self-report
Skill2 starsChanged 6 months agoMITView on GitHub
File GitHub issues against joestump/claude-skills when another skill in this repo hits friction during a run. Other skills in this repo delegate their self-evaluation reporting to this skill rather than implementing their own filing logic. Triggers when another skill explicitly invokes self-report after detecting that its trip thresholds were exceeded (tool-call budget, repeated bug retries, material assumptions, render integrity issues, user pushback in same turn), or when the user explicitly invokes /self-report. If multiple skills from this repo ran in the same session and each independently tripped, file one issue per skill — never bundle reports for different skills into a single issue. Each issue is labeled with both skill-self-report and skill:<skill-name> so they can be filtered per-skill on the issues tab. Issue bodies must never contain user data, account balances, names, or document contents — only meta-signals about how the run went.
In this repository7 other files it gives its agents.
- CLAUDE.mdCLAUDE.md
- cut-releaseSkill
- gemini-mockupSkill
- outline-runbook-curatorSkill
- pr-sweepSkill
- refresh-miatrix-tokenSkill
- retirement-planSkill
The file
We split this skill into the rules it gives an agent
8 rules. About 0 are common, 7 are distinctive, and 1 is very specific to this project.
≈0
Common · estimate
Many files like this have a rule of this kind.
≈7
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
- Very specific: line 20
Do not self-report this skill: If self-report itself fails, surface the failure to the user in chat.
- Distinctive: line 26
When multiple issues are filed in one session, mention this to the user once at the end:
- Distinctive: line 30
Don't repeat. Don't nag.
- Distinctive: line 53
Never include user financial data, account balances, names, document contents, addresses, partner names, or direct quotes from user …
- Distinctive: line 54
Never bundle reports for multiple skills into a single issue.
- Distinctive: line 55
Never file an issue for a clean run.
- Distinctive: line 56
Never bring up the self-report more than once per session to the user.
- Distinctive: line 57
Never self-report this skill.
≈ “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
self-report
This skill is the single owner of "skill hit friction → file a GitHub issue." Other skills in this repo do not implement their own filing logic. They detect their own trip conditions, then hand off to self-report with a skill name, a short title, and a body.
When to run
- Another skill in this repo signals that its run tripped one or more thresholds defined in that skill's own
references/self-eval.md. Common signals (each skill defines its own exact thresholds):- Tool-call budget exceeded for the run mode
- Same bug retried more than twice
- More than 3 material assumptions during the run
- Render-integrity failures (literal
${...},NaN/undefinedin output, missing tabs, etc.) - User pushback in the same turn ("wrong", "ugly", "broken", "fix this")
- The user explicitly invokes
/self-report.
Do not self-report this skill. If self-report itself fails, surface the failure to the user in chat. Filing-about-filing is a recursion trap.
Multi-skill runs
If two or more skills from this repo ran in the same session and each independently tripped, file one issue per skill. Never bundle reports for different skills into a single issue — they go to different audiences (the maintainer of each skill) and have different fix surfaces.
When multiple issues are filed in one session, mention this to the user once at the end:
I noticed friction in this run across
retirement-planandweekly-review. I've filed one issue per skill. [link, link]
Don't repeat. Don't nag.
Workflow
For each skill that tripped:
- Build the issue body following
references/issue-format.md. Lift the run-specific facts (tool-call count, retry count, phase reached, failure-signal checkboxes) from the calling skill's run state. - Sanitize. Apply
references/privacy.mdbefore writing the body — no balances, names, document contents, addresses, partner identifiers, or direct quotes from user docs. - File via the path that's available (in order):
- GitHub MCP, if available. Repo:
joestump/claude-skills. Labels:skill-self-reportandskill:<skill-name>. Title:[<skill-name>] <short summary>. ghCLI viascripts/file_issue.sh— call it once per skill:file_issue.sh <skill-name> "<title>" <body-file>. The script ensures the per-skill label exists, then files.- Fallback: the script writes the body to
$SKILL_ISSUE_OUT_DIR/skill-issue-<skill-name>.md(default/mnt/user-data/outputs/) and prints a prefilledhttps://github.com/joestump/claude-skills/issues/newURL withlabels=skill-self-report,skill:<skill-name>&title=...query params.
- GitHub MCP, if available. Repo:
Mention to the user once per session, only on the fallback path:
I noticed friction in this run. I've written self-reports to
skill-issue-*.md— paste them as new issues at https://github.com/joestump/claude-skills/issues/new if you'd like to track them.
Labels
skill-self-report— applied to every issue this skill files. Already exists on the repo.skill:<skill-name>— per-skill filter. The script auto-creates this label on first use with color#c5def5. Examples:skill:retirement-plan,skill:weekly-review.
Things to never do
- Never include user financial data, account balances, names, document contents, addresses, partner names, or direct quotes from user documents in an issue body.
- Never bundle reports for multiple skills into a single issue.
- Never file an issue for a clean run.
- Never bring up the self-report more than once per session to the user.
- Never self-report this skill.
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.

