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[Web Browser Content] GoClaw - GoClaw is OpenClaw rebuilt in Go — with multi-tenant isolation, 5-layer security, and native concurrency. Deploy AI agent teams at scale without compromising on safety. Repository: github.com/nextlevelbuilder/goclaw Core Features: - 8-Stage Agent Pipeline: context, history, prompt, think, act, observe, memory summarize. - 4-Mode Prompt System: Full / Task / Minimal / None. - 3-Tier Memory: Working, Episodic, Semantic. - Knowledge Vault: Document registry with wikilinks, hybrid search (FTS + pgvector), filesystem sync. - Agent Teams & Orchestration: Shared task boards, inter-agent delegation. - Multi-Tenant PostgreSQL: Per-user workspaces, encrypted API keys (AES-256-GCM).

[Web Browser Content] GoClaw — Enterprise AI Agent Platform https://goclaw.sh/#architecture ARCHITECTURE Built for the Real World A layered architecture designed for reliability, observability, and zero-trust security at every level. Channels: Telegram, Discord, Slack, Zalo, Feishu/Lark, WhatsApp, WebSocket. API Gateway: Auth & JWT, Rate Limiting, Request Routing, OpenTelemetry Traces, Injection Detection, SSRF Protection, Shell Pattern Guard, AES-256-GCM, CVE-2026-25253 Patch. Agent Engine: Agent Teams, MCP Protocol, Task Boards, 40+ Tools, Conversation Handoff, Evaluate Loops, Quality Gates. LLM Providers: Anthropic, OpenAI, Google Gemini, Groq, Mistral, Ollama, + 14 more. Connect Everything: Meet your users where they are — across 7 messaging platforms, 20+ AI providers, and 40+ built-in tools. 40+ Built-in Tools: Web search, code execution, file management, database queries, HTTP requests, browser automation, and more. GitHub: github.com/nextlevelbuilder/goclaw

[Web Browser Content] GoClaw — Ente X nextlevelbuilde Pricing — Ager Loading... about:blank TOSE - The outs ClaudeKit AgentKit AgentWiki Ranking Reels Ask Gemini Work

Screen: Still have questions? E support@tose.sh What frameworks do you support? We support all major frameworks: Next.js, React, Vue, Nuxt, Svelte, Node.js, Python, Go, and any Docker container. If it runs in a container, it runs on TOSE. How does billing work? Can I use my own domain? What about database? Do I get free credit? How do I get support? x We offer managed PostgreSQL and Redis add-ons. Or connect to your existing database - we support any external connection. What about database? x Yes! You get free $10 credit when you create an account. No credit card required. Use it to deploy and test your apps on real infrastructure. Do I get free credit? x In I spent 4 years building a platform called DXUP to simplify this process, but didn't dare to release it publicly because of security concern

Screen: 00 TOSE - The outstandinc X xtlevelbuilder/goclav X -5 tose.sh TOSE Trusted by 500+ developers Work Features How It Works Pricing Docs EN VI Log in Click, Deploy, Done, From code to live website in 2 minutes. No DevOps Get Started Free e Auto SSL K8s tose deploy $ git push origin main Detecting framework ... Next. js Building U essfut in 45s Singapore o Kubernetes cluster ... v' Live at your-app.tose.sh needed. I app Next. js Deploy your Deploy Your First App Get free $10 credit when you sign up @ Watch Demo 9,840+ Deployments Uptime lox Faster than DIY K8s Singapore Auto SSL K8s Singapore Choose your resources. We handle SSL, domains, and scaling automatically. Link your GitHub repo. We auto- detect your framework. Hit deploy. Your app is live globally in under 2 minutes. 02 Configure 01

Screen: GoClaw — Enterprise A X TOSE - The outstandinc X ClaudeKit - Al Developc AgentWiki - Knowledg 20 github.com/nextlevelbuilder/goclaw nextlevelbuilder/goclav x x Projects AgentKit - Production-I x Pricing — AgentBrain x A Ranking Reels — Videc 2 Ask Gemini x Work nextlevelbuilder goclaw Q Type CZ) to search Code Issues 149 Pull requests 151 Q) Agents Discussions Actions Tags Security and quality Go to file Insights Add file Watch 24 Fork 838 Star 3.1k dev Branches Q mrgoonie and viettranx fix(discord): suppress pairing reply in groups without @... a97e502 • 2 weeks ago < > Code v O 1,528 Commits 3 weeks ago 2 months ago last month 3 weeks ago 2 months ago 2 months ago last month 3 weeks ago last month 2 weeks ago 3 weeks ago 2 months ago last month last month 2 months ago 3 weeks ago About G

[Web Browser Content] TOSE - The outstanding ship experience for every codebase Navigation: - GoClaw - Enterprise - ClaudeKit - AI Development - AgentWiki - Knowledge - AgentKit - Production-Ready Resources: - tose.sh - Pricing - AgentBrain - Ranking Reels - Video - Documentation (Tài liệu) - Pricing (Bảng giá) Language: English / Vietnamese Tools: Ask Gemini, Google Translate

[Web Browser Content] GoClaw — Enterprise ClaudeKit - AI Development AgentWiki - Knowledge nextlevelbuilder/goclav AgentKit - Production-I Pricing — AgentBrain Ranking Reels — Video Ask Gemini Work

Screen: NEW TEMPLATE I-CLICK DEPLOY TOSE GoCIaw click with Skip the DevOps grind. Launch a production-ready GoClaw server in under a minute with the official TOSE template — estimated $10-$20 / month all-in. TOSE.SH GoClaw • Enterprise AI Agents Pick the GoClaw template on TOSE Plug in your LLM API keys Hit Deploy — TOSE handles TLS, DB, DNS + Deploy GoClaw now $10-$2e MONTHLY COST Explore TOSE cå FIRST DEPLOY tose template tose deploy goclaw - -template Pulling goclaw:latest Provisioning PostgreSQL + Redis Issuing TLS certificate Warming Anthropic prompt cache Deploying goclaw... https : //goclaw. yourteam. tose. sh .-e25MB BINARY SIZE Ready to serve RUNTIME DEPS LATEST ARTICLES TOSE.SH GoClaw • Enterprise Al Agents Pick the GoClaw template on TOSE Plug in your LLM API keys Hit Deploy — TOSE hand

Screen: ClaudeKit - Al Develop; GoClaw — Enterprise A X AgentWiki - Knowledg o— -o goclaw.sh x AgentKit - Production-I x Pricing — AgentBrain Integrations x Blog A Ranking Reels — Videc GoClaw O Enterprise Al Agent Platform Why GoClaw Compare Architecture Team Docs EN VI O GitHub Get Started goclaw — enterprise agent platform The Secure, Scalable AI Agent Platform for Enterprise GoClaw is OpenClaw rebuilt in Go — with multi-tenant isolation, 5-layer security, and native concurrency. Deploy Al agent teams at scale without compromising on safety. InstaLL GoCLaw binary (æ25MB) go install github.com/nextlevelbuilder/goclaw@latest Start with multi-tenant PostgreSQL -config goclaw.yaml goclaw server GoC1aw vl.o.e starting. .. PostgreSQL RLS: enabled Security layers: 5/5 active Channels: Telegram, Discor

