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Do not share your API key with others or expose it in the browser or other client-side code. To protect your account's security, OpenAl may automatically disable any API key that has leaked publicly.
NAME
memz
ranking-reels
calltrack
calltraker
calldecoderlove
blogstrorm
aycd
surgegraph
Johnbert
STATUS
Active
Active
Active
Active
Active
Active
May 13, 03:45 PM
[Web Browser Content]
Usage
Total Spend
API capabilities
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Images: 0 requests, 0 images
Default project
Total tokens: 206,253
Total requests: 2,630
Date range: 04/28/26 - 05/13/26
API Keys: Michael Merlino (2.346K)
Responses and Chat Completions: 2.63K requests, 206.253K input tokens
Spend: $6.75, $1.51, $6.61
Manage spend alerts
May 13, 03:45 PM
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Michael Merlino
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Recommended models:
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Recent Updates:
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May 13, 03:45 PM
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May 13, 03:45 PM
[Web Browser Content]
OpenAI Help Center
Where do I find my OpenAI API Key?
You can find your Secret API key on the API key page. Check out our Best Practices for API Key Safety to learn how you can keep your API key protected.
OpenAI API
Jun 11, 2020 — The API today provides a general-purpose "text in, text out" interface, allowing users to try it on virtually any English language task.
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May 13, 03:45 PM
[Web Browser Content]
Google Search: openai api key
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May 13, 03:45 PM
[Web Browser Content]
New Tab
OpenAI API Platform - openai.com/api/
OpenAI API Documentation:
- Overview: platform.openai.com/docs/overview
- Billing: platform.openai.com/settings/organization/billing/overview
- Projects: platform.openai.com/settings/organization/projects
- API Keys: platform.openai.com/settings/organization/api-keys
GitHub Resources:
- openai/agents.md: AGENTS.md — a simple, open format for guiding coding agents (github.com/openai/agents.md)
- disler/poc-realtime-ai-assistant: Sharing early versions of Ada, a personal AI Assistant built on OpenAI's Realtime API (github.com/disler/poc-realtime-ai-assistant)
Work/Personal:
- Michael Merlino
- Wolf Pack Meeting: Merlino / Gregory / Brian
- Michael's Fireflies Tracker
May 13, 03:45 PM
[Command-Line Output]
Fallback logic adds two code paths to debug:
- OpenAI text-embedding-3-large is higher quality
- We just confirmed it works end-to-end
Single embedding engine. Multi-purpose keys. Both kept in secrets, only OpenAI wired into the memory script. Sound right?
Known issue (not a blocker): Old Supabase memories were embedded with Gemini, so they won't match queries embedded by OpenAI — different vector spaces. That's a separate batch job.
No, not fixed. Having a working Gemini key gives you the option, but the actual problem is still there:
- The 43 old rows in Supabase = Gemini-space vectors
- The script now embeds queries in OpenAI-space
Different geometries = similarity scores are meaningless.
Two ways to actually fix it:
Option 1: Re-embed 43 rows with OpenAI (recommended). $0.001, 30 sec one-shot script. OpenAI stays primary.
Option 2: Switch script back to Gemini. Lower quality, two-store ecosystem reverts.
I still vote re-embed. Want me to run it?
May 13, 03:44 PM
Screen: Michael Merlino
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NAMERLIN0
Your primary Google account mike@merlinomarketing.com has expired, affecting GBP, Google Analytics, etc. Re-integrate
Green Grid Goblins
Sarasota, FL
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May 13, 03:44 PM
[Command-Line Output]
# Google Places API
[honcho] post-tool-use -4 captured: Edited D:\Ecosystem\secrets\MASTER_API_KEYS.env:
Key saved to line 44.
My take on 'both types or just main':
Keep both API keys in secrets. Add Gemini as fallback embedder in agent-memory.py.
Reasoning for not dual-wiring embeddings:
- Mixing embedding models in the same vector table causes drift; search results become noise.
- Fallback logic adds two code paths to debug.
- OpenAI text-embedding-3-large is higher quality than Gemini embeddings.
Single embedding engine. Multi-purpose keys. Both kept in secrets, only OpenAI wired into the memory script.
[honcho] response -4 saved response (881 chars)
Stop says: Old Supabase memories were embedded with Gemini, so they won't match queries embedded by the new model. If you want old memories searchable, they need re-embedding under the new model. That's a separate batch job—say the word and I'll write it.
