Agent skill
skill-analytics
Track skill usage patterns, most-used skills, token savings, and skill health metrics.
Install this agent skill to your Project
npx add-skill https://github.com/majiayu000/claude-skill-registry/tree/main/skills/other/skill-analytics
Metadata
Additional technical details for this skill
- oneshot
-
{ "emoji": "\ud83d\udcca", "requires": { "bins": [] } }
SKILL.md
/skill-analytics - Track Usage Patterns
Know what works. Track which skills you use most, token savings, and skill health.
When To Use
User says:
/skill-analyticsor/analytics- "show skill stats"
- "most used skills"
- "skill usage report"
- "token savings"
- "unused skills"
How It Works
Track usage in beads:
- Log each skill invocation to
.beads/skill_usage.json - Track metadata: skill name, timestamp, session, project
- Analyze patterns across sessions
- Report insights
Commands
# Show top skills
bd analytics --top-skills
# Show unused skills
bd analytics --unused
# Show token savings
bd analytics --tokens
# Full analytics report
bd analytics --report
# Skill health score
bd analytics --health
Usage Tracking Format
{
"skill_usage": [
{
"skill": "front-door",
"invoked_at": "2025-01-31T10:30:00Z",
"session": "afd19be4",
"project": "oneshot",
"trigger": "build me",
"success": true
}
],
"token_savings": {
"freesearch": 45000,
"dispatch": 12000,
"total": 57000
}
}
Report Formats
Top Skills
$ bd analytics --top-skills
📊 Most Used Skills (Last 30 Days)
1. front-door 45 uses (40%) ████████████████████
2. beads 28 uses (25%) ████████████
3. debugger 15 uses (13%) ██████
4. implement-plan 12 uses (11%) █████
5. freesearch 8 uses (7%) ███
Total invocations: 108
Avg per session: 12.3
Unused Skills
$ bd analytics --unused
📋 Unused Skills (Last 30 Days)
High Priority (Core):
- create-plan (Core skill, never used)
- resume-handoff (Context skill, never used)
Medium Priority (Advanced):
- ci-cd-setup (Last used: 90 days ago)
- oci-resources (Last used: 60 days ago)
Low Priority (Specialized):
- the-audit (Specialized, rarely expected)
- visual-iteration (UI-specific, rarely expected)
Recommendation: Consider removing or aliasing unused Core skills
Token Savings
$ bd analytics --tokens
💰 Token Savings (Last 30 Days)
Source | Tokens Saved | % of Total
----------------|--------------|-----------
/freesearch | 45,000 | 79%
/dispatch | 12,000 | 21%
----------------|--------------|-----------
Total Saved | 57,000 |
Equivalent to: ~114 standard Claude messages (500 tokens each)
Cost avoided: ~$1.14 (at $0.02/1k tokens)
Skill Health
$ bd analytics --health
🏥 ONE_SHOT Skill Health: 87/100
Test Coverage: 78% (25/32 tested) [████████████░░] 26 pts
Syntax Valid: 100% (43/43 valid) [██████████████] 30 pts
Tools Available: 95% (41/43 ok) [██████████████░] 25 pts
Recent Updates: 60% (26/43 <30d) [██████████░░░░░] 6 pts
Action Items:
- Add tests for: git-workflow, secrets-sync
- Check tools for: oci-resources, api-designer
- Update docs for: hooks-manager (last updated 90d ago)
Integration with Session Tracking
Auto-Log Skill Usage
When a skill is invoked:
# In skill implementation, after loading:
import json
from datetime import datetime, timezone
usage = {
"skill": "skill-name",
"invoked_at": datetime.now(timezone.utc).isoformat(),
"session": os.getenv("CLAUDE_SESSION_ID", "unknown"),
"project": os.path.basename(os.getcwd()),
"success": True
}
# Append to usage log
usage_file = ".beads/skill_usage.json"
with open(usage_file, "a") as f:
f.write(json.dumps(usage) + "\n")
Token Savings Tracking
# For freesearch skill:
tokens_saved_before = 0 # Would have used WebSearch
tokens_saved_after = 500 # Used Exa API instead
# Log savings
savings = {
"source": "freesearch",
"tokens_saved": 500,
"date": datetime.now(timezone.utc).isoformat()
}
Analytics Queries
Skills by Category
$ bd analytics --by-category
Category | Skills | Uses (30d) | Avg Use
---------------|--------|------------|----------
Core | 5 | 72 | 14.4
Research | 4 | 18 | 4.5
Development | 7 | 10 | 1.4
Operations | 6 | 5 | 0.8
Skill Correlations
$ bd analytics --correlations
🔗 Skill Usage Patterns
front-door → create-plan (85% of front-door uses)
create-plan → implement-plan (92% of plans)
debugger → test-runner (67% after debugging)
beads → resume-handoff (45% of sessions)
Insights:
- Consider auto-chaining: front-door → create-plan
- Add test-runner suggestion after debugger
Project-Specific Usage
$ bd analytics --by-project
Project | Sessions | Top Skills
---------------|----------|----------------------------
oneshot | 45 | beads, front-door, freesearch
homelab | 12 | docker-composer, secrets-sync
client-xyz | 8 | push-to-cloud, observability
Quick Win from Research
Competitor Analysis: No existing skill system has built-in analytics Opportunity: Be the first to track skill usage and insights Value: Data-driven decisions about which skills to improve/remove
Implementation Notes
Storage: .beads/skill_usage.json (git-ignored, aggregated for reports)
Privacy: Local-only, no telemetry sent externally
Performance: Append-only writes, minimal overhead
Anti-Patterns
- Obsessive micro-tracking (log at session level, not per API call)
- Tracking private data (only skill names and timestamps)
- Comparing across users (analytics is personal, not social)
- Over-optimizing for usage (some skills are rarely needed but critical)
Keywords
analytics, stats, usage, metrics, most used, unused skills, token savings, skill health
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