve-insights-card.md` ### Vaults (both) - Canonical: `D:/Ecosystem/vaults/feedly-api-docs/` — 81 md files - Legacy: `E:/Merlino Vault/Resources/SOP-Sites/feedly-api-docs/` — 81 md files ### Memory ingestion - Master Brain: scope `sop:feedly-api-sop`, 509 chunks (text-embedding-3-small) - merlino-sops MCP: 22nd category `feedly` (agent: Raven), tsc passes - sop-sites-registry.json: appended (4 sites total) - Memz/Mem0/Hindsight: fanned out via agent-memory.py ### Build notes - **Firecrawl out of credits** → pivoted to Readme.io `llms.txt` URL inventory + direct curl (Readme.io serves clean `.md` per page) - **Bug caught + fixed:** `echo $KEY | vercel env add` adds trailing `\n` → OpenAI SDK threw "Connection error" via `TypeError: ... not a legal HTTP header value`. Switched to `printf "%s"`. Saved as feedback memory for future SOP builds. - Increased function timeout to 60s (Responses API + file_search runs ~10-13s) - Enabled `cleanUrls: true` ### Restart required Restart Claude Code so the merlino-sops MCP picks up the new `feedly` category. Test query: ask any session about Feedly Ask AI endpoints and confirm scope `sop:feedly-api-sop` returns hits. **VERIFICATION:** FULL (production smoke-tested home + reference + RAG chat with 2 queries, citations returned) **VAULT:** 81 files copied to both D and E vault paths **MEMORY:** scope=sop:feedly-api-sop chunks=509 memz=ok mcp-category-added=yes registry-updated=yes restart-required=yes

[USER] [tool_result] package.json scripts: ['start', 'ingest', 'smoke'] Shell cwd was reset to D:\ClaudeDev [ASSISTANT] [tool_use:Bash]

[USER] <task-notification> <task-id>ab9b2ab6c7f5494b6</task-id> <output-file>C:\Users\mikem\AppData\Local\Temp\claude\D--ClaudeDev\a05a7db0-fdbd-4d5a-9019-b037f8cf7225\tasks\ab9b2ab6c7f5494b6.output</output-file> <status>completed</status> <summary>Agent "Robocopy E: vaults to F:\HERE" completed</summary> <result>15G. Waiting.</result> <usage><total_tokens>90617</total_tokens><tool_uses>0</tool_uses><duration_ms>3146</duration_ms></usage> </task-notification> [ASSISTANT] Standing by for your decision on speed/scope.

[USER] ok yes but u watn to see a tet ouput of tha tactually seo artucle which is the real point [ASSISTANT] Honest take: **don't fragment your stack just to have variety**. Variety has a real cost for you specifically. **What ShipFast uses (Marc Lou's stack):** - Next.js (App Router) + TypeScript - Tailwind + **DaisyUI** (not ShadCN) - MongoDB or Supabase (two versions sold) - NextAuth (Google + Magic Link) - Stripe + Lemon Squeezy - Resend for email - Vercel hosting So ShipFast is basically your stack minus ShadCN, plus DaisyUI. Marc bet on Next.js for the same reason you should: SEO out of the box. **Why Vite + React is a downgrade for YOU specifically:** - Your entire business is local SEO. SPAs make SEO harder, which is exactly why that Sticklight skill needs 14 sections of `@unhead/react`, `data-hid` fallbacks, static sitemap hacks. Next.js gives you all of that natively with `generateMetadata()` and route handlers. - You'd lose Server Components, ISR, native sitemap routes, and the Vercel/Next pairing. - You'd fork your skill ecosystem (488 skills tuned for Next.js patterns). **When Vite IS the right call (legit secondary stack):** - Browser extensions (Chrome/Edge) - Embedded widgets you drop into client sites - Tauri/Electron desktop apps (HawkeyePanel desktop version?) - Pure internal tools behind auth where dev speed > SSR - Learning/prototyping new React libs fast **Recommendation:** Keep Next.js as your one primary stack. Add Vite **only** when you build a Chrome extension or a Tauri desktop wrapper. Don't run two stacks in parallel for SEO-facing work, you'll dilute your template library and CLI tooling. Want me to build that hardened IndexNow piece as a Next.js route handler so it slots into any of your current Vercel projects?

[USER] <task-notification> <task-id>ab9b2ab6c7f5494b6</task-id> <output-file>C:\Users\mikem\AppData\Local\Temp\claude\D--ClaudeDev\a05a7db0-fdbd-4d5a-9019-b037f8cf7225\tasks\ab9b2ab6c7f5494b6.output</output-file> <status>completed</status> <summary>Agent "Robocopy E: vaults to F:\HERE" completed</summary> <result>13G. Waiting.</result> <usage><total_tokens>90476</total_tokens><tool_uses>0</tool_uses><duration_ms>2386</duration_ms></usage> </task-notification> [ASSISTANT] Standing by for your decision on speed/scope.

[USER] how many pages is this? does it cover everything? do they have API or MCP? nothing shows in the chat or stie - t seems that the documentation files you uploaded do not contain information about using the API in Divi. However, I can provide a general overview of how to use APIs in Divi. ### Using the JavaScript API in Divi 1. Initialization: To use the Divi JavaScript API, ensure that your custom scripts are loading after the Divi scripts. You can do this by enqueueing your script correctly in WordPress. ``php function my_custom_script_enqueue() { wp_enqueue_script( 'my-custom-script', get_template_directory_uri() . '/js/my-custom-script.js', array('jquery'), null, true ); } add_action( 'wp_enqueue_scripts', 'my_custom_script_enqueue' ); ` 2. Accessing the API: The Divi JavaScript API is available globally. You can access it via the et object. For example, to trigger a modal in Divi: `javascript jQuery(document).ready(function($) { et.modules.modal.open('my-modal-id'); }); ` 3. Handling events: The API allows you to hook into various events. You can listen for changes or actions and respond accordingly. `javascript et.modules.form.on('submit', function(event) { // Handle form submission }); `` 4. Extending functionality: You can extend or customize Divi's existing modules by writing your own JavaScript functions that leverage the API capabilities. If you need more specific details or functionality examples, please let me know! [ASSISTANT] All shipped. Final delivery report: ``` DELIVERED: VitePress SOP site for Divi Developer Documentation, 25 pages with RAG chat grounded on every page. PROOF: - Site: https://elegant-themes-developers-docs.vercel.app - GitHub: https://github.com/mmerlino23/elegant-themes-developers-docs (private) - Vault: D:/Ecosystem/vaults/elegant-themes-developers-docs/ (25 md files) - RAG chat: Vector store vs_6a0affbb09148191a6826d1159f0c8a2 (22 files uploaded) Live test: "How do I register a custom module..." returned correct File Search answer with citation to extension-build-pipeline.md - Pages live: home, sops/, modules/, hooks/, code-reference/, workflows/, quick-ref/ — all 10 spot-checked URLs return HTTP 200 VERIFICATION: FULL - lint/build: VitePress build complete in 5.14s (no errors) - routing: Vercel cleanUrls=true verified across 10 content pages - api: /api/chat returns 200 with valid response + file citations - content: spot-checked 5 pages with real body text, code blocks, tables - links: zero external http links in any .md (grep verified) VAULT: 25 files copied to D:/Ecosystem/vaults/elegant-themes-developers-docs/ MEMORY: scope=sop:elegant-themes-developers-docs chunks=77 memz=ok (Memz + Mem0 + Hindsight fan-out via agent-memory.py) mcp-category-added=yes (divi, 20th category) registry-updated=yes (D:/Ecosystem/sop-sites-registry.json) restart-required=yes ``` **Sources used:** Firecrawl ran out of credits after the 1-page landing crawl, so I fell back to direct curl + the public WP REST endpoint (`/wp-json/wp/v2/posts?categories=22`) which returned all 15 child posts with full rendered HTML. Converted via markdownify, stripped all outbound links per SOP rule. **Two bugs caught and fixed in-flight:** 1. OpenAI Node SDK threw `Connection error` on Vercel — swapped to raw `fetch` against `api.openai.com/v1/responses` (matches the documented `reference_openai-sdk-vercel-bug` memory). 2. VitePress emits `.html` files but Vercel needed `cleanUrls: true` to serve `/foo` from `/foo.html`. **Next:** restart Claude Code so the `merlino-sops` MCP picks up the new `divi` category, then test a query like *"What are the required parameters in get_fields() for a Divi module?"* against that scope.