[Web Browser Content] nextlevelbuilder/ui-ux-pro-max-skill: An AI SKILL that provide design intelligence for building professional UI/UX multiple platforms Repository: nextlevelbuilder/ui-ux-pro-max-skill Issues: 71 | Pull requests: 76 Code | Actions | Agents | Projects | Security and quality | Insights Branch: main | 17 Tags Recent Commits: - mrgoonie: Merge pull request #184 from Jenser77/feat/design-system-visual-i... - amyragan3297: Merge pull request #191 from amyragan3297/amyragan3297.. Project Overview: An AI SKILL that provides design intelligence for building professional UI/UX across multiple platforms and frameworks. Features: - Searchable database of UI styles, color palettes, font pairings, chart types, and UX guidelines. - AI-powered design recommendations. - CLI support: $ uipro init --ai claude Stats: - 78.6k stars - 8.1k forks - 380 watching - 33 Contributors Languages: - Python 78.5% - JavaScript 11.4% - TypeScript 6.6% - HTML 3.5%

[Web Browser Content] ChatGPT Interface Recent Projects & Tools: - GoClaw Enterprise - AgentKit Production - AgentWiki Knowledge Base - Ranking Reels - ClaudeKit AI Development - Local Link Hunter - Business Schema Generator - SEO Advisor Active Tasks: - OpenClaw Setup & Research - Market Comparison: OpenClaw vs Claudecode - Clawdbot Installation Guide - Notion Formatting Request - Epistemic Validation Mode User: Michael Merlino

[Web Browser Content] Translation Bridge: Switch WordPress Page Builders in Seconds Features: - Translate Any Builder: 9 builders supported, 72 unique conversion paths. - Auto-Publish to WP: Content injected directly via REST API. - WP REST Integration: Uses WordPress Application Passwords for secure access; no plugins required. Technical Details: - PHP Engine for speed. - Python Engine for precision. - API endpoints: /translate, /translate-and-publish, /health. Built for production, ready today for scaling WordPress site migrations.

[Web Browser Content] Ranking Reels — Video Ads That Rank on Google Dashboard Overview: - 174 videos, 2930 credits used. - Statuses: Approved, Rejected, Unreviewed. Omega Indexer V2: - The new and improved indexing solution. - Omega Indexer has cut indexing time to 9 days. How Does Omega Indexer V2 Work? 1. API: Log into the dashboard and add the links you wish to index. 2. Filtering: After filtering, the remaining indexable links move into the process. 3. Campaign Statuses Explained: - Valid: The campaign is all valid. - Filtering: The campaign is in the initial stage of filtering. - Refunded: Links that were not indexed are refunded. Additional Features: - Retains its indexing drip, allowing you to spread links over a number of days.

[Web Browser Content] GoClaw — Enterprise AI Agent Platform Navigation: Why GoClaw | Compare | Architecture | Integrations | Blog | Team | Docs Main Content: The Secure, Scalable AI Agent Platform for Enterprise Tools/Links: - goclaw.sh - GitHub - Get Started Language: EN | VI

[Web Browser Content] PayFlow - Payments infrastructure for the internet. Products: Payments, Billing, Connect, Radar Developers: Documentation, API Reference, SDKs, Plugins Security features: - End-to-end encryption: All data encrypted in transit and at rest - Tokenization: Sensitive data replaced with secure tokens - 3D Secure 2: Additional authentication for card payments - Real-time monitoring: 24/7 threat detection and response Security Certifications: - PCI DSS Level 1: Highest level of certification - ISO 27001: Information security management - SOC 2 Type II: Audited security controls - GDPR Compliant: EU data protection Pricing: - Standard: 2.9% per successful card charge, basic fraud protection, standard support. - Enterprise: Custom volume-based pricing, advanced fraud tools, dedicated support, custom integrations. - Platform: 0.5% + standard fees, multi-party payments, split payments, onboarding tools. © 2024 PayFlow, Inc. All rights reserved.

[Web Browser Content] A Ranking AgentKit AgentWl Governed AI, Trusted Outcomes Deploy AI agents with built-in approvals, brand guardrails, and audit trails. Every step is visible, reviewable, and compliant. UI/UX Preview: Agenforce Marketing Template Code | Download

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[Editor Content] VIDEO-TOOLS File: output/omegaindexer-ab/assets/omegaindexer-v2-good-news.png [AI Agent Interaction] - Task: Create video punchline about link indexing - Status: Interrupted - Current Action: Testing Gemini API key against image generation [Technical Notes] - Brand colors: #112337 (dark navy), #204ce5 (bright blue), #EEEADD (cream), #FFFFFF (white) - OpenAI API pricing and vision model limitations (medical images, non-Latin text) - Bash command: ls D:/ClaudeDev/@@_GITHUB/_working—on/Tools/VIDEO—TOOLS/output/omegaindexer—ab/assets/ [Terminal Output] - Checking models available to Gemini API key - Post-tool-use: HTTP request to API successful

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[Web Browser Content] Ranking Reels | Done-For-You Video Ads in 7 Days Packages: STARTER - $2,500/mo - 4 Ad-Ready Videos / Month - Creative strategy and scripting - Professional talent casting - Filming and professional editing - 7 business day turnaround - Slack communication channel GROWTH (Most Popular) - $4,800/mo - 10 Ad-Ready Videos / Month - Everything in Starter - Multiple talent options per cycle - A/B script variations included - Priority turnaround SCALE - $7,800/mo - 20 Ad-Ready Videos / Month - Everything in Growth - Dedicated creative strategist - Platform-specific cuts: Meta, YouTube, TikTok - Monthly performance review call All packages include creative strategy, scripting, talent, filming, and professional editing. 7-day turnaround. 3-month minimum.

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[Web Browser Content] Google AI Studio Creatify - Ad Flow Ranking Reels - Done-For-You Resources Use image 2.0 via API - Google Happy Horse 1.0 is now on fal Generative AI | Run Image, Video, 3D and Audio Models | fal.ai Explore Documentation Pricing Enterprise Ask Gemini Contact Sales Work Login Generative media platform for developers. The world's best generative image, video, and audio models, all in one place. Develop and fine-tune models with serverless GPUs and on-demand clusters. Get started Contact Sales

[Web Browser Content] OpenAI Developers API Overview API meta information: - openai-organization: The organization associated with the request - openai-processing-ms: Time taken processing your API request - openai-version: REST API version used for this request - x-request-id: Unique identifier for this API request (used in troubleshooting) Rate limiting information: - x-ratelimit-limit-requests - x-ratelimit-remaining-requests - x-ratelimit-remaining-tokens - x-ratelimit-reset-requests - x-ratelimit-reset-tokens OpenAI recommends logging request IDs in production deployments for more efficient troubleshooting. Our official SDKs provide a property on top-level response objects containing the value of the x-request-id header. Supplying your own request ID with X-Client-Request-Id: In addition to the server-generated x-request-id, you can supply your own unique identifier for each request via the X-Client-Request-Id request header. This header is not added automatically; you must explicitly set it on the request.

