Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx skills add skynetcmd/m3-memory --skill m3-find-in-chatgit clone --depth 1 https://github.com/skynetcmd/m3-memoryWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/skynetcmd/m3-memory/m3-find-in-chat)<a href="https://agentmods.dev/skills/skynetcmd/m3-memory/m3-find-in-chat"><img src="https://agentmods.dev/badge/skills/skynetcmd/m3-memory/m3-find-in-chat/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/skynetcmd/m3-memory/m3-find-in-chat"><img src="https://agentmods.dev/badge/skills/skynetcmd/m3-memory/m3-find-in-chat.svg" alt="Reviewed on agentmods" width="80" height="20"></a>What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00023 | $0.00184 |
| Opus 5 | $0.00012 | $0.00092 |
| Sonnet 5 | $0.00005 | $0.00037 |
| Haiku 4.5 | $0.00002 | $0.00018 |
Grade A, and why
m3-find-in-chat scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 11d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
What it actually says
M3 Find In Chat
When to Use
Use this skill when the user wants to search past conversation transcripts or look up specific things they discussed with the assistant in prior turns or sessions.
Instructions
Call the m3:chatlog_search MCP tool with query="$ARGUMENTS", k=10.
Group results by conversation_id and present chronologically. For each match show:
- timestamp + host_agent (claude-code / gemini-cli / antigravity-cli)
- model_id
- 2-line excerpt with the matching span highlighted
If results span more than one conversation, mention that — the user may want to drill into a specific session via chatlog_list_conversations (a related MCP tool).
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 11d ago First seen · 19 lines · 23 tokens per session scan A 03dd3d762bc7
m3-find-in-chat is a skill published in the GitHub repository skynetcmd/m3-memory (24 stars, last pushed today), licensed Apache-2.0. It adds 23 tokens to every session and 184 once invoked, about $0.0001 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.
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