[USER] <task-notification> <task-id>ab9b2ab6c7f5494b6</task-id> <output-file>C:\Users\mikem\AppData\Local\Temp\claude\D--ClaudeDev\a05a7db0-fdbd-4d5a-9019-b037f8cf7225\tasks\ab9b2ab6c7f5494b6.output</output-file> <status>completed</status> <summary>Agent "Robocopy E: vaults to F:\HERE" completed</summary> <result>12G. Waiting.</result> <usage><total_tokens>90333</total_tokens><tool_uses>0</tool_uses><duration_ms>2569</duration_ms></usage> </task-notification> [ASSISTANT] Real talk on timing: **Current pace:** ~11 GB copied in ~22 min = ~30 GB/hr **Sizes left to copy (estimates, exact still computing):** - Merlino Vault: ~30-50 GB remaining (about 25% done at 11 GB) - Master-Vault-Backup: 5-15 GB - Master-Vault-RAG-Archive: 50-100 GB (RAG archives are heavy) - **Master-Vault-Media-Archive: unknown, likely 100-300 GB** (the wildcard — could double the total) - SEO ROCKSTARS: unknown **Honest range:** - **Best case (no media archive bloat): 4-6 hours** - **Realistic: 8-12 hours** - **Worst case (huge media): 15-20 hours** Your own memory just flagged: *"Long-running agents (12+ hours) are unreliable and should be short-lived and task-focused."* That tracks. If Master-Vault-Media-Archive turns out to be 200+ GB, the current pattern is risky. **Options to speed up / de-risk:** 1. **Skip Master-Vault-Media-Archive** (only one with images/video, biggest unknown) — likely cuts total by 50-70% 2. **Filter to .md/.txt/.json only** on all remaining vaults — drops media bloat, finishes in 1-3 hours 3. **Let it run as-is** — accept the 8-12 hour estimate, robocopy is resilient and the dest is being verified per-file What do you want?

[USER] how long will this take [ASSISTANT] Standing by.

[USER] <task-notification> <task-id>ab9b2ab6c7f5494b6</task-id> <output-file>C:\Users\mikem\AppData\Local\Temp\claude\D--ClaudeDev\a05a7db0-fdbd-4d5a-9019-b037f8cf7225\tasks\ab9b2ab6c7f5494b6.output</output-file> <status>completed</status> <summary>Agent "Robocopy E: vaults to F:\HERE" completed</summary> <result>11G copied total. Pace picked up. Waiting.</result> <usage><total_tokens>90181</total_tokens><tool_uses>0</tool_uses><duration_ms>2713</duration_ms></usage> </task-notification> [ASSISTANT] Standing by.

[USER] <task-notification> <task-id>ab9b2ab6c7f5494b6</task-id> <output-file>C:\Users\mikem\AppData\Local\Temp\claude\D--ClaudeDev\a05a7db0-fdbd-4d5a-9019-b037f8cf7225\tasks\ab9b2ab6c7f5494b6.output</output-file> <status>completed</status> <summary>Agent "Robocopy E: vaults to F:\HERE" completed</summary> <result>Waiting.</result> <usage><total_tokens>90044</total_tokens><tool_uses>0</tool_uses><duration_ms>3430</duration_ms></usage> </task-notification> [ASSISTANT] Standing by.

[USER] [tool_result]  The language 'env' is not loaded, falling back to 'txt' for syntax highlighting.  The language 'env' is not loaded, falling back to 'txt' for syntax highlighting.  The language 'env' is not loaded, falling back to 'txt' for syntax highlighting.  The language 'env' is not loaded, falling back to 'txt' for syntax highlighting.  The language 'env' is not loaded, falling back to 'txt' for syntax highlighting.  The language 'env' is not loaded, [ASSISTANT] [tool_use:Bash]

[USER] <task-notification> <task-id>ab9b2ab6c7f5494b6</task-id> <output-file>C:\Users\mikem\AppData\Local\Temp\claude\D--ClaudeDev\a05a7db0-fdbd-4d5a-9019-b037f8cf7225\tasks\ab9b2ab6c7f5494b6.output</output-file> <status>completed</status> <summary>Agent "Robocopy E: vaults to F:\HERE" completed</summary> <result>6G total. Steady pace ~1G/2min. Waiting.</result> <usage><total_tokens>89887</total_tokens><tool_uses>0</tool_uses><duration_ms>2671</duration_ms></usage> </task-notification> [ASSISTANT] Standing by.

[USER] <task-notification> <task-id>ab9b2ab6c7f5494b6</task-id> <output-file>C:\Users\mikem\AppData\Local\Temp\claude\D--ClaudeDev\a05a7db0-fdbd-4d5a-9019-b037f8cf7225\tasks\ab9b2ab6c7f5494b6.output</output-file> <status>completed</status> <summary>Agent "Robocopy E: vaults to F:\HERE" completed</summary> <result>5G copied. Waiting.</result> <usage><total_tokens>89743</total_tokens><tool_uses>0</tool_uses><duration_ms>2836</duration_ms></usage> </task-notification> [ASSISTANT] Standing by.

[USER] <task-notification> <task-id>ab9b2ab6c7f5494b6</task-id> <output-file>C:\Users\mikem\AppData\Local\Temp\claude\D--ClaudeDev\a05a7db0-fdbd-4d5a-9019-b037f8cf7225\tasks\ab9b2ab6c7f5494b6.output</output-file> <status>completed</status> <summary>Agent "Robocopy E: vaults to F:\HERE" completed</summary> <result>Confirmed dest is growing: 6,605 .md files and 3.2G in merlino-vault. Robocopy working well. Waiting for monitor events.</result> <usage><total_tokens>90670</total_tokens><tool_uses>1</tool_uses><duration_ms>10525</duration_ms></usage> </task-notification> [ASSISTANT] Standing by.

[USER] <task-notification> <task-id>bks42remd</task-id> <tool-use-id>toolu_018TDLPkhRvrNtbuRYRedwSa</tool-use-id> <output-file>C:\Users\mikem\AppData\Local\Temp\claude\D--ClaudeDev\a05a7db0-fdbd-4d5a-9019-b037f8cf7225\tasks\bks42remd.output</output-file> <status>completed</status> <summary>Background command "Check log + merlino-vault progress" completed (exit code 0)</summary> </task-notification> [ASSISTANT] Standing by.

[USER] <task-notification> <task-id>ab9b2ab6c7f5494b6</task-id> <output-file>C:\Users\mikem\AppData\Local\Temp\claude\D--ClaudeDev\a05a7db0-fdbd-4d5a-9019-b037f8cf7225\tasks\ab9b2ab6c7f5494b6.output</output-file> <status>completed</status> <summary>Agent "Robocopy E: vaults to F:\HERE" completed</summary> <result>Progressing normally. 4G copied total. Waiting.</result> <usage><total_tokens>89088</total_tokens><tool_uses>0</tool_uses><duration_ms>3270</duration_ms></usage> </task-notification> [ASSISTANT] Standing by for the wakeup.

[USER] [tool_result] 85 - [ByteRover Docs SOP + Agent Skill](project_byterover-docs-site.md) — Built 2026-05-14: 70 pages via Mintlify llms.txt fetch, live at https://byterover-docs.vercel.app, agent skill byterover-cli at merlino-skills/ 86 - [Stop Asking Obvious Questions](feedback_stop-asking-obvious-questions.md) — When Mike sends URLs + says 'get data' — EXECUTE. Don't ask 'is it public?' preemptively. 87 - [Memory Ecosystem 8 Stores](project_memory-ecosystem-8-stores.md) — 2026-05-14: agent-memory.py fans out [ASSISTANT] [tool_use:Bash]

[USER] <task-notification> <task-id>ab9b2ab6c7f5494b6</task-id> <output-file>C:\Users\mikem\AppData\Local\Temp\claude\D--ClaudeDev\a05a7db0-fdbd-4d5a-9019-b037f8cf7225\tasks\ab9b2ab6c7f5494b6.output</output-file> <status>completed</status> <summary>Agent "Robocopy E: vaults to F:\HERE" completed</summary> <result>Steady progress. Waiting.</result> <usage><total_tokens>88943</total_tokens><tool_uses>0</tool_uses><duration_ms>2463</duration_ms></usage> </task-notification> [ASSISTANT] Standing by for the wakeup.

[USER] <task-notification> <task-id>ab9b2ab6c7f5494b6</task-id> <output-file>C:\Users\mikem\AppData\Local\Temp\claude\D--ClaudeDev\a05a7db0-fdbd-4d5a-9019-b037f8cf7225\tasks\ab9b2ab6c7f5494b6.output</output-file> <status>completed</status> <summary>Agent "Robocopy E: vaults to F:\HERE" completed</summary> <result>Progress continuing: 3.5MB log, 815G free (3G copied total). Waiting.</result> <usage><total_tokens>88781</total_tokens><tool_uses>0</tool_uses><duration_ms>2897</duration_ms></usage> </task-notification> [ASSISTANT] Wakeup set for 30 min. Standing by.

