docs-cleaner

📁 daymade/claude-code-skills 📅 Jan 19, 2026
60
总安装量
59
周安装量
#3650
全站排名
安装命令
npx skills add https://github.com/daymade/claude-code-skills --skill docs-cleaner

Agent 安装分布

claude-code 50
opencode 41
gemini-cli 37
codex 37
antigravity 35
github-copilot 32

Skill 文档

Documentation Cleaner

Consolidate redundant documentation while preserving 100% of valuable content.

Core Principle

Critical evaluation before deletion. Never blindly delete. Analyze each section’s unique value before proposing removal. The goal is reduction without information loss.

Workflow

Phase 1: Discovery

  1. Identify all documentation files covering the topic
  2. Count total lines across files
  3. Map content overlap between documents

Phase 2: Value Analysis

For each document, create a section-by-section analysis table:

Section Lines Value Reason
API Reference 25 Keep Unique endpoint documentation
Setup Steps 40 Condense Verbose but essential
Test Results 30 Delete One-time record, not reference

Value categories:

  • Keep: Unique, essential, frequently referenced
  • Condense: Valuable but verbose
  • Delete: Duplicate, one-time, self-evident, outdated

See references/value_analysis_template.md for detailed criteria.

Phase 3: Consolidation Plan

Propose target structure:

Before: 726 lines (3 files, high redundancy)
After:  ~100 lines (1 file + reference in CLAUDE.md)
Reduction: 86%
Value preserved: 100%

Phase 4: Execution

  1. Create consolidated document with all valuable content
  2. Delete redundant source files
  3. Update references (CLAUDE.md, README, imports)
  4. Verify no broken links

Value Preservation Checklist

Before finalizing, confirm preservation of:

  • Essential procedures (setup, configuration)
  • Key constraints and gotchas
  • Troubleshooting guides
  • Technical debt / roadmap items
  • External links and references
  • Debug tips and code snippets

Anti-Patterns

Pattern Problem Solution
Blind deletion Loses valuable information Section-by-section analysis first
Keeping everything No reduction achieved Apply value criteria strictly
Multiple sources of truth Future divergence Single authoritative location
Orphaned references Broken links Update all references after consolidation

Output Artifacts

A successful cleanup produces:

  1. Consolidated document – Single source of truth
  2. Value analysis – Section-by-section justification
  3. Before/after metrics – Lines reduced, value preserved
  4. Updated references – CLAUDE.md or README with pointer to new location