[Editor Content] File: omegaindexer-v2-good-news.png Path: output > omegaindexer-ab > assets > omegaindexer-v2-good-news.png Chat/Log: - u ave this gemini key ? AlzaSyAnAUFluzc98FYj1e7alHKzJr6dKq5sBZE does it work for nano banana 2? - naon banana Google api key not Model Limitations: - Rotation: The model may misinterpret rotated or upside-down text and images. - Graphs: The model may struggle to understand graphs or text where colors or styles vary. - Reasoning: The model struggles with tasks requiring precise spatial localization. - Accuracy: The model may generate incorrect descriptions or captions. - Image shape: The model struggles with panoramic and fisheye images. - Metadata and resizing: The model doesn't process original file names or metadata. - Counting: The model may give approximate counts for objects in images. - CAPTCHAS: For safety reasons, our system blocks the submission of CAPTCHAs. System Info: - We process images at the token level, so each image we process counts towards your tokens per minute (TPM) limit. - For the most precise and up-to-date estimates for image processing, please use our image pricing calculator available here: https://openai.com/api/pricing/ Command-Line Output: $ cat /c/Users/mikem/AppData/Local/Temp/claude/D——ClaudeDev-@@-GITHUB—-working—on—Tools-VIDEO—TOOLS/214d@514-8586-4484-bb9c—fadfbddc65a @/tasks/b318s6z@x.output 2>&1 | head -10

[Editor Content] Explorer: - VIDEO-TOOLS - ranking-reels - test-anna-vs-diana-... - test-case-study-ava... Terminal: - Re-generating all 7 rejected images. - Testing Gemini API key against image generation. - Total models: 50. - Methods: generateContent, countTokens, batchGenerateContent. Documentation: - Images and vision: Overview of building applications involving images with the OpenAI API. - Limitations: Rotation, text size, graph/line styles, spatial localization, accuracy, image shape, metadata/resizing, counting, CAPTCHAs. - Pricing: Images processed at token level; check pricing calculator at https://openai.com/api/pricing/.

Screen: Platform APIs Audio Videos Images Embeddings Evals Fine Tuning Batches Webhooks Events Overview Responses Conversations Streaming events This API reference describes the RESTful, streaming, and realtime APIs you can use to interact with the OpenAl platform. REST APIs are usable via HTTP in any environment that supports HTTP requests. Language-specific SDKs are listed on the libraries page. Authentication The OpenAl API uses API keys for authentication. Create, manage, and learn more about API keys in your organization settings. Remember that your API key is a secretl Do not share it with others or expose it in any client-side code (browsers, apps). API keys should be securely loaded from an environment variable or key management service on the server. API keys should be provided via HTTP B

u ave this gemini key ? [REDACTED:GCP API key]does it work for nano banana 2?

[Web Browser Content] OpenAI Codex: One agent for everywhere you code. Codex is OpenAI's coding agent for software development. It helps with writing code, understanding unfamiliar codebases, reviewing code, debugging, and automating development tasks. Getting Started: - Configuration - Config File - Speed - Rules - Hooks - AGENTS.md Resources: - API reference - Use cases - Apps SDK - Commerce - Ads

Screen: Images 7 7 Generate an Image Edit an Image Create Variation Image generation streaming Creates an image given a prompt. Learn more. Body Parameters } JSO prompt: string Generate image Create image Streaming HTTP C 5) Expand , ' > > A text description of the desired image(s). The maximum length is 32000 characters for the GPT image models, 1000 characters forl dall-e-2 and 4000 characters forl dall-e-3 . background: optional "transparent" or "opaque" or "auto" Allows to set transparency for the background of the generated image(s). This parameter is only supported for the GPT image models. Must be one of *ransparent opaque or auto (default value). When auto is used, the model will automatically determine the best background for the image. If transparent I, the output format needs to support

[Web Browser Content] OpenAI Developers - API Reference - Images Endpoints: - Create image: POST /images/generations - Create image edit: POST /images/edits - Create image variation: POST /images/variations Models: - Image: Represents the content or URL of an image generated by the OpenAI API. Events: - ImageGenStreamEvent: Emitted when a partial image is available during image generation streaming. - ImageEditStreamEvent: Emitted when a partial image is available during image editing streaming. - ImageGenCompletedEvent: Emitted when image generation has completed. - ImageEditCompletedEvent: Emitted when image editing has completed.

[Editor Content] Explorer: - VIDEO-TOOLS - test-anna-vs-diana-... - test-case-study-ava... Terminal: Tip: Try the Plan agent to research and plan before implementing changes. - Create video punchline about link indexing OpenAI Vision Model Limitations: - Text: Enlarge text within the image to improve readability. - Rotation: The model may misinterpret rotated or upside-down text and images. - Graphs: The model may struggle to understand graphs or text where colors or styles vary. - Reasoning: The model struggles with tasks requiring precise spatial localization. - Accuracy: The model may generate incorrect descriptions or captions. - Image shape: The model struggles with panoramic and fisheye images. - Metadata and resizing: The model doesn't process original file names or metadata. Images may be resized before analysis. - Counting: The model may give approximate counts for objects in images. - CAPTCHAS: Our system blocks the submission of CAPTCHAs. Pricing: We process images at the token level, so each image counts towards your tokens per minute (TPM) limit. For the most precise and up-to-date estimates for image processing, please use our image pricing calculator available at https://openai.com/api/pricing/.

[Web Browser Content] OpenAI Developers - Images and vision Overview Learn how to understand or generate images. Create images: Use GPT Image models to generate or edit images. Process image inputs: Use our models' vision capabilities to analyze images. In this guide, you will learn about building applications involving images with the OpenAI API. If you know what you want to build, find your use case below to get started. If you're not sure where to start, continue reading to get an overview. A tour of image-related use cases: - Generate or edit images - Analyze images - Calculating costs - Limitations

[Web Browser Content] Search Query: use image 2.0 via api AI Overview: To use GPT-Image 2 (OpenAI's latest image generation model) via API, you typically use the model identifier 'gpt-image-2' through the OpenAI Image API or third-party providers like fal.ai. Endpoints: - images.generate: For text-to-image creation from scratch. - images.edit: For modifying existing images with text prompts. Resources: - OpenAI Image-2 API Deep Dive (YouTube: Stephen W Thomas) - GPT Images 2.0 API Costs Revealed (YouTube: Kyle Balmer) - OpenAI API Documentation: platform.openai.com/docs/guides/images-vision