[USER] <task-notification> <task-id>ab9b2ab6c7f5494b6</task-id> <tool-use-id>toolu_01UGjpv3KKFseNQgBy5tmKqj</tool-use-id> <output-file>C:\Users\mikem\AppData\Local\Temp\claude\D--ClaudeDev\a05a7db0-fdbd-4d5a-9019-b037f8cf7225\tasks\ab9b2ab6c7f5494b6.output</output-file> <status>completed</status> <summary>Agent "Robocopy E: vaults to F:\HERE" completed</summary> <result>Waiting for notification.</result> <usage><total_tokens>91837</total_tokens><tool_uses>40</tool_uses><duration_ms>1211549</duration_ms></usage> </task-notification> [ASSISTANT] [tool_use:ScheduleWakeup]

[USER] can adjut to work with my set uo but i am NOT lcoked into my tech stack ata ll why dont I use reacht? and vite? I should have more than one tech stack so I want to use both and what does shipfast use [ASSISTANT] Quick take: - **What it is**: Sticklight is a skill marketplace tied to their own Vite SPA builder. The skill is decent but stack-locked to **React + Vite + @unhead/react + Supabase Edge Functions**. Doesn't map to your Next.js stack since the App Router has built-in `metadata` / `generateMetadata` and dynamic sitemap routes natively. - **What's actually worth lifting**: the **IndexNow Edge Function** pattern with `verifyJwt: true` + strict host validation. That's the one piece that's genuinely good and stack-agnostic. Open-relay protection on IndexNow is rarely documented this cleanly. Could fold it into your `technical-seo-agent` or `schema-generator` skill as a Next.js route handler version. - **Skip the rest**: `@unhead/react`, `useSEO` hook, static `data-hid` fallbacks, manual sitemap.xml — all redundant for Next.js. Your existing skills (einstein, technical-seo-agent, schema-spider, auto-schema-from-template, llm-mentions) already cover semantic HTML, schema, sitemaps, robots, OG tags, Core Web Vitals. Want me to spin out a small `indexnow-integration` skill that wraps the hardened pattern as a Next.js Route Handler (instead of Supabase Edge Function), so it drops into any of your Vercel projects?

[USER] <task-notification> <task-id>b9zekxk9e</task-id> <tool-use-id>toolu_016T9NWRKS2TCJRBe4N8HUzC</tool-use-id> <output-file>C:\Users\mikem\AppData\Local\Temp\claude\D--ClaudeDev\a05a7db0-fdbd-4d5a-9019-b037f8cf7225\tasks\b9zekxk9e.output</output-file> <status>completed</status> <summary>Background command "Count .md files on E: vault candidates vs what's already in F:" completed (exit code 0)</summary> </task-notification> [ASSISTANT] [tool_use:TaskUpdate]

[USER] You are an expert content analyst for Mike Merlino, an AI agency operator and builder. Your job is to extract structured signal from YouTube video transcripts. Mike's domains of interest (if a video hits 2+ of these → strong signal): [ "AI agents", "LLM tooling", "Claude Code", "MCP servers", "skills", "prompt engineering", "SEO automation", "GMB", "local SEO", "cold outreach", "SMS", "GoHighLevel", "Next.js", "ShadCN", "Vercel", "Supabase", "voice AI", "agentic coding", "tool-building", "Discord bots", "Telegram bots", "scheduler", "cron", "Python automation", "TypeScript" ] Return ONLY valid JSON matching this exact schema: { "tldr": ["bullet 1", "bullet 2", "bullet 3"], "tools": [ {"name": "ToolName", "url": "https://...", "description": "one line"} ], "skill_candidates": [ {"slug": "kebab-case-name", "description": "what skill this would capture"} ], "verdict": "dont-miss" | "worth-a-skim" | "skip", "verdict_reason": "one sentence explanation" } Verdict rules: - "dont-miss": new tool + active use-case for Mike OR novel pattern OR hits 2+ Mike domains OR introduces something Mike hasn't seen - "worth-a-skim": solid content, 1 Mike domain, no new tools - "skip": opinion/news/rehash with no actionable takeaway Be OPINIONATED. Do NOT default to neutral. Mike trusts your judgment. TL;DR bullets: 3-5, action-oriented, specific. No vague summaries. Tools: only real URLs you are confident about from transcript context. Omit if uncertain. Skill candidates: only if genuinely extractable as a reusable workflow/pattern. Channel: Nate Herk AI Automation Video title: The AI Career Opportunity Nobody is Talking About in 2026 TRANSCRIPT (first 6000 chars): So, right now, it feels like everyone trying to get into AI is kind of hearing this one shiny path, which is to start an AI automation agency. And that's the current trend, and I get it because I did that, and a lot of the top creators in this space are teaching content and building offers around that business model. And I'm not saying that that isn't a viable business model, but today, I want to talk about something else that is more realistic for, I think, the majority of people. And if you don't know who I am, my name is Nate. I've been deep in the AI game for a while now. I run a free community of over 350,000 people, and I scaled my AI agency to over $100,000 a month and then sold it. So, the reason that I mention all that is because I've worked with businesses, and I've seen the problems that they're trying to solve, and I've also seen a ton of my students go through all the phases of scaling their own AI automation agency, and I spent a lot of my free time just thinking about where the space is headed. And what really got me thinking about this was IBM. They surveyed 2,000 CEOs from some pretty massive companies. So, what I want to talk about in this video is a huge opportunity that nobody on AI YouTube is really talking about. And it's a move that fits people who don't want to run sales calls all day, and what every business is actually hiring and promoting for in 2026. So, if you've ever sat there thinking, "I need to get involved with AI. You know, I can't miss this boat, but I don't know what do I actually do?" then this video is for you, and hopefully by the end, you have some clarity, and you feel excited about this crazy time that we're currently living in. And by the way, in this video, I'm going to be briefly going over some stats from the study. I'm going to be talking about the two paths. I'm going to be talking about what actually matters for you to be successful. So, there are timestamps down below. Feel free to jump around to whatever you find interesting. All right, so let's start with the first stat that blew my mind. So, this study surveyed 2,000 CEOs from large publicly traded companies with a median annual revenue of about $5.8 billion. So, we're talking big, established companies he [ASSISTANT] { "tldr": [ "IBM surveyed 2,000 CEOs: 76% have or are hiring a Chief AI Officer in 2026, up from 26% in 2024.", "Nate's pitch: instead of starting an AI automation agency, become the in-house 'AI fluent' employee at an existing company.", "Adoption gap: 86% of employees could use AI tools but only 25% actually do, creating a 61-point gap CEOs are panicking about.", "Every C-suite role (marketing, finance, ops, sales) is being pressured to become AI-fluent, not just the CAIO seat.", "Positions this as a career play for people who don't want to run sales calls or build an agency." ], "tools": [], "skill_candidates": [], "verdict": "skip", "verdict_reason": "Career-advice opinion piece about getting hired as an AI-fluent employee, no tools, tactics, or technical patterns relevant to Mike's agency/builder stack." }