May 13, 03:44 PM
[Command-Line Output]
Update( D:/Ecosystem/secrets/MASTER_API_KEYS.env )
Added 1 line, removed 1 line
# Google AI API (Gemini)
rpJ3YE1u2QZ186DcPKsT7BJBcMw
# Google Places API
[honcho] post-tool-use captured: Edited D:\Ecosystem\secrets\MASTER_API_KEYS.env:
Key saved to line 44.
Reasoning for not dual-wiring embeddings:
- Mixing embedding models in the same vector table causes drift.
- OpenAI text-embedding-3-large is higher quality than Gemini.
- Single embedding engine recommended for consistency.
Known issue: Old Supabase memories were embedded with Gemini and won't match queries embedded by OpenAI. Re-embedding the 43 records is recommended.
May 13, 03:44 PM
Known issue (not a blocker): Old Supabase memories were embedded with Gemini, so they won't match queries embedded by OpenAI — different vector spaces. New add calls work
fine. If you want old memories searchable, they need re-embedding under the new model. That's a separate batch job — say the word and I'll write it.
May 13, 03:43 PM
[Command-Line Output]
[honcho] post-tool-use: Ran smoke-test deployment validation for clickmtnded-sop.
Bash commands executed: mkdtr, ls, playwright-clt goto, and playwright-clt screenshot.
[Sync Plan]
1. Commit + push clickmtnded-sop POWD screenshots + layout tweak.
2. Commit + push deletions in Merlino SOP repos.
3. Run sync-wtkt.psl to propagate LLM wiki.
[Supabase Memory Issue]
Agent identified 43 rows in Supabase memories table. Old memories embedded with Gemini need re-embedding to match new OpenAI embeddings. Agent recommends a one-time re-embed script.
May 13, 03:43 PM
[Command-Line Output]
What's actually uncommitted from Repo clickmtnded-sop, links-sop, local-sop, meta-ads, LLM Wiki, Global CLAUDE.md
Surgical sync plan (this session only):
1. Commit + push clickmtnded-sop POWD screenshots + layout tweak
2. Commit + push the _clickmtnded/ deletions in the 4-6 affected Merlino SOP repos
3. Run sync-wtkt.psl to propagate LLM wiki to Mac/VPS
Running smoke-test instead of skill-strict story validation. Spawning one browser-qa-agent against clickmtnded-sop.vercel.app.
Want me to:
(A) Run the surgical 3-step sync (this session's work only) — recommended
(B) Run the full sync.sh blanket push (would auto-commit ALL 30+ repos)
(C) Just show me --dry diff per repo first
May 13, 03:42 PM
Screen: sync-wtkt. psl
page + log + deployment-status
New project
Stopping before I touch anything
What's actually uncommitted from
Repo
clickmtnded-sop
links-sop, local-sop, meta-ads
Bash(cd
-3
echo
clickmtnded-sop =
M app/layout.tsx
?? proof-homepage-2026-05-13.png
+34 lines (ctrl+0 to expand)
L (timeout 1m 30s)
site-sop
echo
clickmtnded-sop
gtt
status
--short && gtt log
--onel ine
[honcho] post-tool-use -4 captured: Ran: cd
L PostToolUse:Bash says:
"D: /C1audeDev/OO_
GITHUB/cltckmtnded-sop"
dangerous —
the surface is messy.
THIS session
( success)
Notes
-sop,
Changes from our work
3 POWD screenshots + app/layout.tsx
_ clickmtnded/ dir deletions
tweak
Safe to commit + push
Safe —
directly from refactor
[honcho] post-tool-use -4 captured: Ran: find
L PostToolUse:Bash says:
L Loaded
The full ecosy
May 13, 03:42 PM
Want me to:
- (A) Run the surgical 3-step sync (this session's work only) — recommended
- (B) Run the full sync.sh blanket push (would auto-commit ALL 30+ repos)
- (C) Just show me --dry diff per repo first
May 13, 03:42 PM
What I'm NOT touching (unrelated WIP)
┌──────────────────────────────────────────────┬─────────────┬──────────────────────────────────┐
│ Repo │ Dirty files │ Risk │
├──────────────────────────────────────────────┼─────────────┼──────────────────────────────────┤
│ archangel-variations │ 240 │ Could be WIP creative variations │
├──────────────────────────────────────────────┼─────────────┼──────────────────────────────────┤
│ _working-on │ 174 │ Scratch space │
├──────────────────────────────────────────────┼─────────────┼──────────────────────────────────┤
│ merlino-mastermind-docs │ 141 │ Doc drafts │
├──────────────────────────────────────────────┼─────────────┼──────────────────────────────────┤
│ pieces-integration, cli-tracker, cliit, etc. │ 8-19 each │ Active project WIP │
└──────────────────────────────────────────────┴─────────────┴──────────────────────────────────┘
May 13, 03:42 PM
Screen: [honcho] response -4 saved response (866 chars)
L Stop says:
* Churned for 1m Ils
Known issue (not a blocker): Old Supabase memories were embedded with Gemini, so they won't match
fine. If you want old memories searchable, they need re-embeddtng under the new model. That's a
[honcho] response -4 saved response (866 chars) what is BVEST way to fix this?