# Images and vision ## Overview <div className="mb-10 w-full max-w-full overflow-hidden"> </div> In this guide, you will learn about building applications involving images with the OpenAI API. If you know what you want to build, find your use case below to get started. If you're not sure where to start, continue reading to get an overview. ### A tour of image-related use cases Recent language models can process image inputs and analyze them—a capability known as **vision**. GPT Image models can use text and image inputs to create new images or edit existing ones. The OpenAI API offers several endpoints to process images as input or generate them as output, enabling you to build powerful multimodal applications. | API | Supported use cases | | ---------------------------------------------------- | --------------------------------------------------------------------- | | [Responses API](https://developers.openai.com/api/docs/api-reference/responses) | Analyze images and use them as input and/or generate images as output | | [Images API](https://developers.openai.com/api/docs/api-reference/images) | Generate images as output, optionally using images as input | | [Chat Completions API](https://developers.openai.com/api/docs/api-reference/chat) | Analyze images and use them as input to generate text or audio | To learn more about the input and output modalities supported by our models, refer to our [models page](https://developers.openai.com/api/docs/models). ## Generate or edit images You can generate or edit images using the Image API or the Responses API. The state-of-the-art image generation model, `gpt-image-2`, can understand text and images and use broad world knowledge to generate images with strong instruction following and contextual awareness. Generate images with Responses ```javascript import OpenAI from "openai"; const openai = new OpenAI(); const response = await openai.responses.create({ model: "gpt-4.1-mini", input: "Generate an image of gray tabby cat hugging an otter with an orange scarf", tools: [{type: "image_generation"}], }); // Save the image to a file const imageData = response.output .filter((output) => output.type === "image_generation_call") .map((output) => output.result); if (imageData.length > 0) { const imageBase64 = imageData[0]; const fs = await import("fs"); fs.writeFileSync("cat_and_otter.png", Buffer.from(imageBase64, "base64")); } ``` ```python from openai import OpenAI import base64 client = OpenAI() response = client.responses.create( model="gpt-4.1-mini", input="Generate an image of gray tabby cat hugging an otter with an orange scarf", tools=[{"type": "image_generation"}], ) // Save the image to a file image_data = [ output.result for output in response.output if output.type == "image_generation_call" ] if image_data: image_base64 = image_data[0] with open("cat_and_otter.png", "wb") as f: f.write(base64.b64decode(image_base64)) ``` ```cli openai responses create \\ --model gpt-5.5 \\ --raw-output \\ --transform 'output.#(type=="image_generation_call").result' <<'YAML' | base64 --decode > cat_and_otter.png tools: - type: image_generation input: Generate an image of a gray tabby cat hugging an otter with an orange scarf. YAML ``` You can learn more about image generation in our [Image generation](https://developers.openai.com/api/docs/guides/image-generation) guide. ### Using world knowledge for image generation GPT Image models can use visual understanding of the world to generate lifelike images including real-life details without a reference. For example, if you prompt GPT Image to generate an image of a glass cabinet with the most popular semi-precious stones, the model knows enough to select gemstones like amethyst, rose quartz, jade, etc, and depict them in a realistic way. ## Analyze images **Vision** is the ability for a model to "see" and understand images. If there is text in an image, the model can also understand the text. It can understand most visual elements, including objects, shapes, colors, and textures, even if there are some [limitations](#limitations). ### Giving a model images as input You can provide images as input to generation requests in multiple ways: - By providing a fully qualified URL to an image file - By providing an image as a Base64-encoded data URL - By providing a file ID (created with the [Files API](https://developers.openai.com/api/docs/api-reference/files)) You can provide multiple images as input in a single request by including multiple images in the `content` array, but keep in mind that [images count as tokens](#calculating-costs) and will be billed accordingly. <div data-content-switcher-pane data-value="url"> <div class="hidden">Passing a URL</div> Analyze the content of an image ```javascript import OpenAI from "openai"; const openai = new OpenAI(); const response = await openai.responses.create({ model: "gpt-4.1-mini", input: [{ role: "user", content: [ { type: "input_text", text: "what's in this image?" }, { type: "input_image", image_url: "https://api.nga.gov/iiif/a2e6da57-3cd1-4235-b20e-95dcaefed6c8/full/!800,800/0/default.jpg", }, ], }], }); console.log(response.output_text); ``` ```python from openai import OpenAI client = OpenAI() response = client.responses.create( model="gpt-4.1-mini", input=[{ "role": "user", "content": [ {"type": "input_text", "text": "what's in this image?"}, { "type": "input_image", "image_url": "https://api.nga.gov/iiif/a2e6da57-3cd1-4235-b20e-95dcaefed6c8/full/!800,800/0/default.jpg", }, ], }], ) print(response.output_text) ``` ```csharp using OpenAI.Responses; string key = Environment.GetEnvironmentVariable("OPENAI_API_KEY")!; OpenAIResponseClient client = new(model: "gpt-5", apiKey: key); Uri imageUrl = new("https://api.nga.gov/iiif/a2e6da57-3cd1-4235-b20e-95dcaefed6c8/full/!800,800/0/default.jpg"); OpenAIResponse response = (OpenAIResponse)client.CreateResponse([ ResponseItem.CreateUserMessageItem([ ResponseContentPart.CreateInputTextPart("What is in this image?"), ResponseContentPart.CreateInputImagePart(imageUrl) ]) ]); Console.WriteLine(response.GetOutputText()); ``` ```bash curl https://api.openai.com/v1/responses \\ -H "Content-Type: application/json" \\ -H "Authorization: Bearer $OPENAI_API_KEY" \\ -d '{ "model": "gpt-4.1-mini", "input": [ { "role": "user", "content": [ {"type": "input_text", "text": "what is in this image?"}, { "type": "input_image", "image_url": "https://api.nga.gov/iiif/a2e6da57-3cd1-4235-b20e-95dcaefed6c8/full/!800,800/0/default.jpg" } ] } ] }' ``` ```cli openai responses create \\ --model gpt-5.5 \\ --raw-output \\ --transform 'output.