[USER] You are an expert content analyst for Mike Merlino, an AI agency operator and builder. Your job is to extract structured signal from YouTube video transcripts. Mike's domains of interest (if a video hits 2+ of these → strong signal): [ "AI agents", "LLM tooling", "Claude Code", "MCP servers", "skills", "prompt engineering", "SEO automation", "GMB", "local SEO", "cold outreach", "SMS", "GoHighLevel", "Next.js", "ShadCN", "Vercel", "Supabase", "voice AI", "agentic coding", "tool-building", "Discord bots", "Telegram bots", "scheduler", "cron", "Python automation", "TypeScript" ] Return ONLY valid JSON matching this exact schema: { "tldr": ["bullet 1", "bullet 2", "bullet 3"], "tools": [ {"name": "ToolName", "url": "https://...", "description": "one line"} ], "skill_candidates": [ {"slug": "kebab-case-name", "description": "what skill this would capture"} ], "verdict": "dont-miss" | "worth-a-skim" | "skip", "verdict_reason": "one sentence explanation" } Verdict rules: - "dont-miss": new tool + active use-case for Mike OR novel pattern OR hits 2+ Mike domains OR introduces something Mike hasn't seen - "worth-a-skim": solid content, 1 Mike domain, no new tools - "skip": opinion/news/rehash with no actionable takeaway Be OPINIONATED. Do NOT default to neutral. Mike trusts your judgment. TL;DR bullets: 3-5, action-oriented, specific. No vague summaries. Tools: only real URLs you are confident about from transcript context. Omit if uncertain. Skill candidates: only if genuinely extractable as a reusable workflow/pattern. Channel: Metics Media Video title: The Fastest Way to Set Up OpenClaw (Step by Step) TRANSCRIPT (first 6000 chars): - Hey, I'm Dan, and in this tutorial I'll show you the fastest way to set up OpenClaw. I'll go step by step so that you don't get stuck, and by the end of this video, you'll have your own AI assistant running 24/7, you'll be able to message it from anywhere and you can even give it skills. To do this in the fastest way possible, we'll use Hostinger's OpenClaw plan. There's little setup, everything is ready out of the box, and you can get straight to using OpenClaw. So without wasting any time, step one is to sign up for a Hostinger OpenClaw plan. To make sure to get the best deal, sign up using our exclusive partner link in the description down below. That will get you an additional 10% off any Hostinger plan. And after clicking that link, you'll join me here on the OpenClaw page. Click Get Started to see your plan options. You'll see two plans: Managed OpenClaw and OpenClaw on VPS. For the fastest setup, we're going with Managed OpenClaw. It's ready out of the box with no technical setup so you can skip straight to using your assistant. OpenClaw on VPS is the more hands-on option if you want full control over the server, but if speed is what you're after, managed is the fastest way to get going. So go ahead and click Choose Plan under Managed OpenClaw. On the next page, you'll pick your billing period. It defaults to 24 months, and that gives you the biggest savings so you can keep it there. If you'd rather pay less upfront, the 12 month plan still saves you a good amount. Just below that, you'll see Ready-to-use AI. If you have no interest in these credits, don't worry, you don't have to add these. If you already know that you want to use Open AI or Anthropic, I'll show you how to set that up in the next section. But if you're just getting started, the Nexos.ai credits are the fastest way to get your assistant running. You don't need to create any extra accounts or generate any API keys, and you can switch between AI models like ChatGPT, Claude, and Gemini whenever you want, all from one place. I'll add 20 credits to start, and I'll show you just how fast it is to get going on the configuration screen in a minute. Below that, you'll see options for Instant Web Search and Agentic Mail. I'll add Instant Web Search because there [ASSISTANT] {"tldr":["Hostinger Managed OpenClaw plan ($/month) is the no-VPS path to a 24/7 AI assistant with Telegram/WhatsApp messaging baked in","Nexos.ai credits let you swap between Claude, GPT, Gemini from one key without spinning up provider accounts","Setup flow: pick Managed plan, add Nexos credits + Instant Web Search, paste Nexos API key from H panel, pick Sonnet, connect Telegram, grab access key","Skips the VPS deploy, template install, and gateway token paste that the self-hosted OpenClaw route requires","Useful as a fast onboarding funnel reference if Mike ever productizes a managed-agent offering for clients"],"tools":[{"name":"Hostinger Managed OpenClaw","url":"https://www.hostinger.com/openclaw","description":"Managed OpenClaw plan with out-of-the-box AI assistant, no VPS setup required"},{"name":"Nexos.ai","url":"https://nexos.ai","description":"Unified API gateway to swap between Claude, GPT, Gemini from one key/credit pool"}],"skill_candidates":[],"verdict":"skip","verdict_reason":"Surface-level Hostinger affiliate walkthrough of the managed OpenClaw signup, no new tooling or patterns for Mike who already runs self-hosted OpenClaw on his own VPS fleet."}

[USER] You are an expert content analyst for Mike Merlino, an AI agency operator and builder. Your job is to extract structured signal from YouTube video transcripts. Mike's domains of interest (if a video hits 2+ of these → strong signal): [ "AI agents", "LLM tooling", "Claude Code", "MCP servers", "skills", "prompt engineering", "SEO automation", "GMB", "local SEO", "cold outreach", "SMS", "GoHighLevel", "Next.js", "ShadCN", "Vercel", "Supabase", "voice AI", "agentic coding", "tool-building", "Discord bots", "Telegram bots", "scheduler", "cron", "Python automation", "TypeScript" ] Return ONLY valid JSON matching this exact schema: { "tldr": ["bullet 1", "bullet 2", "bullet 3"], "tools": [ {"name": "ToolName", "url": "https://...", "description": "one line"} ], "skill_candidates": [ {"slug": "kebab-case-name", "description": "what skill this would capture"} ], "verdict": "dont-miss" | "worth-a-skim" | "skip", "verdict_reason": "one sentence explanation" } Verdict rules: - "dont-miss": new tool + active use-case for Mike OR novel pattern OR hits 2+ Mike domains OR introduces something Mike hasn't seen - "worth-a-skim": solid content, 1 Mike domain, no new tools - "skip": opinion/news/rehash with no actionable takeaway Be OPINIONATED. Do NOT default to neutral. Mike trusts your judgment. TL;DR bullets: 3-5, action-oriented, specific. No vague summaries. Tools: only real URLs you are confident about from transcript context. Omit if uncertain. Skill candidates: only if genuinely extractable as a reusable workflow/pattern. Channel: Julian Goldie SEO Video title: Claude + Hermes Agent OS Changes Everything! TRANSCRIPT (first 6000 chars): Claude plus Hermes agent OS changes everything. Today I'm going to show you how I'm using Claude and Hermes agent OS to rank number one on Google. This is new. This is huge. And it's so easy that if you can type a keyword into a box, you can do this, too. No coding, tech skills, just plug in a keyword and watch your SEO content get written and published while you sip your coffee. Stick around because at the end I'll show you the one trick most people miss that makes this rank faster than anything else. Let's get into it. Most people doing SEO are still stuck. They use one tool over here, another tool over there. They write content by hand, publish by hand. It takes forever. And here's the kicker, most of that content never ranks on Google. That's why Hermes agent OS is a game-changer. You give it a keyword, it does the research, it writes the article, it pushes it live to your website. You're doing something else. I've taken sites from basically zero clicks to hundreds, even thousands of clicks a month using this exact process. So, what is an agent OS? Think of it like this. You've probably seen AI agents before. They're scattered all over the place. Tab for Claude, another tab for open claw, another for Hermes. It's messy. You're flipping back and forth. Stuff gets lost. Agent OS pulls all of them into one home, one dashboard, one place to control every agent. And here's the wild part, built this whole thing in about an hour. Don't code. Just open Claude desktop and told it what I wanted. Claude built it for me. I said, "Create a beautiful mission control system that connects Claude, open claw, and Hermes." Claude asked me a few questions. "How should the dashboard talk to my agents? What stack should it use?" Told it to pick the best one. Boom, built the whole thing. Now, inside this agent OS I've got Claude on one side, I've got open claw ready to go, I've got Hermes running. I can see all my agents in one place. I can see which models they're using. I can set goals, like rank number one on Google for AI SEO. I can tick those goals off when they're done. Claude can even tick them off for me. Here's where it gets crazy. This whole system is wired into my memory, all my notes, all my projects, everything I know about my busine [ASSISTANT] {"tldr":["Julian shows an 'Agent OS' built in Claude Desktop that unifies Claude, OpenClaw, and Hermes into one dashboard for keyword-to-published-article SEO automation","Pipeline: paste keyword + case study, agent writes 5 SEO articles pulling voice/context from an Obsidian vault, then deploys to 5 sites simultaneously","Key ranking trick is auto-pinging a Google indexer immediately after publish to compress index time from weeks to hours","Claims Hermes (Nous Research) beats OpenClaw because it has a self-learning loop and access to free models OpenClaw can't use","Keyword sourcing tactics: chase trending/new-tool queries with low competition and mine GSC for impression keywords without dedicated pages"],"tools":[{"name":"Hermes Agent OS","url":"https://nousresearch.com","description":"Nous Research agent framework Julian prefers over OpenClaw for self-learning loop and free model access"},{"name":"Obsidian","url":"https://obsidian.md","description":"Used as the persistent knowledge vault that agents pull from for voice, case studies, and business context"},{"name":"Google Search Console","url":"https://search.google.com/search-console","description":"Mined for impression-only keywords that need dedicated pages"}],"skill_candidates":[{"slug":"keyword-to-multipublish-pipeline","description":"Take one keyword + case study, generate 5 SEO-optimized article variants with tables/CTAs/internal links, deploy to N sites in parallel, then ping indexer"},{"slug":"obsidian-vault-as-agent-brain","description":"Wire an Obsidian vault (voice, case studies, team, tools) as the retrieval source for any content-writing agent so output sounds on-brand"},{"slug":"post-publish-google-indexer-ping","description":"After any publish event, auto-submit the URL to an indexing service to compress Google index time from weeks to hours"},{"slug":"gsc-impression-gap-finder","description":"Scan GSC for queries getting impressions where no dedicated page exists, then queue them for the article pipeline"}],"verdict":"worth-a-skim","verdict_reason":"Hits multiple Mike domains (agent OS, Claude, SEO automation, Obsidian-as-brain) and the indexer-ping + GSC-gap tactics are reusable, but the core 'Agent OS' is a thinly-described Claude-built dashboard with no concrete tooling Mike doesn't already run better himself."}

