rumo-reflect
Skill7 starsChanged 14 days agoMITView on GitHub
Use only when the user explicitly asks to reflect on, review, or learn from the current session, such as "reflect", "复盘一下", or "what should the skills learn from this", or accepts an offer to review the session. Find recurring mistakes, user corrections, and skipped rules in the conversation, propose the strongest place to fix each one (a structural change, a check, a pinned test, skill text, or project instructions), and discuss every item with the user, who decides; nothing changes without approval. Do not use for progress updates or handoff documents (use rumo-handoff), end-of-task summaries, or daily reports.
We split this skill into the rules it gives an agent
4 rules. About 0 are common, 3 are distinctive, and 1 is 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.
1
Very specific
Tied to their project's names, files or tools. Probably skip.
- Common
- Distinctive
- Very specific
- Distinctive: line 12
Read the current conversation and the files it changed.
- Distinctive: line 27
Remove the cause with structure, so the mistake can no longer be made: delete the outdated pattern an agent would copy, merge lists that …
- Distinctive: line 46
Run the checks the edited repository requires for those files.
- Very specific: line 47
Do not commit or push unless the user asks.
≈ “Common” is an estimate: at least 1 in 5 of the 308,232 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
Rumo Reflect
Turn what went wrong in this session into a fix the next session cannot miss, and change only what the user approves.
Collect Candidates
Read the current conversation and the files it changed. Look for:
- corrections the user made, and repeated attempts or workarounds before something worked;
- a rule in a skill,
AGENTS.md,CLAUDE.md, or memory that the agent broke; - a skill that should have loaded and did not, or loaded when it should not have;
- a step that cost time and produced nothing.
Keep a candidate only when the situation will plausibly recur and a fix would change a future decision. Drop one-offs, matters of taste, and mistakes an existing rule already prevented. When a rule existed and was still broken, the candidate is why it was missed: its trigger wording, its placement, or a step that hides it.
Record for each candidate: what happened with its place in the conversation, the decision it would change next time, the proposed location, and the proposed change in one or two sentences.
Pick The Strongest Place
Propose the first location that can hold the fix:
- Remove the cause with structure, so the mistake can no longer be made: delete the outdated pattern an agent would copy, merge lists that must be kept in sync by hand into one source, or make the parser or validator reject the wrong form outright.
- An automatic check the repository already runs: a validator, lint rule, script, test, or hook. Its error names the fix.
- A pinned rule test, when the repository keeps one for skill text.
- Skill text: the
descriptionwhen triggering failed, the body when a step was skipped or unclear. - Project instructions (
AGENTS.md,CLAUDE.md) or the client's memory, for facts about one project or user.
For each candidate, say why each higher level cannot hold it. Prefer tightening an existing rule over adding a new one, and a new skill only when no skill owns the situation. Keep private project facts out of shared skills; put them in a project profile (rumo-project-profile) or the project's own files.
Discuss, Then Decide
Show the candidates as a numbered table: lesson, evidence, proposed location, proposed change, and your recommendation (accept, reject, or backlog) with one line of reasoning. Then stop and wait.
The user decides every item. Apply only items the user explicitly accepts; a general "ok" accepts only the recommendations in the table shown. Backlog items go only where the user says; never open issues, tickets, or notes on your own. A changed proposal is a new item and needs its own approval.
Apply
- Edit only the accepted items, at the agreed location. Follow
rumo-prosefor skill and instruction text when it is installed. - Edit the source of a skill, not an installed copy that an update overwrites, such as a plugin cache. When the source is outside the current workspace or belongs to someone else, give the user the exact proposed edit instead of writing it.
- For a new check or pinned test, run it against the real mistake from this session and confirm that it fails, using the pre-fix version when the mistake was already corrected; a check that never caught the mistake proves nothing. Record the command and result.
- Run the checks the edited repository requires for those files.
- Do not commit or push unless the user asks; then follow
rumo-git-commit.
Stop Conditions
- Nothing in the session recurs or would change a decision: say so. Do not invent lessons to fill the table.
- A fix needs a product decision, another person's repository, or access you do not have: report it as a proposal and stop.
Report
Applied items with path and one line each, rejected items with the user's reason, backlog items with where they were recorded, and the checks run on the changed files.
In this repository22 other files it gives its agents.
- AGENTS.mdAGENTS.md
- CLAUDE.mdCLAUDE.md
- rumo-agent-collaborationSkill
- rumo-clarifySkill
- rumo-coding-guidelinesSkill
- rumo-database-change-safetySkill
- rumo-debugSkill
- rumo-explainSkill
- rumo-filesystem-safetySkill
- rumo-frontendSkill
- rumo-git-commitSkill
- rumo-handoffSkill
- rumo-interfaceSkill
- rumo-lifecycle-safetySkill
- rumo-planSkill
- rumo-project-profileSkill
- rumo-proseSkill
- rumo-remote-opsSkill
- rumo-reviewSkill
- rumo-setupSkill
- rumo-testSkill
- rumo-verifySkill
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.