#(type=="message").content.0.text' <<'YAML' input: - role: user content: - type: input_text text: What is in this image? - type: input_image image_url: https://api.nga.gov/iiif/a2e6da57-3cd1-4235-b20e-95dcaefed6c8/full/!800,800/0/default.jpg YAML ``` </div> <div data-content-switcher-pane data-value="base64-encoded" hidden> <div class="hidden">Passing a Base64 encoded image</div> Analyze the content of an image ```javascript import fs from "fs"; import OpenAI from "openai"; const openai = new OpenAI(); const imagePath = "path_to_your_image.jpg"; const base64Image = fs.readFileSync(imagePath, "base64"); const response = await openai.responses.create({ model: "gpt-4.1-mini", input: [ { role: "user", content: [ { type: "input_text", text: "what's in this image?" }, { type: "input_image", image_url: \`data:image/jpeg;base64,\${base64Image}\`, }, ], }, ], }); console.log(response.output_text); ``` ```python import base64 from openai import OpenAI client = OpenAI() # Function to encode the image def encode_image(image_path): with open(image_path, "rb") as image_file: return base64.b64encode(image_file.read()).decode("utf-8") # Path to your image image_path = "path_to_your_image.jpg" # Getting the Base64 string base64_image = encode_image(image_path) response = client.responses.create( model="gpt-4.1", input=[ { "role": "user", "content": [ { "type": "input_text", "text": "what's in this image?" }, { "type": "input_image", "image_url": f"data:image/jpeg;base64,{base64_image}", }, ], } ], ) print(response.output_text) ``` ```csharp using OpenAI.Responses; string key = Environment.GetEnvironmentVariable("OPENAI_API_KEY")!; OpenAIResponseClient client = new(model: "gpt-5", apiKey: key); Uri imageUrl = new("https://openai-documentation.vercel.app/images/cat_and_otter.png"); using HttpClient http = new(); // Download an image as stream using var stream = await http.GetStreamAsync(imageUrl); OpenAIResponse response1 = (OpenAIResponse)client.CreateResponse([ ResponseItem.CreateUserMessageItem([ ResponseContentPart.CreateInputTextPart("What is in this image?"), ResponseContentPart.CreateInputImagePart(BinaryData.FromStream(stream), "image/png") ]) ]); Console.WriteLine($"From image stream: {response1.GetOutputText()}"); // Download an image as byte array byte[] bytes = await http.GetByteArrayAsync(imageUrl); OpenAIResponse response2 = (OpenAIResponse)client.CreateResponse([ ResponseItem.CreateUserMessageItem([ ResponseContentPart.CreateInputTextPart("What is in this image?"), ResponseContentPart.CreateInputImagePart(BinaryData.FromBytes(bytes), "image/png") ]) ]); Console.WriteLine($"From byte array: {response2.GetOutputText()}"); ``` </div> <div data-content-switcher-pane data-value="file" hidden> <div class="hidden">Passing a file ID</div> Analyze the content of an image ```javascript import OpenAI from "openai"; import fs from "fs"; const openai = new OpenAI(); // Function to create a file with the Files API async function createFile(filePath) { const fileContent = fs.createReadStream(filePath); const result = await openai.files.create({ file: fileContent, purpose: "vision", }); return result.id; } // Getting the file ID const fileId = await createFile("path_to_your_image.jpg"); const response = await openai.responses.create({ model: "gpt-4.1-mini", input: [ { role: "user", content: [ { type: "input_text", text: "what's in this image?" }, { type: "input_image", file_id: fileId, }, ], }, ], }); console.log(response.output_text); ``` ```python from openai import OpenAI client = OpenAI() # Function to create a file with the Files API def create_file(file_path): with open(file_path, "rb") as file_content: result = client.files.create( file=file_content, purpose="vision", ) return result.id # Getting the file ID file_id = create_file("path_to_your_image.jpg") response = client.responses.create( model="gpt-4.1-mini", input=[{ "role": "user", "content": [ {"type": "input_text", "text": "what's in this image?"}, { "type": "input_image", "file_id": file_id, }, ], }], ) print(response.output_text) ``` ```csharp using OpenAI.Files; using OpenAI.Responses; string key = Environment.GetEnvironmentVariable("OPENAI_API_KEY")!; OpenAIResponseClient client = new(model: "gpt-5", apiKey: key); string filename = "cat_and_otter.png"; Uri imageUrl = new($"https://openai-documentation.vercel.app/images/{filename}"); using var http = new HttpClient(); // Download an image as stream using var stream = await http.GetStreamAsync(imageUrl); OpenAIFileClient files = new(key); OpenAIFile file = await files.UploadFileAsync(BinaryData.FromStream(stream), filename, FileUploadPurpose.Vision); OpenAIResponse response = (OpenAIResponse)client.CreateResponse([ ResponseItem.CreateUserMessageItem([ ResponseContentPart.CreateInputTextPart("what's in this image?"), ResponseContentPart.CreateInputImagePart(file.Id) ]) ]); Console.WriteLine(response.GetOutputText()); ``` </div> ### Image input requirements Input images must meet the following requirements to be used in the API. <table> <tr> <td>Supported file types</td> <td> - PNG (`.png`) - JPEG (`.jpeg` and `.jpg`) - WEBP (`.webp`) - Non-animated GIF (`.gif`) </td> </tr> <tr> <td>Size limits</td> <td> - Up to 512 MB total payload size per request - Up to 1500 individual image inputs per request </td> </tr> <tr> <td>Other requirements</td> <td> - No watermarks or logos - No NSFW content - Clear enough for a human to understand </td> </tr> </table> ### Choose an image detail level The `detail` parameter tells the model what level of detail to use when processing and understanding the image (`low`, `high`, `original`, or `auto`). If you skip the parameter, the model will use `auto`. This behavior is the same in both the Responses API and the Chat Completions API. On `gpt-5.5`, `auto` and the default omitted behavior are equivalent to `original`. Use the following guidance to choose a detail level: | Detail level | Best for | | ------------ | ---------------------------------------------------------------------------------------------------------------------------------------------- | | `low` | Fast, low-cost understanding when fine visual detail is not important. The model receives a low-resolution 512px x 512px version of the image. | | `high` | Standard high-fidelity image understanding. | | `original` | Large, dense, spatially sensitive, or computer-use images. Available on `gpt-5.4` and future models. | | `auto` | Automatic detail selection. On `gpt-5.5`, `auto` and the omitted/default behavior are equivalent to `original`. | For computer use, localization, and click-accuracy use cases on `gpt-5.4` and future models, we recommend `"detail": "original"`. See the [Computer use guide](https://developers.openai.com/api/docs/guides/tools-computer-use) for more detail. Read more about how models resize images in the [Model sizing behavior](#model-sizing-behavior) section, and about token costs in the [Calculating costs](#calculating-costs) section below. ### Model sizing behavior Different models use different resizing rules before image tokenization: <table> <tr> <th>Model family</th> <th>Supported detail levels</th> <th>Patch and resizing behavior</th> </tr> <tr> <td> <code>gpt-5.5</code> </td> <td> <code>low</code>, <code>high</code>, <code>original</code>, <code>auto</code> </td> <td> <code>high</code> allows up to 2,500 patches or a 2048-pixel maximum dimension. <code>original</code> allows up to 10,000 patches or a 6000-pixel maximum dimension. If either limit is exceeded, we resize the image while preserving aspect ratio to fit within the lesser of those two constraints for the selected detail level. <code>auto</code> and omitted <code>detail</code> use the same sizing behavior as <code>original</code>. [Full resizing details below.](#patch-based-image-tokenization) </td> </tr> <tr> <td> <code>gpt-5.4</code> </td> <td> <code>low</code>, <code>high</code>, <code>original</code>, <code>auto</code> </td> <td> <code>high</code> allows up to 2,500 patches or a 2048-pixel maximum dimension. <code>original</code> allows up to 10,000 patches or a 6000-pixel maximum dimension. If either limit is exceeded, we resize the image while preserving aspect ratio to fit within the lesser of those two constraints for the selected detail level. <code>auto</code> and omitted <code>detail</code> use the same sizing behavior as <code>high</code>.