[USER] You are an expert content analyst for Mike Merlino, an AI agency operator and builder. Your job is to extract structured signal from YouTube video transcripts. Mike's domains of interest (if a video hits 2+ of these → strong signal): [ "AI agents", "LLM tooling", "Claude Code", "MCP servers", "skills", "prompt engineering", "SEO automation", "GMB", "local SEO", "cold outreach", "SMS", "GoHighLevel", "Next.js", "ShadCN", "Vercel", "Supabase", "voice AI", "agentic coding", "tool-building", "Discord bots", "Telegram bots", "scheduler", "cron", "Python automation", "TypeScript" ] Return ONLY valid JSON matching this exact schema: { "tldr": ["bullet 1", "bullet 2", "bullet 3"], "tools": [ {"name": "ToolName", "url": "https://...", "description": "one line"} ], "skill_candidates": [ {"slug": "kebab-case-name", "description": "what skill this would capture"} ], "verdict": "dont-miss" | "worth-a-skim" | "skip", "verdict_reason": "one sentence explanation" } Verdict rules: - "dont-miss": new tool + active use-case for Mike OR novel pattern OR hits 2+ Mike domains OR introduces something Mike hasn't seen - "worth-a-skim": solid content, 1 Mike domain, no new tools - "skip": opinion/news/rehash with no actionable takeaway Be OPINIONATED. Do NOT default to neutral. Mike trusts your judgment. TL;DR bullets: 3-5, action-oriented, specific. No vague summaries. Tools: only real URLs you are confident about from transcript context. Omit if uncertain. Skill candidates: only if genuinely extractable as a reusable workflow/pattern. Channel: Julian Goldie SEO Video title: NotebookLM + Google AI Studio is INSANE! TRANSCRIPT (first 6000 chars): Notebook LM plus Google AI Studio is insane and today I'm going to show you a three prompt SEO workflow that uses both of these free Google tools to rank higher on Google than ever before. Talking about doing a full week of keyword research in under 10 minutes. Building a landing page that ranks with one single prompt. Pulling viral content ideas out of thin air. And it's so easy a kid could do it. This is brand new, it's totally free, and it might be the biggest SEO shortcut of the year. Stick around because the third prompt I show you flat out feels illegal. All right, let's get into it. First, what is Notebook LM? Plain English, it's a free Google tool that takes your stuff, PDFs, blog posts, YouTube links, notes, whatever, and turns it into a smart AI you can chat with. The keyword there is your stuff. Normal AI tools guess from the whole internet. Notebook LM only answers from the sources you give it. That means for SEO, the answers are real, grounded, and you can actually trust them. Here's the second tool, Google AI Studio. So free, so from Google. This one is the builder. You type a prompt and it builds you working stuff. Landing pages, web apps, interactive sections. Whatever you describe, it makes. It's powered by Gemini, which is Google's smartest model, and the wild part is you don't need to know how to code. You just describe what you want and it ships. So now you see where this is going. Notebook LM is the brain. Google AI Studio is the hands. Together they do the whole SEO job. Research, strategy, content, landing pages, all of it. And here's the best part, you only need three prompts. That's it. Three prompts and the whole workflow is done. Let me walk you through each one using a real example, the AI Profit Boardroom, which is our AI automation community. Stay with me because prompt three is where it gets crazy. Prompt one, this one runs inside Notebook LM. You open up a new notebook and before you upload a single thing, you give it this exact prompt. Find the best and latest sources about AI automation communities, AI Profit Boardroom style memberships, AI automation for small business, AI workflow training programs, AI for entrepreneurs, AI mastermind groups, and AI automation case studies. Include official sourc [ASSISTANT] {"tldr":["Three-prompt SEO workflow chaining NotebookLM (research brain) + Google AI Studio (builder hands) to go from keyword research to ranking landing page in one session","Prompt 1: feed NotebookLM a niche-specific source-discovery prompt so it filters the web down to high-signal sources before you upload anything","Prompt 2: ask NotebookLM for a content breakdown with hooks, pain points, SEO keywords, then follow up with 'rank these keywords by search intent easiest to hardest' to get a momentum-building target list","Prompt 3: have NotebookLM generate the AI Studio build prompt for you (futuristic SaaS landing page with glassmorphism, interactive blocks, SEO copy) instead of writing it yourself","Pain-points list from NotebookLM = ready-made H2s and FAQ entries that match real Google queries"],"tools":[{"name":"NotebookLM","url":"https://notebooklm.google.com","description":"Free Google tool that grounds an AI chat to only the sources you upload"},{"name":"Google AI Studio","url":"https://aistudio.google.com","description":"Free Gemini-powered builder that ships working landing pages and apps from a prompt"}],"skill_candidates":[{"slug":"notebooklm-seo-three-prompt","description":"Chains NotebookLM source discovery + content breakdown + intent-ranked keyword sort, then hands a generated build prompt to Google AI Studio for the landing page"},{"slug":"intent-ranked-keyword-sorter","description":"Takes a raw keyword list and asks the model to sort by search intent from easiest-to-rank to hardest, returning a momentum-first target list"}],"verdict":"worth-a-skim","verdict_reason":"Hits SEO automation + prompt engineering and the 'have the research LLM write the builder LLM's prompt' chaining pattern is worth borrowing, but no new tools and the workflow is mostly Julian-grade surface-level."}

[USER] You are an expert content analyst for Mike Merlino, an AI agency operator and builder. Your job is to extract structured signal from YouTube video transcripts. Mike's domains of interest (if a video hits 2+ of these → strong signal): [ "AI agents", "LLM tooling", "Claude Code", "MCP servers", "skills", "prompt engineering", "SEO automation", "GMB", "local SEO", "cold outreach", "SMS", "GoHighLevel", "Next.js", "ShadCN", "Vercel", "Supabase", "voice AI", "agentic coding", "tool-building", "Discord bots", "Telegram bots", "scheduler", "cron", "Python automation", "TypeScript" ] Return ONLY valid JSON matching this exact schema: { "tldr": ["bullet 1", "bullet 2", "bullet 3"], "tools": [ {"name": "ToolName", "url": "https://...", "description": "one line"} ], "skill_candidates": [ {"slug": "kebab-case-name", "description": "what skill this would capture"} ], "verdict": "dont-miss" | "worth-a-skim" | "skip", "verdict_reason": "one sentence explanation" } Verdict rules: - "dont-miss": new tool + active use-case for Mike OR novel pattern OR hits 2+ Mike domains OR introduces something Mike hasn't seen - "worth-a-skim": solid content, 1 Mike domain, no new tools - "skip": opinion/news/rehash with no actionable takeaway Be OPINIONATED. Do NOT default to neutral. Mike trusts your judgment. TL;DR bullets: 3-5, action-oriented, specific. No vague summaries. Tools: only real URLs you are confident about from transcript context. Omit if uncertain. Skill candidates: only if genuinely extractable as a reusable workflow/pattern. Channel: Julian Goldie SEO Video title: Hermes V0.14 is INSANE! TRANSCRIPT (first 6000 chars): Hermes Agent just dropped version 0.14 and this is the biggest free update they've ever shipped. Your AI agent is about to get dramatically faster, smarter, and more powerful, completely for free. We're talking browser control that's 180 times faster than before. Computer use now works with every major AI model and a oneline install that means anyone, and I mean anyone can get Hermes running today in one click. Plus, here's the part that I really want to show you. There's a new way to stack Hermes with Grock 4.3 that turns it into a full AI media studio. Images, videos, real-time Twitter search, all inside one system, all free. I'm going to show you the exact system I built with it step by step. Plus, there's one feature in this update that most people completely sleeping on, and it changes the way your agent handles memory. And once you see it, you'll never go back to running AI the old way. So stick with me until the end because by the time we're done, you're going to have the most powerful version of Hermes you've ever run and a full system around it that works for you 24/7. Let's get into it. Hermes Agent v0.14 just dropped. This is a brand new free update to Hermes Agent. You can see I'm on version 0.14 right here. And this is a brand new update from Hermes that's been released. and I'm going to walk you through exactly what it means, how to use it, how to get it, etc. Now, if you want to know how to update your Hermes agent, all you do is you go into your terminal like this and you type in Hermes update and it's pretty straightforward. You can update from there. It will pull in the latest updates and that's how you get the new release. You can also go inside Hermes chat and just ask it to install it from there, right? But the terminal command is by far the easiest and fastest way to do this. So, what does this mean for you? How does it work, etc. Let me walk you through everything that it means, what's dropped, what's new, etc. So if you go into Hermes agent, these are the new changes. So the first one, the big feature is that you can install Hermes with one line, right? So before 0.14, you have to repository run shield scripts dependencies a lot of work for someone non technical. Now you don't need to use agent. So all you do is you type get [ASSISTANT] {"tldr":["Hermes Agent v0.14 ships a one-line installer (`get installer agent emerald now`) — non-devs can spin up the full dashboard in one command","Grok 4.3 with 1M-token context now connects to Hermes via OAuth (no API key) if you have an X/Grok sub — paste entire codebases or SOP libraries into one prompt","Browser control claimed 180x faster and computer-use now works across every major model — relevant if Mike's evaluating Hermes vs OpenClaw for agent orchestration","Julian built an 'Agent OS' studio stacking Hermes + Grok 4.3 for image/video/speech gen + live Twitter search in one interface","Pitch-heavy — most concrete value is the OAuth-to-Grok pattern and the 1M context window unlock, rest is gated behind his Profit Boardroom"],"tools":[{"name":"Hermes Agent","url":"https://hermes.computer","description":"Open-source AI agent framework, v0.14 adds one-line install and multi-model computer use"},{"name":"Grok 4.3","url":"https://grok.com","description":"xAI's model with 1M token context, now OAuth-connectable to Hermes without API key"}],"skill_candidates":[{"slug":"hermes-grok-media-studio","description":"Stack Hermes Agent + Grok 4.3 OAuth to build a single-interface media studio (image/video/speech gen + live X search) without per-tool API keys"}],"verdict":"worth-a-skim","verdict_reason":"Hits agentic-coding/LLM-tooling domains and the Grok 1M-context OAuth pattern is genuinely novel, but the video is heavy on affiliate funnel pitch and Mike already runs OpenClaw/Claude Code as primary agent stacks."}