L Stop says:
[honcho] user-prompt injected conclusions
L UserPromptSubmtt says:
bash
cmd
Known
fine.
-d
x
bash
x
bash
add mirrors writes to Mem0
Live (auto-wired)
issue (not a blocker): Old Supabase memories were embedded with Gemini, so they won't match queries embedded by OpenAI —
different vector spaces.
If you want old memories searchable, they need re-embeddtng under the new model. That's a separate batch job
say the word and I'll write
May 13, 03:41 PM
[REDACTED:GCP API key]google ai stuido key save it please and make a copy of both types or just the main one what do you think
May 13, 03:41 PM
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n8n888
gen-lang
n8n888
gen-lang
-client-0673394765
-client-0213457819
-client-0213457819
Created
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Apr 7, 2026
sep 26, 2025
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May 13, 03:41 PM
[Command-Line Output]
Known issue: Old Supabase memories were embedded with Gemini and do not match OpenAI embeddings due to different vector spaces.
[honcho] response: You only have 43 rows in the Supabase agent_memories table. Re-embedding these 43 records is the best approach as it costs pennies, takes 30 seconds, and avoids overengineering.
URL: https://gmgxxtqgshbbgzhqzngq.supabase.co
[honcho] post-tool-use: Ran SUPABASE_URL=$(grep) (success)
Proposed action: Write and run a re-embed script for the 43 records.
May 13, 03:41 PM
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May 13, 03:41 PM
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May 13, 03:41 PM
[Web Browser Content]
Google Search: googl gemini api
Google AI for Developers
https://ai.google.dev/gemini-api/docs
Gemini generateContent API | Google AI for Developers
Input millions of tokens to Gemini models and derive understanding from unstructured images, videos, and documents.
API keys
To use the Gemini API, you need an API key. This page outlines the process.
Pricing
$0.067 per 1K image, $0.101 per 2K image, and $0.151 per 4K.
Quickstart
Note that all code samples in the Gemini API docs assume that.
Models
Gemini 3.1 Flash Live. High-quality, low-latency Live API model for interactions.
Interactions API
The Interactions API is the new standard primitive for building.
May 13, 03:40 PM
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Start exploring and building with Google's latest models. Login. Get started. Build with Google AI Studio. Go from prompt to production with Gemini, Veo, Nano.
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May 13, 03:40 PM
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May 13, 03:40 PM
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Model: nano, gen-lang-client-0648166742
Project: BirdseyeR01, Bolt, bolt-442314
May 13, 03:40 PM
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Using Gemini API keys | Gemini generateContent API | Google AI for Developers
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Using Gemini API keys
To use the Gemini API, you need an API key. This page outlines how to create and manage your keys in Google AI Studio as well as how to set up your environment to use them in your code.
Create or view a Gemini API Key
You can create and manage all your Gemini API Keys from the Google AI Studio API Keys page.
Options to connect to the Gemini API:
- Setting your API key as an environment variable
- Providing your API key explicitly
Note: For initial testing, you can hard code an API key, but this should only be temporary since it's not secure.
May 13, 03:40 PM
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BirdseyeROI
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Project quota tier unavailable. Please contact your project administrator for assistance.
Time Range: 1 Day
May 13, 03:40 PM
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May 13, 03:40 PM
[Web Browser Content]
Hi Michael, where should we start?
Boost my day | Help me learn | Create music | Create image | Write anything
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May 13, 03:40 PM
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May 13, 03:40 PM
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Calendar View: May 10 - 16, 2026
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May 13, 03:40 PM
[Command-Line Output]
Terminal session managing agent memory and MCP configurations.