[Full resizing details below.](#patch-based-image-tokenization) </td> </tr> <tr> <td> <code>gpt-5.4-mini</code>, <code>gpt-5.4-nano</code>, <code>gpt-5-mini</code>, <code>gpt-5-nano</code>, <code>gpt-5.2</code>, <code>gpt-5.3-codex</code>, <code>gpt-5-codex-mini</code>, <code>gpt-5.1-codex-mini</code>, <code>gpt-5.2-codex</code>, <code>gpt-5.2-chat-latest</code>, <code>o4-mini</code>, and the{" "} <code>gpt-4.1-mini</code> and <code>gpt-4.1-nano</code> 2025-04-14 snapshot variants </td> <td> <code>low</code>, <code>high</code>, <code>auto</code> </td> <td> <code>high</code> allows up to 1,536 patches or a 2048-pixel maximum dimension. If either limit is exceeded, we resize the image while preserving aspect ratio to fit within the lesser of those two constraints. [Full resizing details below.](#patch-based-image-tokenization) </td> </tr> <tr> <td> <code>GPT-4o</code>, <code>GPT-4.1</code>, <code>GPT-4o-mini</code>, <code>computer-use-preview</code>, and o-series models except <code>o4-mini</code> </td> <td> <code>low</code>, <code>high</code>, <code>auto</code> </td> <td> Use tile-based resizing behavior. See{" "} <a href="#gpt-4o-gpt-41-gpt-4o-mini-cua-and-o-series-except-o4-mini"> the detailed behavior below </a> </td> </tr> </table> ## Calculating costs Image inputs are metered and charged in token units similar to text inputs. How images are converted to text token inputs varies based on the model. You can find a vision pricing calculator in the FAQ section of the [pricing page](https://openai.com/api/pricing/). ### Patch-based image tokenization Some models tokenize images by covering them with 32px x 32px patches. Each model defines a maximum patch budget. The token cost of an image is determined as follows: A. Compute how many 32px x 32px patches are needed to cover the original image. A patch may extend beyond the image boundary. ``` original_patch_count = ceil(width/32)×ceil(height/32) ``` B. If the original image would exceed the model's patch budget, scale it down proportionally until it fits within that budget. Then adjust the scale so the final resized image stays within budget after converting to integer pixel dimensions and computing patch coverage. ``` shrink_factor = sqrt((32^2 * patch_budget) / (width * height)) adjusted_shrink_factor = shrink_factor * min( floor(width * shrink_factor / 32) / (width * shrink_factor / 32), floor(height * shrink_factor / 32) / (height * shrink_factor / 32) ) ``` C. Convert the adjusted scale into integer pixel dimensions, then compute the number of patches needed to cover the resized image. This resized patch count is the image-token count before applying the model multiplier, and it is capped by the model's patch budget. ``` resized_patch_count = ceil(resized_width/32)×ceil(resized_height/32) ``` D. Apply a multiplier based on the model to get the total tokens: | Model | Multiplier | | --------------- | ---------- | | `gpt-5.4-mini` | 1.62 | | `gpt-5.4-nano` | 2.46 | | `gpt-5-mini` | 1.62 | | `gpt-5-nano` | 2.46 | | `gpt-4.1-mini*` | 1.62 | | `gpt-4.1-nano*` | 2.46 | | `o4-mini` | 1.72 | _For `gpt-4.1-mini` and `gpt-4.1-nano`, this applies to the 2025-04-14 snapshot variants._ **Cost calculation examples for a model with a 1,536-patch budget** - A 1024 x 1024 image has a post-resize patch count of **1024** - A. `original_patch_count = ceil(1024 / 32) * ceil(1024 / 32) = 32 * 32 = 1024` - B. `1024` is below the `1,536` patch budget, so no resize is needed. - C. `resized_patch_count = 1024` - Resized patch count before the model multiplier: `1024` - Multiply by the model's token multiplier to get the billed token units. - A 1800 x 2400 image has a post-resize patch count of **1452** - A. `original_patch_count = ceil(1800 / 32) * ceil(2400 / 32) = 57 * 75 = 4275` - B. `4275` exceeds the `1,536` patch budget, so we first compute `shrink_factor = sqrt((32^2 * 1536) / (1800 * 2400)) = 0.603`. - We then adjust that scale so the final integer pixel dimensions stay within budget after patch counting: `adjusted_shrink_factor = 0.603 * min(floor(1800 * 0.603 / 32) / (1800 * 0.603 / 32), floor(2400 * 0.603 / 32) / (2400 * 0.603 / 32)) = 0.586`. - Resized image in integer pixels: `1056 x 1408` - C. `resized_patch_count = ceil(1056 / 32) * ceil(1408 / 32) = 33 * 44 = 1452` - Resized patch count before the model multiplier: `1452` - Multiply by the model's token multiplier to get the billed token units. ### Tile-based image tokenization #### GPT-4o, GPT-4.1, GPT-4o-mini, CUA, and o-series (except o4-mini) The token cost of an image is determined by two factors: size and detail. Any image with `"detail": "low"` costs a set, base number of tokens. This amount varies by model. To calculate the cost of an image with `"detail": "high"`, we do the following: - Scale to fit in a 2048px x 2048px square, maintaining original aspect ratio - Scale so that the image's shortest side is 768px long - Count the number of 512px squares in the image. Each square costs a set amount of tokens, shown below. - Add the base tokens to the total | Model | Base tokens | Tile tokens | | ------------------------ | ----------- | ----------- | | gpt-5, gpt-5-chat-latest | 70 | 140 | | 4o, 4.1, 4.5 | 85 | 170 | | 4o-mini | 2833 | 5667 | | o1, o1-pro, o3 | 75 | 150 | | computer-use-preview | 65 | 129 | ### GPT Image 1 For GPT Image 1, we calculate the cost of an image input the same way as described above, except that we scale down the image so that the shortest side is 512px instead of 768px. The price depends on the dimensions of the image and the [input fidelity](https://developers.openai.com/api/docs/guides/image-generation?image-generation-model=gpt-image-1#input-fidelity). When input fidelity is set to low, the base cost is 65 image tokens, and each tile costs 129 image tokens. When using high input fidelity, we add a set number of tokens based on the image's aspect ratio in addition to the image tokens described above. - If your image is square, we add 4160 extra input image tokens. - If it is closer to portrait or landscape, we add 6240 extra tokens. To see pricing for image input tokens, refer to our [pricing page](https://developers.openai.com/api/docs/pricing#latest-models). ## Limitations While models with vision capabilities are powerful and can be used in many situations, it's important to understand the limitations of these models. Here are some known limitations: - **Medical images**: The model is not suitable for interpreting specialized medical images like CT scans and shouldn't be used for medical advice. - **Non-English**: The model may not perform optimally when handling images with text of non-Latin alphabets, such as Japanese or Korean. - **Small text**: Enlarge text within the image to improve readability. When available, using `"detail": "original"` can also help performance. - **Rotation**: The model may misinterpret rotated or upside-down text and images. - **Visual elements**: The model may struggle to understand graphs or text where colors or styles—like solid, dashed, or dotted lines—vary. - **Spatial reasoning**: The model struggles with tasks requiring precise spatial localization, such as identifying chess positions. - **Accuracy**: The model may generate incorrect descriptions or captions in certain scenarios. - **Image shape**: The model struggles with panoramic and fisheye images. - **Metadata and resizing**: The model doesn't process original file names or metadata. Depending on image size and `detail` level, images may be resized before analysis, affecting their original dimensions. - **Counting**: The model may give approximate counts for objects in images. - **CAPTCHAS**: For safety reasons, our system blocks the submission of CAPTCHAs. --- We process images at the token level, so each image we process counts towards your tokens per minute (TPM) limit. For the most precise and up-to-date estimates for image processing, please use our image pricing calculator available [here](https://openai.com/api/pricing/).