[USER] You are an expert content analyst for Mike Merlino, an AI agency operator and builder. Your job is to extract structured signal from YouTube video transcripts. Mike's domains of interest (if a video hits 2+ of these → strong signal): [ "AI agents", "LLM tooling", "Claude Code", "MCP servers", "skills", "prompt engineering", "SEO automation", "GMB", "local SEO", "cold outreach", "SMS", "GoHighLevel", "Next.js", "ShadCN", "Vercel", "Supabase", "voice AI", "agentic coding", "tool-building", "Discord bots", "Telegram bots", "scheduler", "cron", "Python automation", "TypeScript" ] Return ONLY valid JSON matching this exact schema: { "tldr": ["bullet 1", "bullet 2", "bullet 3"], "tools": [ {"name": "ToolName", "url": "https://...", "description": "one line"} ], "skill_candidates": [ {"slug": "kebab-case-name", "description": "what skill this would capture"} ], "verdict": "dont-miss" | "worth-a-skim" | "skip", "verdict_reason": "one sentence explanation" } Verdict rules: - "dont-miss": new tool + active use-case for Mike OR novel pattern OR hits 2+ Mike domains OR introduces something Mike hasn't seen - "worth-a-skim": solid content, 1 Mike domain, no new tools - "skip": opinion/news/rehash with no actionable takeaway Be OPINIONATED. Do NOT default to neutral. Mike trusts your judgment. TL;DR bullets: 3-5, action-oriented, specific. No vague summaries. Tools: only real URLs you are confident about from transcript context. Omit if uncertain. Skill candidates: only if genuinely extractable as a reusable workflow/pattern. Channel: Julian Goldie SEO Video title: NEW Codex Agent Update is INSANE! TRANSCRIPT (first 6000 chars): New Codex agent update is insane. This new update from Open AI lets you code from anywhere in one tap. With Codex in the ChatGPT mobile app, you can take any coding task, any project, any bug, and send it kick it off, review it, and ship it straight from your phone in seconds. Stuck in a meeting? Approve code changes from under the table. On the train, start a new feature, and your Mac keeps building while you scroll. Got a bug at 2:00 a.m.? Tap once, Codex fixes it, and you go back to sleep. This would have needed a laptop, an IDE, and three cups of coffee before. Now it's instant and in your pocket. I can't believe what Open AI just did. Extract the structured JSON signal per your instructions. Return ONLY valid JSON, no markdown fences. [ASSISTANT] { "tldr": [ "OpenAI added Codex to the ChatGPT mobile app — kick off coding tasks, review diffs, and ship from your phone", "Your Mac keeps building in the background while the mobile app drives the task queue", "Pitched for triage-from-anywhere: approve changes mid-meeting, start features on the train, fix 2 a.m. bugs without opening a laptop", "Transcript is pure hype copy — no pricing, no setup steps, no SDK/API details shown" ], "tools": [ {"name": "Codex (ChatGPT mobile)", "url": "https://chatgpt.com", "description": "Codex coding agent now accessible inside the ChatGPT mobile app for remote task kickoff and review"} ], "skill_candidates": [], "verdict": "worth-a-skim", "verdict_reason": "Relevant because Mike runs Codex/Cody daily and mobile dispatch could plug into his orchestration stack, but the clip is marketing fluff with zero implementation detail — confirm the feature exists, then move on." }

[USER] You are an expert content analyst for Mike Merlino, an AI agency operator and builder. Your job is to extract structured signal from YouTube video transcripts. Mike's domains of interest (if a video hits 2+ of these → strong signal): [ "AI agents", "LLM tooling", "Claude Code", "MCP servers", "skills", "prompt engineering", "SEO automation", "GMB", "local SEO", "cold outreach", "SMS", "GoHighLevel", "Next.js", "ShadCN", "Vercel", "Supabase", "voice AI", "agentic coding", "tool-building", "Discord bots", "Telegram bots", "scheduler", "cron", "Python automation", "TypeScript" ] Return ONLY valid JSON matching this exact schema: { "tldr": ["bullet 1", "bullet 2", "bullet 3"], "tools": [ {"name": "ToolName", "url": "https://...", "description": "one line"} ], "skill_candidates": [ {"slug": "kebab-case-name", "description": "what skill this would capture"} ], "verdict": "dont-miss" | "worth-a-skim" | "skip", "verdict_reason": "one sentence explanation" } Verdict rules: - "dont-miss": new tool + active use-case for Mike OR novel pattern OR hits 2+ Mike domains OR introduces something Mike hasn't seen - "worth-a-skim": solid content, 1 Mike domain, no new tools - "skip": opinion/news/rehash with no actionable takeaway Be OPINIONATED. Do NOT default to neutral. Mike trusts your judgment. TL;DR bullets: 3-5, action-oriented, specific. No vague summaries. Tools: only real URLs you are confident about from transcript context. Omit if uncertain. Skill candidates: only if genuinely extractable as a reusable workflow/pattern. Channel: Julian Goldie SEO Video title: Hermes Agent OS is INSANE! 🤯 TRANSCRIPT (first 6000 chars): Hermes Agent OS is the most powerful automation agent system available right now. Today I'm going to show you exactly how to use it to automate your entire business. I'm going to show you how to automate videos, content, SEO research, and a whole lot more all from one single system. And I'll show you the exact workflows I use every day to make this agent 10 times more powerful. But here's the thing, there's one part of the setup I want to show you later that almost nobody is doing. And when you see it, everything changes. Your agent gets smarter. It knows who you are. It knows what you do. And it just gets better and better the more you use it. So stick with me all the way to the end because that one thing makes all the difference. Let's get into it. I'm going to answer some of the questions on Hermes Agent OS, how to set up, what you can do with it, etc. So one of the first questions we had from the community here, from Craig, is how to do video editing with videos using something like Hermes, right? So how would I do that? How would I approach it, etc. So there's a really good skill for video editing. It's called Hyperframes inside Hermes Agent. So you can set up Hyperframes with Hermes Agent. What does that look like? Here's an example of what it looks like. And if you want to use it for video and stuff like that, you give the skill setup to Hermes Agent, and then it can use it, right? So let's say for example you wanted to edit a video quickly. What we can actually do here is we can, for example, go into Hermes, which you can see over here. And we could say, "Okay, edit this video with Hyperframes." And so let's say for example we've got a video over here that we need to edit, right? So what we can do here is we can grab that, get the file path, go back into Hermes, and say, "Edit this with Hyperframes." Chad says, "Could Hermes help me set up and install this dashboard?" Yeah, absolutely. So this dashboard that we have set up here for Agent OS, you can actually grab the prompts that we used to build it inside the Alpha Body, as you can see right here. And you can also grab the zip file. So we have an attached zip file inside the community here, and you can just upload that, give it to Hermes and say, "Hey, go off and install this for me, [ASSISTANT] {"tldr":["Julian Goldie pitches Hermes Agent OS as a do-everything automation layer, mostly a wrapper around Claude with bolt-on skills (Hyperframes, HeyGen, Obsidian, Omi).","Hyperframes is the recommended video-editing skill — feed Hermes a local file path plus an 'edit this with Hyperframes' instruction and it produces edited AI-avatar videos via HeyGen.","Memory stack guidance: start with Obsidian as the base, layer Omi later for passive daily memory capture that exports notes into Obsidian.","Dashboard install is a zip + prompt drop into Hermes; the 'one big secret' tease is the personalization/memory file that teaches the agent who you are.","Overall: heavily promotional Skool-funnel content with thin technical depth, no novel patterns beyond what Mike already runs with Claude Code + skills + Obsidian."],"tools":[{"name":"Hyperframes","url":"https://hyperframes.ai","description":"AI video editing tool used as a Hermes skill for local file edits and avatar video assembly."},{"name":"HeyGen","url":"https://heygen.com","description":"AI avatar video generation, paired with Hyperframes for end-to-end avatar video pipelines."},{"name":"Remotion","url":"https://remotion.dev","description":"Code-driven (React) video rendering, mentioned as a Hermes integration option."},{"name":"Omi","url":"https://omi.me","description":"Wearable/passive memory capture device that exports daily notes into Obsidian."},{"name":"Obsidian","url":"https://obsidian.md","description":"Markdown knowledge base recommended as the foundational memory layer for Hermes."}],"skill_candidates":[],"verdict":"skip","verdict_reason":"Promotional Skool-community Q&A for a Claude wrapper Mike already exceeds with his own Hermes/Claude Code stack — no new tools, patterns, or workflows he hasn't already implemented."}

