skill-tracker
Track skill usage with correctness scoring, generate reports, and identify unused or misused skills for pruning.
التثبيت باستخدام Codex أو Claude انسخ هذا Prompt والصقه في Codex أو Claude أو مساعد آخر ليراجع صفحة Skill ويثبّتها لك.
القائمة
Track skill usage with correctness scoring, generate reports, and identify unused or misused skills for pruning.
التثبيت باستخدام Codex أو Claude انسخ هذا Prompt والصقه في Codex أو Claude أو مساعد آخر ليراجع صفحة Skill ويثبّتها لك.
استنادا إلى تصنيف SOC المهني
| name | skill-tracker |
| description | Track skill usage with correctness scoring, generate reports, and identify unused or misused skills for pruning. |
| kind | sop |
Track which skills are being used, how often, and whether they're being used correctly. Generate reports to identify:
Synced Report Location: ~/.pi/skill-tracker/REPORT.md (auto-generated)
log - Log a skill usage eventreport - Generate usage reportmark - Mark a skill usage as proper/improperstats - Quick statistics summaryreview - Review recent usages for correctnessproper, improper, or unknowntable, json, or markdownWhen to use: After any skill is triggered, log its usage.
Python CLI:
python3 skills/skill-tracker/tracker.py log --skill <name> --correctness <proper|improper|unknown> --notes "<context>" --context "<what user asked>"
Examples:
# Log proper usage
python3 skills/skill-tracker/tracker.py log --skill pdd --correctness proper --notes "Perfect fit for feature planning" --context "User wanted to design a new feature"
# Log with unknown correctness (will prompt for review later)
python3 skills/skill-tracker/tracker.py log --skill code-assist --correctness unknown --context "User asked for help with code"
# Log improper usage with explanation
python3 skills/skill-tracker/tracker.py log --skill pdd --correctness improper --notes "User just wanted a quick fix, not full design" --context "Quick bug fix"
Auto-logging: The system should automatically log when skills are triggered via /skill run or skill shortcuts.
Python CLI:
python3 skills/skill-tracker/tracker.py report [--days 30] [--format table|json|markdown]
Examples:
# Default table report
python3 skills/skill-tracker/tracker.py report
# Markdown report for sharing
python3 skills/skill-tracker/tracker.py report --format markdown
# JSON for programmatic use
python3 skills/skill-tracker/tracker.py report --format json
# Last 7 days only
python3 skills/skill-tracker/tracker.py report --days 7
Report includes:
Synced Report: To update the synced report file:
python3 skills/skill-tracker/tracker.py report --format markdown > ~/.pi/skill-tracker/REPORT.md
When to use: Retroactively mark whether a skill was used properly.
Python CLI:
python3 skills/skill-tracker/tracker.py mark --entry-id <id> --correctness <proper|improper> [--notes "<reason>"]
Example:
python3 skills/skill-tracker/tracker.py mark --entry-id 890b955f --correctness improper --notes "User seemed confused about what this skill does"
Python CLI:
python3 skills/skill-tracker/tracker.py stats [--days 30]
Shows:
Python CLI:
python3 skills/skill-tracker/tracker.py review
Interactive review of recent usages with unknown correctness. Lists entries that need to be marked as proper or improper.
~/.pi/skill-tracker/usage.jsonl (JSON Lines, append-only)~/.pi/skill-tracker/config.json~/.pi/skill-tracker/REPORT.md (regenerate with report --format markdown)Entry Fields:
id: Short UUID for the entryskill_name: Name of skill usedtimestamp: ISO8601 timestamptrigger_source: How triggered (/skill, auto, shortcut)context: Brief description of user requestcorrectness: proper, improper, or unknownnotes: Optional notes on usage qualitysession_id: Session identifier for groupingSkill | Uses | Proper | Improper | Rate
-----------------------|------|--------|----------|------
code-assist | 45 | 42 | 3 | 93%
pdd | 12 | 10 | 2 | 83%
skill-tracker | 3 | 2 | 1 | 67%
Full structured data for programmatic use.
Formatted for documentation or sharing.
Mark as PROPER when:
Mark as IMPROPER when:
Mark as UNKNOWN when:
python3 skills/skill-tracker/tracker.py log --skill pdd --correctness proper --notes "User wanted to plan a feature, PDD was perfect fit" --context "Feature design session"
python3 skills/skill-tracker/tracker.py report --days 30 --format markdown > ~/.pi/skill-tracker/REPORT.md
# First find the entry ID from review or data file
python3 skills/skill-tracker/tracker.py review
# Then mark it
python3 skills/skill-tracker/tracker.py mark --entry-id abc123 --correctness improper --notes "User just wanted a simple edit"
python3 skills/skill-tracker/tracker.py stats
cat ~/.pi/skill-tracker/REPORT.md
No data showing:
~/.pi/skill-tracker/usage.jsonl existspython3 skills/skill-tracker/tracker.py stats to verifyReport seems incomplete:
--days parameter to look further backWant to reset data:
mv ~/.pi/skill-tracker/usage.jsonl ~/.pi/skill-tracker/usage-$(date +%Y%m%d).jsonl> ~/.pi/skill-tracker/usage.jsonlPython not found:
python3 explicitly (macOS/Linux)/usr/bin/python3 skills/skill-tracker/tracker.py~/bibo/skills/skill-tracker/SKILL.md~/bibo/skills/skill-tracker/tracker.py~/.pi/skill-tracker/usage.jsonl~/.pi/skill-tracker/config.json~/.pi/skill-tracker/REPORT.mdConsolidate and clean up existing brain memory. Run this periodically (like a sleep cycle) to dedupe, decay, merge, and relocate memories to vault.
Remove old pi session files to reclaim disk space
Testing-focused coding workflow. Extends code-assist with enhanced test generation, coverage analysis, and test quality gates.
Systematic debugging workflow for diagnosing and fixing issues. Follows a structured approach to isolate problems, form hypotheses, and verify fixes.
Generate documentation from code or scratch - READMEs, API docs, changelogs, and user guides. Complements codebase-summary which analyzes existing code.
Extract durable learnings and preferences from the current conversation for memory capture. Use this after a conversation to capture what should be remembered.