[Web Browser Content] Google AI Studio Creatify - Ad Flow Ranking Reels | Done-For-You Ask Gemini Gmail Login to your Podbean Account | Podbean Sign in to GitHub Sign in - Google Accounts Claude Web Store Customize Chrome Search queries: use ai, use synonym, use a calculator, use case, gpt image 2, grok 2 image generator, imagen video, appimage file

[Editor Content] Project: VIDEO-TOOLS Files: - inventory.json - inventory-v2.json - omegaindexer-dashboard.png Brand colors locked from site CSS: - #112337 dark navy (primary dark) - #204ce5 bright blue (accent) - #EEEADD cream - #FFFFFF white Task: Re-generating all 7 rejected images with brand palette locked in every prompt + high quality.

[Web Browser Content] /spend?project=gen-lang-client-0673394765 Docs Gemini API Spend • Tier I API Keys Project: Gemini Project Monthly spend cap: Experimental Set spend cap Overages may occur during 10 minutes latency. Resets on the first day of each month (PST). Learn more New: Control your API cost Set a monthly spend cap to prevent accidental overspending Next Spend 28 Days All Models Your total cost (April 17 - May 14, 2026) Cost: $0.01 Savings: $0.00 Total cost: $0.01 Graph data showing cost trends from April 23, 2026 to May 14, 2026.

[Web Browser Content] API Keys | Google AI Studio Dashboard API Keys Projects Usage Rate Limit Spend Billing Logs and Datasets Changelog Get API key Settings team@merlinomarketing.com API Keys Key | Project | Created | Billing Tier ...sBZE | Gemini API Key | Gemini Project | May 9, 2026 | Tier 1 ...dcv8 | Gemini API Key | Gemini Project | Apr 7, 2026 | Free tier ...hlDE | n8n | n8n888 | Sep 26, 2025 | Free tier Create a new key Name your key: Gemini API Key Choose an imported project: Gemini Project Create key

[Web Browser Content] Ranking Reels | Done-For-You Video Ads in 7 Days [Pricing Packages] STARTER: $2,500/mo - 4 Ad-Ready Videos / Month - Creative strategy and scripting - Professional talent casting - Filming and professional editing - 7 business day turnaround - Slack communication channel GROWTH (Most Popular): $4,800/mo - 10 Ad-Ready Videos / Month - Everything in Starter - Multiple talent options per cycle - A/B script variations included - Priority turnaround SCALE: $7,800/mo - 20 Ad-Ready Videos / Month - Everything in Growth - Dedicated creative strategist - Platform-specific cuts: Meta, YouTube, TikTok - Monthly performance review call All packages include creative strategy, scripting, talent, filming, and professional editing with a 7-day turnaround and 3-month minimum.

[Web Browser Content] Chrome Profiles List Ava (avaeamerlino@gmail.com) Better Map (bettermaprankings.com) Brand (ascendrecoverycenters.com) Buy The (buythehourmovers.com) CTR (ctrgeeks.com) Damjan (merlinomarketing.com) Flat Fee (flatfeemovers.com) Flat Fee (flatfeemovers.net) Kaboom (kaboomseo.com) Karma (karmamovers.com) Maps (northvalleysolarpower.com) merlino (pmnow.biz) Michael (greengridgoblins.com) Michael (MichaelMerlin020) Michael (mikemerlino.com) Michael (TEAM merlinomarketing.com) Mike (MichaelMerlin02020) Mikey (Mikey Botz)

[Web Browser Content] Ranking Reels — Video Ads That Rank on Google Concepts for Review: - unindexed link rejected - money burning cash - google spider crawling - links being built Task: omegaindexer-2026-05-15 Date: May 14, 2026 Status: Verdict Pending (Approve/Reject/Delete) UI Elements: ChatGPT, AgentKit, AgentWl, Pricing, Ask Gemini

[Editor Content] North Valley Honest read Proactiv A1 SaaS ShtpFast Cory Marketing Ranking Reels Memz DARK by default (black bg, white text). Bold ghosted-then-solid headline reveal, blue CTA pill, avatar trust strip with 5 stars, "Trusted by 27,000+ creators" social proof, dashboard mockup peeking up from below. SaaS marketing energy with strong social proof. Light bg, MASSIVE black headline ("Generate Images, Text and Videos with AI"), "We've raised $69M seed funding" pill, dashboard mockup. Most punch-in-the-face hero of all the options. Paid SaaS boilerplate. Tailwind/DaisyUI based. Famous indie hacker template. Pricing-page-heavy template. Not in your local gallery — separate $199 purchase. Closest to current Agenforce vibe: AI SaaS (option 3) — light theme, giant hero, fits your brand without dark mode violation. Most "premium SaaS launch". Proactiv — but it's dark by default; we'd have to convert it to light (your standing rule). Skip Schedule until I fix its broken build, screenshot is useless. ShtpFast is a different beast — Tailwind/DaisyUI not ShadCN/Aceternity. Pivot of stacks. I can do it if you own it. My recommendation: Stay on Agenforce (current) OR switch to AI SaaS template. Both are light-default, both are Aceternity, both have the giant typographic hero you've been gravitating toward. Agenforce already has Translation Bridge content fully wired. AI SaaS would be a template-clone swap — about 20 min of work. What do you want to do? - 'keep agenforce': stop hopping templates, finish polishing what's live - 'swap to ai-saas': Frankie does the swap - 'swap to proactiv': Frankie clones, forces light theme - 'fix schedule then show me': I unblock the build, regen the screenshot - 'shipfast': separate path, you need to confirm you own a license [honcho] response -4 saved response (2373 chars) Stop says: Crunched for 1m 38s. You re-evaluate. Recap: We deployed Translation Bridge as a live REST API on Railway (with custom domain translate.merlinoai.com) plus a sales page built on the Aceternity Agenforce template at translation-bridge-sales.vercel.app. Next: you pick whether to keep Agenforce or swap to AI SaaS, Proactiv, Schedule, or ShipFast. (disable recaps in /config) User says: bitch I said build them all separate URLs so I can pick with Cory which we like best. stop making me repeat myself [honcho] user-prompt injected conclusions (cached) Ranking Reels — Video Ad... Schedule Marketing... Switch WordPress page builders in seconds, not weeks, permissions on (shift+tab to cycle) Install and deploy Translation Bridge tool 10:51 PM 5/14/2026

[Command-Line Output] Translation Bridge Project Status: - Deployed: REST API on Railway (translate.merlinoai.com) - Sales Page: Built on Aceternity Agenforce template (translation-bridge-sales.vercel.app) Template Options: 1. Agenforce (Current): Light-default, Aceternity, giant typographic hero. 2. AI SaaS: Light-default, Aceternity, giant hero, fits brand. 3. Proactiv: Dark by default, requires conversion to light theme. 4. Schedule: Build error (Three.js dependency), currently unusable. 5. ShipFast: Tailwind/DaisyUI based, requires separate $199 license. Recommendation: Stay on Agenforce or switch to AI SaaS (approx. 20 mins of work). Action Items: - 'keep agenforce': Stop hopping, polish current site. - 'swap to at-saas': Frankie performs swap. - 'swap to proactiv': Frankie clones and forces light theme. - 'fix schedule then show me': Unblock build and regenerate screenshot. - 'shipfast': Confirm license ownership.

