// Diagnose why a skill is missing from Pi /skill or Cursor lists. Use when a skill exists on disk but does not appear, Pi shows only project or extension skills, or after adding a repo skill under .agents/skills/.
| name | skill-not-showing |
| description | Diagnose why a skill is missing from Pi /skill or Cursor lists. Use when a skill exists on disk but does not appear, Pi shows only project or extension skills, or after adding a repo skill under .agents/skills/. |
| user_invocable | true |
Read-only diagnostic. Confirm with the user before changing settings or running sync scripts.
includeDefaults is false → Pi loads only paths in ~/.pi/agent/settings.json skills[]. Extension skills (why, autocontext, …) are separate from repo SSOT under .agents/skills/.
| Step | Command |
|---|---|
| Sync + link + verify | bash scripts/ensure-repo-skills.sh |
| Check only | npm run verify:pi-skills |
Then restart Pi and try /skill:<name>.
name matches the folder you expect.~/.pi/agent/settings.json lists ~/.agents/skills (and cwd .pi/settings.json is not overriding).ls -la ~/.agents/skills/<name> .cursor/skills/<name> — broken symlinks → re-run ensure-repo-skills.sh.zereight-mode) means SSOT paths are not registered — not a content bug in the skill file.ljg-skill-map — global ~/.agents/skills layoutskill-cleaner — duplicate roots / token auditRun iterative agent evaluation and improvement loops (judge, improve, scenarios, playbooks) via pi-autocontext or autoctx CLI. Use when improving repeatable agent workflows (review rubrics, skill quality, scenario-based feedback), checking run status, or accumulating knowledge—not for one-off code edits or repo pattern drift (use continuity) or single PR review (use zereight-review).
Pi-native evaluate→improve→persist harness. Provides a systematic loop for generating candidates, judging them against rubrics, and accumulating knowledge as playbooks. Use for iterative output improvement, not for one-off edits (use continuity) or single PR review (use zereight-review).
Audit agent skills — token cost, duplicates, outdated plugin versions, unused skills, and overly long descriptions. Use when trimming skill prompt budget, finding duplicate or unused skills, auditing plugin versions, or deciding which skills to remove.
Comprehensive code review skill for practical PR feedback. Use for feature, bugfix, and refactor reviews. Prioritizes correctness, edge cases, logic invariants, fallback-chain safety, async state transitions, architecture analysis, OWASP security, and clear actionable feedback.
Skill map and inventory workflow. Use for scanning installed skills, skill overview, 스킬 목록, skill map.
Inspects Cursor agent transcript history, analyzes repeated assistant mistakes, and turns durable learnings into corrective skills or context updates. Use when the user asks to review previous Cursor chats, learn from a failed interaction, run /session-lessons, or stop the model repeating a mistake.