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critical-skillgovern

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🔍 Critical SkillGovern — 批判式技能治理框架。跨平台(Hermes/Claude Code/Codex)技能质量审查方法论,已在 120+ 技能实战验证

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READMESource: master@c516237e

🔍 Critical SkillGovern

A cross-platform skill quality governance framework — battle-tested on 128 skills across 40 categories.

License: MIT Platforms

中文版


The Problem

The more skills you have, the harder it is for an LLM agent to pick the right one. This isn't a model limitation — it's a routing problem. Skill descriptions lack the signal LLMs need for accurate selection.

Skill Count Routing Issues Impact
1-10 Nearly none Easy to distinguish
10-50 Occasional misfires Descriptions too vague
50-100 Frequent misfires Need structured routing
100+ Unreliable system Must govern

Critical SkillGovern gives you a battle-tested workflow to keep your skill library accurate at any scale.


Why You Should Care

The third-party skill packs you downloaded — Superpowers workflow pack, Baoyu creative pack, Matt Pocock TypeScript pack, design skill packs — likely have routing issues:

Source Routing Health Typical Problem
Built-in (official) 100% ✅ —
Superpowers pack Excellent ✅ Best among community packs
Baoyu pack ⚠️ ~60% Weak negative samples, single-layer tags
Design pack (16 skills) ⚠️ ~19% 13/16 had weak negative samples
Matt Pocock pack ⚠️ ~70% Weak negative sample

📖 Full case study → examples/third-party-packs.md

Before governance:

【不适用场景】不需要生成创意内容/可视化时    ← Too vague, no alternative

After governance:

【不适用场景】For simple charts/diagrams → use excalidraw;
For AI art rather than structured infographics → use image generation
            ← Points to specific alternatives

The difference: before, the model guesses wrong ~30% of the time. After, misfires drop to ~5%.


Core Pipeline

Routing Diagnosis → Critical Questioning → User Approval → Execution → Verification → Final Report
Phase What It Does Output
1️⃣ Routing Diagnosis Scan skill descriptions for template residuals, English-only triggers, weak negative samples Issue list
2️⃣ Critical Questioning 5W1H questioning + reverse thinking + assumption mining Deep analysis
3️⃣ User Approval Severity-based triage, user decides what to fix Approved fix list
4️⃣ Execution Modify routing only (never touch functionality) Patched files
5️⃣ Verification Re-run diagnosis to confirm fixes Verification report
6️⃣ Final Report Document results Complete audit report

Supported Platforms

Platform Skill Format Adapter
🏛️ Hermes Agent SKILL.md (YAML frontmatter + Markdown) adapters/hermes.md
🔌 DeepSeek Harness DSH tool plugin (defineTool) dsh-plugin/
🤖 Codex CLI Prompt templates / Shell wrappers adapters/codex.md

Quick Start

# 1. Review all your skills
python scripts/batch-review.py --path ~/.hermes/skills --format hermes

# 2. Review a specific category (e.g., third-party packs)
python scripts/batch-review.py --path ~/.hermes/skills/creative --format hermes

# 3. Export CSV report
python scripts/batch-review.py --path ~/.hermes/skills --format hermes --csv report.csv

What to Fix (Priority Order)

Severity Issue How to Fix
🔴 Critical Template residuals (.join, kw[:) Remove Python literals from descriptions
🔴 Critical English-only triggers Translate to Chinese (or user's locale)
🟡 Suggested Weak negative samples Point to specific alternative skills
🟢 Optional Single-layer tags Add subcategory tags
🟢 Optional Missing related_skills Link cross-category skills

Project Structure

critical-skillgovern/
├── README.md                         # English (this file)
├── README.zh-CN.md                   # 中文版
├── LICENSE                           # MIT
├── docs/
│   ├── methodology.md                # Core methodology (6-stage pipeline)
│   ├── routing-optimization.md       # Routing optimization guide
│   └── prompts/
│       └── classify-skills-v2.txt    # Skill classification prompt v2.1
├── adapters/
│   ├── hermes.md                     # Hermes Agent guide
│   └── codex.md                      # Codex CLI guide
├── dsh-plugin/                       # DeepSeek Harness plugin
│   ├── package.json                  # DSH bundle manifest
│   ├── cordis.patch.yml              # Cordis configuration
│   └── index.js                      # Plugin entry (3 tools)
├── templates/
│   ├── diagnostic-card.md            # Diagnostic card template
│   └── skill-audit-report.md         # Audit report template
├── scripts/
│   ├── batch-review.py               # Batch review script
│   └── validate-routing.py           # Routing validation script
├── examples/
│   ├── before-after.md               # Before/after optimization examples
│   ├── full-audit-example.md         # Full 128-skill audit walkthrough
│   └── third-party-packs.md          # Third-party pack case study
└── CONTRIBUTING.md                   # Contribution guide

Real-World Impact

Tested on a 128-skill, 40-category Hermes Agent library with Superpowers, Baoyu, and 16 design skill packs:

Metric Before After
Routing coverage 23/128 (18%) 128/128 (100%)
Template residuals 14 skills 0
English-only triggers 97 skills 0
Weak negative samples 54 skills All fixed
Third-party pack misfire rate ~30% ~5%

Why Critical SkillGovern?

Feature Critical SkillGovern Traditional Approaches
Cross-platform Hermes / Codex / DeepSeek Harness Single platform only
Critical thinking Reverse thinking + assumption mining Forward checks only
Third-party pack support Dedicated case studies + batch scripts No third-party coverage
Battle-tested 128 real skills with real data Theoretical design
User-controlled Severity-based triage + selective fix Fully automated, no oversight
Verification step Full re-check after fixes No verification

DeepSeek Harness Plugin

Install the DSH plugin to get 3 skill governance tools directly in your agent:

# From GitHub
dsh plugin --profile web add github:Xiaopeng212321414321413231/critical-skillgovern#path:dsh-plugin

# Or from local clone
dsh plugin --profile web add ./dsh-plugin
Tool Description
skill-diagnose Diagnose a single skill file for routing health issues
skill-audit Batch audit all skills in a directory
skill-classify Classify skills into structured categories (7 major, 19 sub)

Listed on DSH 1024Store.


Contributing

PRs and issues welcome! See CONTRIBUTING.md.

License

MIT — free to use, modify, and distribute.

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