[Command-Line Output] Ranking Reels [honcho] response: Spinning up live preview deploys of 5 candidates. Candidates: A. proactiv: https://prevtew-saas-proacttv.vercel.app B. startup-landing: https://prevtew-saas-startup.vercel.app C. saas-foxtrot: https://prevtew-saas-foxtrot.vercel.app D. agenforce: https://prevtew-saas-agenforce.vercel.app E. cosmtc: https://prevtew-saas-cosmtc.vercel.app Goal: Clone vslqueen.com as the Ranking Reels funnel and ship to Vercel + GHL. Pending Tasks (7 open): - Build 3 funnel pages in GHL Funnel Builder - Build GHL workflow + pipeline - Create 4 email templates in GHL - Set calendar availability Mon-Fri 10-5 ET - Create 3 Stripe products + payment links

[Command-Line Output] North Valley Cory Claude Code v2.1.141 Opus 4.7 (1M context) [honcho] user-prompt injected conclusions UserPromptSubmtt says: Stopped. Nothing running, no agents in flight. LangChatn/LangGraph experimentation is parked. The pilot at D:/Ecosystem/langgraph-ptlot/ exists but the dev server is not running and no further work is queued against it. What do you want me on instead? [honcho] response -4 saved response Stop says: Recap: We wired LangSmith tracing across agent-memory, the subagent hook, and an eval hub, scaffolded a LangGraph pilot, then you told me to stop touching LangChain. Next action: pick what you want to work on instead. [honcho] response -4 saved response Stop says: Recap: Built the CrewAI SOP site (live at https://crewai-sop.vercel.app), wired its 246 docs into the merlino-sops MCP, and copied everything into a standalone Obsidian vault at E:\Merltno Vault\Vaults\crewat-sop-vault. Next: restart Claude Code so the new MCP category loads. Obsidian Vault Details: - Path: E:\Merltno Vault\Vaults\crewat-sop-vault\ - Total .md files: 251 - Vault size: 32 MB - Structure: 9 section directories (reference, concepts, enterprise, examples, guides, learn, mcp, observability, tools) - Entry points: README.md, _moc.md Privacy confirmed: Both mmerltn023/crewat-sop and mmerltn023/merltno-sops-mcp are private.

[Editor Content] Ranking Tasks and Link Indexing Review - Ranking - Translatic - AgentForce - UI/UX Projects - AgentKit Status/Verdict: - Approved - Keep - Never Delete - Reject Concepts: - Unindexed link rejected - Google spider crawling - Links being built Metadata: - megaindexer-2026-05-15 - Updated: 5/14/2026 - Path: D:\Program Files\Python31...

[Editor Content] VIDEO-TOOLS - Visual Studio Code EXPLORER VIDEO-TOOLS - test-anna-vs-diana - test-case-study-ava TERMINAL Creatify API balance: 1,216 credits ($133.76). Task: Approve keepers from the database and fire videos using only the approved image set (no stock filler). Workflow: 1. Approve keepers from the DB. 2. Fire videos using only the approved image set. 3. Notify when rating is complete. Status: - 1 shell running. - Baked for 5m 36s. - Recap: Use RankingReels production spec to burn today's Creatify credits before they expire. - Concept images available at https://rankingreets.com/images. Rating Interface: - Verdict: Approve, Keep, Reject, Never, Delete, Tag. - Concept: links being built. - Updated 5/14/2026. - Feedback: How is Claude doing this session?

[Web Browser Content] OmegaIndexer Dashboard - AI-Indexed Links Guaranteed Review and approve 12 generated images for video renders. Concepts being reviewed: - AI brain indexing - Nine day timer - Money burning cash - Authority flowing link - Links being built - Google spider crawling - Unindexed link rejected - SEO professional relieved - Rankings climbing - Credit refund automatic Dashboard Stats: - Total Images: 12 - Approved: 1 - Rejected: 5 - Unreviewed: 6 - Balance: $2,165.23 Actions: Approve, Keep, Reject, Never, Delete Updated: 5/14/2026

image-omegaindexer-omegaindexer-logo-cta gpt-image-1 REJECTED omegaindexer logo cta omegaindexer-2026-05-15 gpt-image-1 May 14, 2026 Open full Verdict Approve Keep Reject Never Delete Tag HQ ($$) LQ ($) Concept: ogpt image-2 and not our brand colors megaindexer logo cta Clear review Updated 5/14/2026, 10:49:19 PM image-omegaindexer-seo-professional-relieved gpt-image-1 DELETE seo professional relieved omegaindexer-2026-05-15 gpt-image-1 May 14, 2026 Open full Verdict Approve Keep Reject Never Delete Tag HQ ($$) LQ ($) Concept: seo professional relieved Clear review Updated 5/14/2026, 10:49:19 PM image-omegaindexer-rankings-climbing gpt-image-1 APPROVED rankings climbing omegaindexer-2026-05-15 gpt-image-1 May 14, 2026 Open full Verdict Approve Keep Reject Never Delete Tag HQ ($$) LQ ($) Concept: rankings climbing Clear review Updated 5/14/2026, 10:49:27 PM image-omegaindexer-credit-refund-automatic gpt-image-1 DELETE credit refund automatic omegaindexer-2026-05-15 gpt-image-1 May 14, 2026 Open full Verdict Approve Keep Reject Never Delete Tag HQ ($$) LQ ($) Concept: credit refund automatic Clear review Updated 5/14/2026, 10:49:33 PM image-omegaindexer-nine-day-timer gpt-image-1 DELETE nine day timer omegaindexer-2026-05-15 gpt-image-1 May 14, 2026 Open full Verdict Approve Keep Reject Never Delete Tag HQ ($$) LQ ($) Concept: nine day timer Clear review Updated 5/14/2026, 10:49:37 PM image-omegaindexer-omegaindexer-dashboard gpt-image-1 APPROVED omegaindexer dashboard omegaindexer-2026-05-15 gpt-image-1 May 14, 2026 Open full Verdict Approve Keep Reject Never Delete Tag HQ ($$) LQ ($) Concept: omegaindexer dashboard Clear review Updated 5/14/2026, 10:49:43 PM image-omegaindexer-ai-brain-indexing gpt-image-1 APPROVED ai brain indexing omegaindexer-2026-05-15 gpt-image-1 May 14, 2026 Open full Verdict Approve Keep Reject Never Delete Tag HQ ($$) LQ ($) Concept: ai brain indexing Clear review Updated 5/14/2026, 10:49:47 PM image-omegaindexer-authority-flowing-link gpt-image-1 DELETE authority flowing link omegaindexer-2026-05-15 gpt-image-1 May 14, 2026 Open full Verdict Approve Keep Reject Never Delete Tag HQ ($$) LQ ($) Concept: authority flowing link Clear review Updated 5/14/2026, 10:49:52 PM image-omegaindexer-unindexed-link-rejected gpt-image-1 DELETE unindexed link rejected omegaindexer-2026-05-15 gpt-image-1 May 14, 2026 Open full Verdict Approve Keep Reject Never Delete Tag HQ ($$) LQ ($) Concept: unindexed link rejected Clear review Updated 5/14/2026, 10:49:57 PM image-omegaindexer-money-burning-cash gpt-image-1 APPROVED money burning cash omegaindexer-2026-05-15 gpt-image-1 May 14, 2026 Open full Verdict Approve Keep Reject Never Delete Tag HQ ($$) LQ ($) Concept: money burning cash Clear review Updated 5/14/2026, 10:49:59 PM image-omegaindexer-google-spider-crawling gpt-image-1 APPROVED google spider crawling omegaindexer-2026-05-15 gpt-image-1 May 14, 2026 Open full Verdict Approve Keep Reject Never Delete Tag HQ ($$) LQ ($) Concept: google spider crawling Clear review Updated 5/14/2026, 10:50:06 PM image-omegaindexer-links-being-built gpt-image-1 DELETE links being built omegaindexer-2026-05-15 gpt-image-1 May 14, 2026 Open full Verdict Approve Keep Reject Never Delete Tag HQ ($$) LQ ($) Concept: links being built Clear review Updated 5/14/2026, 10:50:10 PM