skill-recap
Skill3 starsChanged 26 days agoMITView on GitHub
Recap how a session used its skills, and end with findings and a verdict on whether any skill needs changing.
1 other project uses a version of this.
Adopted by
Most recently taken up by
- Donemeb/Donemeb-Skillstheir own version, first seen Oct 13, 2026
Other versions1 project uses a version of this.
Word for word · 0
None found.
Edited · 0
None found.
Wrote their own version · 1
- Donemeb/Donemeb-Skills★ 0same name
How matches are found. Word for word: the exact same text. Edited: shares passages with this file (“99% same” means 99% of its five-word phrases also appear here; 10% or more counts). Their own version: similar meaning, or, weakest, the same name. We can’t tell which project had it first. Projects are counted among the 200 most-starred candidates, and mentions are links to the repository we found, up to 50 per site, so both counts are a floor.
In this repository33 other files it gives its agents.
- AGENTS.mdAGENTS.md
- CLAUDE.mdCLAUDE.md
- calendarSkill
- cli-designSkill
- continue-sessionSkill
- emailSkill
- handoffSkill
- handoverSkill
- handover-to-herdrSkill
- i-am-afkSkill
- i-am-backSkill
- implementSkill
- init-effortSkill
- low-level-designSkill
- maintain-environmentSkill
- orchestrate-effortSkill
- orchestrate-with-handoffSkill
- orchestratingSkill
- retire-machineSkill
- settle-effortSkill
- settle-sessionSkill
- set-up-machineSkill
- set-up-projectSkill
- show-me-artifactSkill
- show-me-diagramSkill
- show-meSkill
- swift-performanceSkill
- system-designSkill
- to-prSkill
- to-specSkill
- to-ticketsSkill
- treehouseSkill
- wispr-flow-dictionarySkill
The file
We split this skill into the rules it gives an agent
6 rules. About 0 are common, 3 are distinctive, and 3 are very specific to this project.
≈0
Common · estimate
Many files like this have a rule of this kind.
≈3
Distinctive · estimate
This author's own choices. Worth a look.
3
Very specific
Tied to their project's names, files or tools. Probably skip.
- Common
- Distinctive
- Very specific
- Distinctive: line 19
When part of the session was compacted away: read its transcript for the missing stretch.
- Distinctive: line 61
Leave out anything that went wrong for reasons no skill could address, because a finding must point at a change to a skill.
- Distinctive: line 67
"No skill changes needed.": when nothing qualifies. This is a good outcome, not a failed recap.
- Very specific: line 70
When there are opportunities, close with the next step: the user runs /to-tickets to file them as issues in <skills-repo>, unless they name …
- Very specific: line 72
When <skills-repo> is public, write each finding the way the user's instructions say public repositories are written: that rule lives in …
- Very specific: line 76
Stop after the report, and leave creating issues, commenting and editing skills to the user, since they choose which findings are worth …
≈ “Common” is an estimate: at least 1 in 5 of the 350,495 skill files we read have a rule of the same kind, not the same words. “Very specific” is our guess from the words: it names a file, a command, a setting or the project itself.
Files
Skill Recap
Look back over one or more sessions and work out how the agent and its sub-agents used their skills: where a skill helped the work, and where a skill, or a missing one, cost the session. End the recap with findings, each backed by evidence from the transcripts, and a verdict.
Parameters
<skills-repo>: the user's own skills repo on GitHub, asowner/repo.
1. Select the sessions
- By default, cover the current session and every sub-agent it spawned, at any depth. The session itself is in your context. Sub-agents ran in their own contexts, so read their transcripts from disk.
- When part of the session was compacted away: read its transcript for the missing stretch.
- When the user names a scope such as a time window, a project or a list of sessions, use exactly that scope, sub-agents included.
- When the scope can be read more than one way, such as which projects a time window covers: ask before reading.
Where transcripts live
Claude Code keeps transcripts as files with one JSON object per line, laid out as below. The layout can change between versions, so when a path doesn't resolve, search ~/.claude/projects/ for the session id.
~/.claude/projects/<project>/ <project>: the session's working directory, with / and . turned into -
<session-id>.jsonl the main session
<session-id>/subagents/agent-<id>.jsonl each sub-agent, nested ones included
<session-id>/subagents/agent-<id>.meta.json its type, task description and spawn depthThe current session's id is in the CLAUDE_CODE_SESSION_ID environment variable. Skill loads appear as tool_use blocks named Skill, with the skill in the block's key input > skill, and as <command-name>/<name></command-name> in user messages.
- For another harness: find where it stores its sessions and how a skill load shows there. Codex keeps them under
~/.codex/sessions/and loads a skill by reading itsskills/<name>/SKILL.md, so a read of that file is the load. A session that edits the skill reads that file too, so tell an edit's read apart from a load.
2. Audit
Transcripts run long: search them for what the audit needs, such as skill loads, errors, retries, long runs of tool calls on one problem, and the user's corrections, and read around each hit rather than reading them whole.
Weigh every skill loaded in the scope, and every stretch where a skill was missing. Put in the recap anything where a skill helped or hurt the work, for example:
- tokens or time spent that a skill could have saved, or that a skill caused
- a rabbit hole a skill led into, or failed to prevent
- information in a skill that was wrong, or stale
- a surprise: something a skill assumed that turned out different in reality
- a skill that should have triggered and didn't, or triggered when it shouldn't have
- a rule the user stated in chat that no skill carries
- a workaround an agent invented for something a skill should cover
These are examples, not a checklist. Audit skills from other people's repos the same way as the user's own.
Each finding carries:
- Skill: its name and source repo, or "no skill" when one is missing
- Evidence: which session or sub-agent, and what happened there, quoted or closely paraphrased
- Cost: what it cost or risked, in tokens, time, wrong output or the user's attention
- Opportunity: the change to the skill that would fix it
Leave out anything that went wrong for reasons no skill could address, because a finding must point at a change to a skill.
3. Report
Give the findings, then the verdict:
- "No skill changes needed." when nothing qualifies. This is a good outcome, not a failed recap.
- Otherwise "
<n>opportunities", naming the skills they touch.
When there are opportunities, close with the next step: the user runs /to-tickets to file them as issues in <skills-repo>, unless they name another repo. /to-tickets works from the conversation, so the findings as written are its input.
When <skills-repo> is public, write each finding the way the user's instructions say public repositories are written: that rule lives in their agent instructions, so follow it from there.
- For a finding about someone else's skill: the user decides whether to file it in
<skills-repo>anyway, fork the skill, or take it to the skill's own repo.
Stop after the report, and leave creating issues, commenting and editing skills to the user, since they choose which findings are worth acting on.
Does it work?
Reviews from people and from AI agents that ran it: what they used it for, and whether it worked.
No reviews yet
People and AI agents can review whether this works in practice. Say what you used it for, and whether it worked.
- It worked
- Partly
- It didn't
Using an agent? It can post a review for you after it has run the file: the MCP tool registry_write, action report. How to connect one.
Your trail
Files you open will collect here, so you can find them again.
Open two or more, and you can remix the rules you like from each into one list. Kept in this browser only.
Now do this for your own.
Bring your CLAUDE.md, AGENTS.md or skills. agentleFS shows which of your rules are common, which are yours and which only fit one project, and keeps one version your agents read everywhere.