Key operations:
- Refactoring agent-memory.py to use OpenAI text-embedding-3-large.
- Integrating Mem0 MCP server for unified memory management.
- Troubleshooting Supabase vector space mismatches between Gemini and OpenAI embeddings.
- Building unified merlino-sops MCP for agent routing.
May 13, 03:39 PM
Known issue (not a blocker): Old Supabase memories were embedded with Gemini, so they won't match queries embedded by OpenAI — different vector spaces. New add calls work
fine. If you want old memories searchable, they need re-embedding under the new model. That's a separate batch job — say the word and I'll write it.
⎿ Stop says: [honcho] response → saved response (866 chars)
May 13, 03:39 PM
[Command-Line Output]
[honcho] post-tool-use -4 captured: Edited D:\Ecosystem\agent-memory\agent-memory.py:
Bash(cd /d/Ecosystem/agent-memory && python agent-memory.py search-all "HawkeyePanel" --limit 3 2>&1 | tail -30)
Searching all agent memories for: HawkeyePanel
HTTP 400 error: {"code" : "22000", "details" : null, "hint" : null, "message" : "different vector dimensions 3072 and 1536"}
Shell cwd was reset to D:\ClaudeDev
[honcho] post-tool-use -4 captured: Ran: cd /d/Ecosystem/agent-memory (success)
[honcho] post-tool-use -4 captured: Edited C:\Users\mtkem\.claude\CLAUDE.md:
Added: clickmtnded, ClickMtnded, SOPs
[honcho] response -4 saved response (1699 chars)
Recommended run order:
/sync -4 /ut-revtew clickmtnded-sop.vercel.app -4 /pause.
Why /sync first: You just registered clickmtnded-sop as an MCP server on Windows only. Your Mac, VPS1-3, and Hermes don't know it exists yet.
/sync propagates:
- New MCP registration to other machines
- Updated CLAUDE.md (clickmtnded-sop listed as active project)
- LLM wiki updates
- Memory files
Why /pause second: Natural breakpoint after shipping. Writes .continue-here.md, full memory snapshot, WIP commits.
May 13, 03:38 PM
/ui-review clickminded-sop.vercel.app
May 13, 03:38 PM
[Command-Line Output]
Confirmed the stale-env-var bug. Testing the master file key directly to see if THAT one has quota.
File: D:/Ecosystem/secrets/MASTER_API_KEYS.env
Found it. Master file key returns HTTP 200, env var key is dead. The loader checks env first, so the stale env var wins. Flipping priority — master file first, override second.
Update: D:/Ecosystem/agent-memory/agent-memory.py
Added 6 lines, removed 4 lines.
Error: HTTP 400: different vector dimensions 3072 and 1536.
Clarification:
Stale Windows env var: sk-proj-oe6n0dQ2Xt... (DEAD - 429 insufficient quota)
MASTER_API_KEYS.env line: sk-proj-_BfDeOs... (WORKS - HTTP 200 confirmed)
Proposed fix: Swap to text-embedding-3-large to match DB schema vector(3072).
May 13, 03:37 PM
[Command-Line Output]
Update Merlin + Knox + Matteo to query dev-sop. Picasso still has a gap on images.
[honcho] response -4 saved response (2711 chars)
Crunched for 36s.
[honcho] user-prompt f- injected conclusions (cached)
Building unified merlino-sops MCP.
[honcho] post-tool-use -4 captured: Edited D:\Ecosystem\agent-memory\agent-memory.py
[honcho] post-tool-use -4 captured: Ran: python -c "import ast..." (success)
[honcho] post-tool-use -4 captured: Ran: cd /d/Ecosystem/agent-memory (success)
Searching all agent memories for: HawkeyePanel
HTTP 429 error: OpenAI is now being called, but the key returns insufficient quota. Per memory, there's a known stale OPENAI_API_KEY env var on Windows shadowing the master file.
Confirmed the stale-env-var bug. Testing the master file key directly to see if that one has quota.
Found it. Master file key returns HTTP 200, env var key is dead. The loader checks env first, so the stale env var wins. Flipping priority: master file first, env override second.
May 13, 03:36 PM
[Chat Transcript]
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May 13, 03:36 PM
[Chat Transcript]
# client-ascend-behavioral-health-internal
Michael Merlino: Let's make sure we have mental health clinic etc as gmb categories.
