Evaluates PopKit efficiency using concrete metrics for context usage, token consumption, and lazy loading validation
Inherits all available tools
Additional assets for this skill
This skill inherits all available tools. When active, it can use any tool Claude has access to.
checklists/context-efficiency.jsonchecklists/file-access-patterns.jsonchecklists/startup-performance.jsonscripts/analyze_loading.pyscripts/calculate_efficiency.pyscripts/measure_context.pystandards/context-efficiency.mdstandards/file-access.mdstandards/startup-performance.mdstandards/token-consumption.mdname: pop-assessment-performance description: "Evaluates PopKit efficiency using concrete metrics for context usage, token consumption, and lazy loading validation" triggers:
Provides concrete, reproducible performance assessment for PopKit plugins using:
python skills/pop-assessment-performance/scripts/measure_context.py packages/plugin/
python skills/pop-assessment-performance/scripts/analyze_loading.py packages/plugin/
python skills/pop-assessment-performance/scripts/calculate_efficiency.py packages/plugin/
Read and apply checklists in order:
checklists/context-efficiency.json - Context window usagechecklists/startup-performance.json - Plugin initializationchecklists/file-access-patterns.json - Read/write efficiencyCombine automated metrics with checklist results for final performance report.
| Standard | File | Key Checks |
|---|---|---|
| Context Efficiency | standards/context-efficiency.md | CE-001 through CE-008 |
| Startup Performance | standards/startup-performance.md | SP-001 through SP-006 |
| File Access | standards/file-access.md | FA-001 through FA-008 |
| Token Consumption | standards/token-consumption.md | TC-001 through TC-006 |
| Metric | Target | Warning | Critical |
|---|---|---|---|
| Skill Prompt Size | <2000 tokens | 2000-4000 | >4000 |
| Agent Prompt Size | <5000 tokens | 5000-8000 | >8000 |
| Tier-1 Agent Count | <=15 | 16-20 | >20 |
| File Reads/Operation | <5 | 5-10 | >10 |
| Startup Files | <10 | 10-20 | >20 |
Returns JSON with:
efficiency_score: 0-100 (higher = better)metrics: Collected performance measurementsbottlenecks: Identified performance issuesoptimizations: Recommended improvements