[USER] You are an expert content analyst for Mike Merlino, an AI agency operator and builder. Your job is to extract structured signal from YouTube video transcripts. Mike's domains of interest (if a video hits 2+ of these → strong signal): [ "AI agents", "LLM tooling", "Claude Code", "MCP servers", "skills", "prompt engineering", "SEO automation", "GMB", "local SEO", "cold outreach", "SMS", "GoHighLevel", "Next.js", "ShadCN", "Vercel", "Supabase", "voice AI", "agentic coding", "tool-building", "Discord bots", "Telegram bots", "scheduler", "cron", "Python automation", "TypeScript" ] Return ONLY valid JSON matching this exact schema: { "tldr": ["bullet 1", "bullet 2", "bullet 3"], "tools": [ {"name": "ToolName", "url": "https://...", "description": "one line"} ], "skill_candidates": [ {"slug": "kebab-case-name", "description": "what skill this would capture"} ], "verdict": "dont-miss" | "worth-a-skim" | "skip", "verdict_reason": "one sentence explanation" } Verdict rules: - "dont-miss": new tool + active use-case for Mike OR novel pattern OR hits 2+ Mike domains OR introduces something Mike hasn't seen - "worth-a-skim": solid content, 1 Mike domain, no new tools - "skip": opinion/news/rehash with no actionable takeaway Be OPINIONATED. Do NOT default to neutral. Mike trusts your judgment. TL;DR bullets: 3-5, action-oriented, specific. No vague summaries. Tools: only real URLs you are confident about from transcript context. Omit if uncertain. Skill candidates: only if genuinely extractable as a reusable workflow/pattern. Channel: Julian Goldie SEO Video title: These Claude Updates Change Everything! 🤯 TRANSCRIPT (first 6000 chars): These Claude updates change everything. On May 11th, 2026, Anthropic dropped something called Agent View inside Claude code. And honestly, it's a way bigger deal than most people are saying. Because for the first time, you can run a dozen Claude agents at the same time in one screen and watch them all work for you. Think about that. 12 Claude sessions going at once, doing different jobs. And you just sit there and check in when one of them needs you. That's not a small update. That's a whole new way of using Claude. And there's more. They also shipped a new command called goal. You type one sentence. Claude keeps going until the job is actually done. Writes, checks its own work, fixes its mistakes. And then a second Claude looks over the first one's work to make sure it's right before it tells you it's finished. Want to walk you through every piece of this, what it is, why it matters, and how regular people, not just coders, can use it to grow a business right now. Stick with me, because by the end, you're going to see Claude in a totally different way. Hey, if we haven't met already, I'm the digital avatar of Julian Goldie, CEO of SEO agency Goldie Agency. Whilst he's helping clients get more leads and customers, I'm here to help you get the latest AI updates. And Julian Goldie reads every comment, so make sure you comment below. Let's start with Agent View. This is the one everyone is talking about. Before this update, if you wanted to run more than one Claude session at the same time, you had a mess. People were opening five terminal tabs, were running T-Mux, which is a tool that splits your screen into little boxes. Agent View fixes all of that. You type one command, Claude agents, and you get one clean list. Every Claude session you have running shows up as a row. Each row tells you the status. Is it working? Is it waiting for your input? Is it done? Did it fail? You can see all of it in one place. You can also send a Claude to the background with a slash BG command. So, you start a task, say go do that, and it goes off and works while you do something else. When it needs you, it pings you. When it's done, you check it. Anthropic's own words on this were simple. He said it's one list of all your sessions. But what that really [ASSISTANT] {"tldr":["Anthropic shipped Agent View in Claude Code (May 11, 2026) — run 12+ Claude sessions in one screen with status rows (working/waiting/done/failed), replacing the tmux/multi-terminal mess","New `/goal` command runs objective-driven loops: Claude works, self-checks, fixes its own mistakes, and a second Claude reviews before reporting done","Lead-agent + sub-agent pattern is now first-class — one Claude orchestrates specialized sub-Claudes packaged with skills + connectors","Anthropic dropped 10 finance agent templates (pitch builder, KYC screener, month-end closer, earnings reviewer, etc.) showing the productized agent-template pattern","Claude now embeds in Excel, PowerPoint, Word with shared context across Microsoft 365 apps"],"tools":[{"name":"Claude Agents (Agent View)","url":"https://claude.com/claude-code","description":"Run `claude agents` in terminal to see all running Claude Code sessions as one status list; /bg sends a session to background"}],"skill_candidates":[{"slug":"claude-agent-view-ops","description":"Operate Claude Code's Agent View: spawn N parallel sessions, route to background with /bg, monitor status rows, and reclaim attention only on waiting/failed states"},{"slug":"goal-command-workflow","description":"Wrap tasks in the /goal pattern — objective-driven instruction + self-check loop + second-Claude reviewer gate before marking complete"},{"slug":"lead-subagent-template","description":"Build lead-agent + sub-agent bundles packaging skills, connectors, and specialized sub-Claudes (mirrors Anthropic's finance template pattern) for Mike's agency workflows"}],"verdict":"dont-miss","verdict_reason":"Hits 3+ Mike domains (Claude Code, agents, skills/tool-building) and the Agent View + /goal + lead/sub-agent pattern directly maps to Oliver/Carlos orchestration — this is the native version of what Mike already built."}