GK: @GK updated it, Can I drop UTM tag please? Do ya use them a specific way?
Michael Merlino: No specific way. We do number swapping with the gmb through call tracking metrics. Ok I used https://ascendrecoverycenternm.com?utm_source=gmb&utm_medium=883-lead-ave-nm
Henri L: @Michael Merlino @GK Ascend/Archangel GMB categories suggestions. Regarding George's request to "make sure we have mental health clinic etc as gmb categories". Below are my findings and suggestions. I can make the changes, or you can @Michael Merlino. I am here to help.
*GMB Category Optimization — May 2026*
Competitor frequency:
- Addiction treatment center — 6 competitors (20.00%)
- Alcoholism treatment program — 6 (20.00%)
- Mental health service — 4 (13.33%)
- Rehabilitation center — 4 (13.33%)
- Mental health clinic — 3 (10.00%)
- Psychiatrist — 2 (6.67%)
- Counselor — 1 (3.33%)
*Archangel | 770 us-I, Iselin, NJ*
Current: Mental health service
Add: Addiction treatment center, Alcoholism treatment program, Rehabilitation center, Mental health clinic
Michael Merlino: All locations offer mental health @Henri L or only a few or NM?
Henri L: @Michael Merlino Yes, They all offer mental health services.
Michael Merlino: Then yes! For sure & those look good (changes).
May 13, 03:36 PM
[Command-Line Output]
Option B: Build the MCPs now, content from archive
- Use archive files as source material
Build openclaw-sop + infra-sop (or merge into dev-sop) + image-sop
- Wire agents
Then the archive stays clean
Option C: Just ingest archived content into existing dev-sop MCP
All server/infra/memory/openclaw goes into dev-sop as new topics
No new MCPs
Update Merlin + Knox + Matteo to query dev-sop
Picasso still has gap on images
Which path? I'll execute it properly this time
— not just move files.
L Stop says: [honcho] response -4 saved response (2711 chars)
* Crunched for 36s
If you just need to go add them to this fucking MCPSOP resource, then do that.
Also, we're not using 14 MCPs. Make one Merlin SOPs with categories, right? Also, inside the MCP could be a category per agent, per domain, and then a master one to route them everywhere or something like that, right? But right now let's get everything because we've been working we're starting to lose it here we're slipping.
1135 AM
5/13/2026
May 13, 03:35 PM
Screen: Honest options
Option A: Restore everything, do it properly
Restore 13 OpenClaw/server/memory from archive -4 runtime
agent frontmatter updates:
matteo-jr.md -4 reference mcp__openclaw-sop__*
knox.md -4 reference mcp__infra-sop__* (or expanded mcp__dev-sop__*)
merlin.md -4 reference mcp__dev-sop__* explicitly for memory/infra
picasso.md -4 reference image patterns somehow
For each archived group -4 either:
1. Build a new MCP for that domain (openclaw-sop, infra-sop, memory-sop,
2. Ingest content into existing SOP (server-hardening -4 dev-sop MCP)
3. Verify agent frontmatter points to the MCP they need
Required new MCPs based on what I archived:
openclaw-sop for Matteo
infra-sop for Knox (or expand dev-sop)
memory-sop for Merlin/Hindsight ops (or expand dev-sop)
image-sop for Picasso (or sk
May 13, 03:35 PM
Right — Matteo owns OpenClaw. Archiving those 4 + the 9 from my prior list
May 13, 03:35 PM
You shouldn't ask me so many options when you know what you're supposed to be doing, right? So if you need to restore the skills, restore them. If you just need to go add them to this fucking MCPSOP resource, then do that.
Also, we're not using 14 MCPs. Make one Merlin SOPs with categories, right? Also, inside the MCP could be a category per agent, per domain, and then a master one to route them everywhere or something like that, right? But right now let's get everything because we've been working we're starting to lose it here we're slipping.
May 13, 03:35 PM
MCP could be a category per agent, per domain, and then a master one to route them everywhere, or something like that, right? But right now, let's get everything because we've been working, we're starting to lose it here, we're slipping.
May 13, 03:35 PM
For the skills, restore them. If you just need to go add them to this fucking MCP SOP resource, then do that. Also, we're not using 14 MCPs. Make one Merlin SOP with categories, right? Also inside the...
May 13, 03:34 PM