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jrc1883

pop-assessment-performance

by jrc1883

AI-powered development workflow automation for Claude Code. Modular plugin suite with 23 commands, 38 skills, and 22 specialized agents for professional software development.

2🍴 0📅 Jan 24, 2026

SKILL.md


name: pop-assessment-performance description: "Evaluates PopKit efficiency using concrete metrics for context usage, token consumption, and lazy loading validation" context: fork triggers:

  • assess performance
  • performance test
  • efficiency audit version: 1.0.0

Performance Assessment Skill

Purpose

Provides concrete, reproducible performance assessment for PopKit plugins using:

  • Measurable efficiency metrics
  • Automated context analysis
  • Token consumption estimation
  • Lazy loading validation

How to Use

Step 1: Run Automated Metrics Collection

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/

Step 2: Apply Performance Checklists

Read and apply checklists in order:

  1. checklists/context-efficiency.json - Context window usage
  2. checklists/startup-performance.json - Plugin initialization
  3. checklists/file-access-patterns.json - Read/write efficiency

Step 3: Generate Report

Combine automated metrics with checklist results for final performance report.

Standards Reference

StandardFileKey Checks
Context Efficiencystandards/context-efficiency.mdCE-001 through CE-008
Startup Performancestandards/startup-performance.mdSP-001 through SP-006
File Accessstandards/file-access.mdFA-001 through FA-008
Token Consumptionstandards/token-consumption.mdTC-001 through TC-006

Performance Targets

MetricTargetWarningCritical
Skill Prompt Size<2000 tokens2000-4000>4000
Agent Prompt Size<5000 tokens5000-8000>8000
Tier-1 Agent Count<=1516-20>20
File Reads/Operation<55-10>10
Startup Files<1010-20>20

Output

Returns JSON with:

  • efficiency_score: 0-100 (higher = better)
  • metrics: Collected performance measurements
  • bottlenecks: Identified performance issues
  • optimizations: Recommended improvements

Score

Total Score

75/100

Based on repository quality metrics

SKILL.md

SKILL.mdファイルが含まれている

+20
LICENSE

ライセンスが設定されている

+10
説明文

100文字以上の説明がある

+10
人気

GitHub Stars 100以上

0/15
最近の活動

1ヶ月以内に更新

+10
フォーク

10回以上フォークされている

0/5
Issue管理

オープンIssueが50未満

+5
言語

プログラミング言語が設定されている

+5
タグ

1つ以上のタグが設定されている

+5

Reviews

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