tma1-ai/tma1/tma1-search
Claude Code and agent skill by tma1-ai/tma1
- community
Checking that the SKILL.md file is still in the repository.
Search past agent sessions on this project by keyword, and read back any session's conversation. Invoke when the answer lives in an earlier session — how something was fixed before, what was decided, what an agent tried last week — or when the user hands you a session id. Trigger phrases: \"what did we decide about\", \"how did we fix this before\", \"search my sessions\", \"find that session\", \"read session <id>\", \"之前是怎么解决的\", \"上次讨论过\", \"找一下以前的 session\", \"/tma1-search\".
Install
npx vskill@latest install tma1-ai/tma1/tma1-searchSKILL.md
TMA1 Session Search
TMA1 keeps every agent session on this machine — yours and other agents' — in a local database. This skill is the read path: find the session, then read it.
Two entry points
--session takes a full id or a prefix of 6+ characters — the abbreviated id in the <tma1-context> block works. Do not infer a session id from a bare token: commit hashes look the same, and cp: ids don't look like hex at all. Anything that isn't behind --session is search text.
Workflow
- Search —
mcp__tma1__search_sessionswith:
query: the keyword text (everything that isn't a flag)agent_source:--agentvalue if given (codex/
copilot / claude / self); omit for every agent
since_min:--days N× 1440, default omitted (7 days)project:"*"when--all-projectsis given; otherwise omit
- Report the matching sessions with their snippets, so the user can
pick. One obvious hit and a clear question → go straight to step 3.
- Read —
mcp__tma1__get_session_transcriptwith thesession_id
from step 1. has_more: true means older messages exist; call again with the returned next_offset if the answer isn't in this page.
- Answer with quotes. The value here is the earlier session's actual
words, not your summary of them.
Reading the search response
sessions[]—session_id,agent_source,last_activity_ago,
hit_count, and snippets[] (each a window around a match).
match_mode—termis the indexed pass: whole words, case-sensitive.
substring means that pass found nothing, so the search widened to a case-folded substring scan; results may include noise, say so.
scope_truncated: true— this project has more sessions in the window
than the search scanned. Narrow with --agent or --days.
note— present only when nothing matched. Say so plainly; don't invent
a plausible past session.
Search behaviour worth knowing
The indexed pass matches whole words and is case-sensitive, so Cwd does not find peerCwdFilter and neither does peercwdfilter. Search for the identifier as it is written in the code. When that pass finds nothing the search widens to a case-folded substring scan and tells you so with match_mode: substring — that is the mode that rescues a mistyped case, at the cost of noisier hits.
Related
- Browsing by agent rather than keyword →
/tma1-peer. - Aggregates over the raw tables (cost by model, tool failure rates) →
the tma1 skill's exec_query.
Security
- Security scanPassed, 90 of 100Pattern checks on the skill's files.
- Model reviewPassed
Quality evaluation
- Task evaluationNot runNo evaluation yet. Run one in Skill Studio.
Source
- SKILL.md in the repositoryCheckingclaude-plugin/skills/tma1-search/SKILL.md
Popularity
- 7-day trend score
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Works with
Any agent vskill installs to: 56 targets in all. These 39 have a page on this site.
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- Cursor
- GitHub Copilot
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- Codex
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- Amp
- Roo Code
- Goose
- Continue
- Kilo Code
- Junie
- Trae
- OpenHands
- Qwen Code
- AI Agent
- Tabnine Chat
- Sourcegraph Cody
- Amazon Q
- Firebase Genkit
- Sweep
- Devin
- Phind
- Mentat
- Claude Desktop
- Aider
- GPT Pilot
- Plandex
- bolt.new
- v0
- Replit Agent
- Anse
- TypingMind
- BetterChatGPT
- LibreChat
- Warp AI
- Pieces
- Fig AI
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