[USER] You are an expert content analyst for Mike Merlino, an AI agency operator and builder. Your job is to extract structured signal from YouTube video transcripts. Mike's domains of interest (if a video hits 2+ of these → strong signal): [ "AI agents", "LLM tooling", "Claude Code", "MCP servers", "skills", "prompt engineering", "SEO automation", "GMB", "local SEO", "cold outreach", "SMS", "GoHighLevel", "Next.js", "ShadCN", "Vercel", "Supabase", "voice AI", "agentic coding", "tool-building", "Discord bots", "Telegram bots", "scheduler", "cron", "Python automation", "TypeScript" ] Return ONLY valid JSON matching this exact schema: { "tldr": ["bullet 1", "bullet 2", "bullet 3"], "tools": [ {"name": "ToolName", "url": "https://...", "description": "one line"} ], "skill_candidates": [ {"slug": "kebab-case-name", "description": "what skill this would capture"} ], "verdict": "dont-miss" | "worth-a-skim" | "skip", "verdict_reason": "one sentence explanation" } Verdict rules: - "dont-miss": new tool + active use-case for Mike OR novel pattern OR hits 2+ Mike domains OR introduces something Mike hasn't seen - "worth-a-skim": solid content, 1 Mike domain, no new tools - "skip": opinion/news/rehash with no actionable takeaway Be OPINIONATED. Do NOT default to neutral. Mike trusts your judgment. TL;DR bullets: 3-5, action-oriented, specific. No vague summaries. Tools: only real URLs you are confident about from transcript context. Omit if uncertain. Skill candidates: only if genuinely extractable as a reusable workflow/pattern. Channel: Julian Goldie SEO Video title: These NEW Codex Update are INSANE! 🤯 TRANSCRIPT (first 6000 chars): These new Codex updates are insane. Open AI just made Codex work without you. Your phone is now the remote control. Your laptop keeps coding. You walk away. The work keeps going. This dropped on May 14th, 2 days ago, and it's already changing how people think about AI. Let me break it down so anyone can follow. Codex is Open AI's AI coding agent. Think of it like a robot helper that writes software, fixes bugs, runs tests, and ships work. Until this week, you had to sit at your computer to use it. You had to baby sit it. You had to be there to click approve every time it asked a question. Not anymore. Open AI just put Codex inside the Chat GPT mobile app. iPhone, Android, free plan, go plan. Everyone gets it. And the way they built it is what makes this nuts. Your phone does not run the code. The code runs on your Mac, or your laptop, or a Mac mini sitting in your closet, or a remote server. Your phone just connects to that machine. Then it shows you what's happening, live, in real time. You see the terminal. You see the test results. You see the changes Codex wants to make. You tap approve. You tap reject. You switch models mid task. You start a brand new task from a coffee shop. Open AI literally said this in the announcement. Start new work, review outputs, steer execution, and approve next steps all from the Chat GPT mobile app. Codex will keep running on your laptop, Mac mini, or dev box. Read between the lines on that. They are telling you to leave your desk. This is huge. And stick with me because I'm going to show you exactly how a normal business owner uses this to grow faster. Hey, if we haven't met already, I'm the digital avatar of Julian Goldie, CEO of SEO agency Goldie Agency. Whilst he's helping clients get more leads and customers, I'm here to help you get the latest AI updates. And Julian Goldie reads every comment, so make sure you comment below. A year ago, AI coding tools maxed out at maybe 30 minutes of work before they broke or got lost. Now, Codex can run for hours. Rakuten, the giant Japanese tech company, said Codex helped them build a full mobile app, back end in Python, the iOS app in Swift, and it compressed a 3-month job into weeks. That's a real number from a real company. And now they're saying you don't [ASSISTANT] {"tldr":["OpenAI shipped Codex in the ChatGPT mobile app (May 14) — phone becomes remote control while code runs on your Mac/laptop/server","Secure relay layer keeps files, creds, and execution on your machine; phone is just a viewport for approve/reject/steer","Real use case: kick off Codex tasks (landing pages, social content batches, FAQ from support tickets) from desk, review and approve from phone while away","Rakuten compressed a 3-month mobile app build (Python backend + Swift iOS) into weeks using Codex","Rest of video pivots to AI Profit Boardroom community pitch — the actual Codex news is front-loaded"],"tools":[{"name":"OpenAI Codex (ChatGPT mobile)","url":"https://chatgpt.com","description":"Codex agent now accessible from ChatGPT iOS/Android app; runs on your remote machine, phone is the control surface"}],"skill_candidates":[{"slug":"codex-mobile-remote-control","description":"Setup pattern for running Codex on a dedicated Mac mini / dev box and steering long-running coding tasks from the ChatGPT mobile app — covers relay config, task templates (landing page, social batch, FAQ from inbox), and approval workflow"}],"verdict":"worth-a-skim","verdict_reason":"Real Codex mobile launch news hits Mike's agentic coding + Claude Code parallel domain, but content is thin promo for a paid community with one actual tool update and no novel patterns Mike hasn't already built into his Cody/Codex Desktop lane."}

[USER] You are an expert content analyst for Mike Merlino, an AI agency operator and builder. Your job is to extract structured signal from YouTube video transcripts. Mike's domains of interest (if a video hits 2+ of these → strong signal): [ "AI agents", "LLM tooling", "Claude Code", "MCP servers", "skills", "prompt engineering", "SEO automation", "GMB", "local SEO", "cold outreach", "SMS", "GoHighLevel", "Next.js", "ShadCN", "Vercel", "Supabase", "voice AI", "agentic coding", "tool-building", "Discord bots", "Telegram bots", "scheduler", "cron", "Python automation", "TypeScript" ] Return ONLY valid JSON matching this exact schema: { "tldr": ["bullet 1", "bullet 2", "bullet 3"], "tools": [ {"name": "ToolName", "url": "https://...", "description": "one line"} ], "skill_candidates": [ {"slug": "kebab-case-name", "description": "what skill this would capture"} ], "verdict": "dont-miss" | "worth-a-skim" | "skip", "verdict_reason": "one sentence explanation" } Verdict rules: - "dont-miss": new tool + active use-case for Mike OR novel pattern OR hits 2+ Mike domains OR introduces something Mike hasn't seen - "worth-a-skim": solid content, 1 Mike domain, no new tools - "skip": opinion/news/rehash with no actionable takeaway Be OPINIONATED. Do NOT default to neutral. Mike trusts your judgment. TL;DR bullets: 3-5, action-oriented, specific. No vague summaries. Tools: only real URLs you are confident about from transcript context. Omit if uncertain. Skill candidates: only if genuinely extractable as a reusable workflow/pattern. Channel: Income stream surfers Video title: I Replaced Opus 4.7 With a Free Chinese AI (INSANE) TRANSCRIPT (first 6000 chars): Okay, guys. So, continuing on with my series where I do a test of all of the latest LLMs and all of the latest models to try and find what is the best alternative to a $200 Claude match subscription. In today's video, we're going to be testing out Mimo inside Claude code, but with a couple of differences. So, this is Mimo Claude code inside, sorry, uh using Astro builder skill, right? This is a completely free skill that you can get in the description of this video. It's something I've been working on for a while now. We're also going to be using superpowers, right? So, overall, this is what we're going to be doing today. We're going to be doing superpowers. We're going to be using superpowers, Mimo V 2.5 Pro, and then also, uh basically, going to be using the Astro builder skill, which, like I said, you can get in the description of this video. So, if you don't know what this Astro builder skill is, I made this 2 months ago or so. Basically, all this is is a fairly simple skill that will generate premium websites for you using any model, right? It uses Astro, it has a database, lead gen, everything you need for a web website. You can easily add this to your own directories using these commands right here. I'll leave a link to this GitHub in the description. I made this, right? So, completely free, open source, do whatever you want with it, as usual. It's fairly popular, 15 stars for four forks isn't bad, really, for something that doesn't haven't really been using that much, to be honest with you. But, I thought today, because the Mimo test yesterday was so effective, or 2 days ago, it was so good, I thought today we'll do another test using Mimo, but this time using the superpower skill and the Astro builder skill. So, let's have a little look at what this actually looks like. So, first of all, I set, um Mimo to use, sorry, I set Claude code to use Mimo, right? So, you see here, model is set to Xiaomi. We can actually test this by going to OpenRouter and going up here, going to logs, and we should see Xiaomi 3:36 p.m. There we go. Uh it doesn't actually say it's inside Claude code, I don't think, but I know it's inside Claude code. So, yeah, it is working. It's running. Beautiful. Okay, so we actually need more tok [ASSISTANT] { "tldr": [ "Income Stream Surfers ran MiniMax M2.5 Pro inside Claude Code via OpenRouter as a free Opus 4.7 alternative, paired with Superpowers + his open-source Astro Builder skill", "Result: full Astro site with images, lead-gen form, Turso DB, and admin login - he claims quality is close to Opus 4.7", "Key hack: on OpenRouter, filter prompt pricing to $0 and route Claude Code to any free model (MiniMax M2.5, Owl Alpha, DeepSeek V4 Flash, Nemotron 3, Gemma 4 31B) for effectively-free Claude Code", "Astro Builder skill = one-command scaffold for premium local-SEO sites (Astro + Turso + image gen + lead gen + admin) - GitHub repo linked in description", "Pattern worth copying: Superpowers skill stack + domain-specific build skill + cheap/free OpenRouter model = Opus-tier output at ~$0" ], "tools": [ {"name": "OpenRouter", "url": "https://openrouter.ai", "description": "Model router - filter prompt pricing to free, plug any model into Claude Code"}, {"name": "Turso", "url": "https://turso.tech", "description": "Edge SQLite DB used by the Astro Builder skill for lead-gen and admin"}, {"name": "Harpa SEO AI", "url": "https://harborseo.ai", "description": "Creator's own SEO writer tool (sponsor plug)"} ], "skill_candidates": [ {"slug": "astro-local-seo-site-builder", "description": "One-shot Claude Code skill that scaffolds an Astro local-service-business site with Turso DB, lead-gen form, admin login, and AI-generated hero/service images - clone the Income Stream Surfers pattern into Mike's local SEO site pipeline"}, {"slug": "free-claude-code-via-openrouter", "description": "Configure Claude Code to route through OpenRouter free-tier models (MiniMax M2.5, DeepSeek V4 Flash, Nemotron, Gemma) with model-switching and fallback logic for zero-cost dev loops"}, {"slug": "superpowers-plus-build-skill-stack", "description": "Pattern: stack the Superpowers plugin with a domain-specific build skill (Astro Builder, etc.) to get Opus-tier output from cheap/free models - reusable composition recipe"} ], "verdict": "dont-miss", "verdict_reason": "Hits 4+ Mike domains (Claude Code, skills, agentic coding, local SEO site building) AND introduces a free-model routing trick plus an open-source Astro local-SEO build skill that directly maps to Mike's lead-gen site factory." }