Consolidates redundant documentation while preserving all valuable content. This skill should be used when users want to clean up documentation bloat, merge redundant docs, reduce documentation sprawl, or consolidate multiple files covering the same topic. Triggers include "clean up docs", "consolidate documentation", "too many doc files", "merge these docs", or when documentation exceeds 500 lines across multiple files covering similar topics.
Installation
Details
Usage
After installing, this skill will be available to your AI coding assistant.
Verify installation:
skills listSkill Instructions
name: docs-cleaner description: Consolidates redundant documentation while preserving all valuable content. This skill should be used when users want to clean up documentation bloat, merge redundant docs, reduce documentation sprawl, or consolidate multiple files covering the same topic. Triggers include "clean up docs", "consolidate documentation", "too many doc files", "merge these docs", or when documentation exceeds 500 lines across multiple files covering similar topics.
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
- Identify all documentation files covering the topic
- Count total lines across files
- 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- Delete: Duplicate, one-time, self-evident, outdated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
- Create consolidated document with all valuable content
- Delete redundant source files
- Update references (CLAUDE.md, README, imports)
- 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:
- Consolidated document - Single source of truth
- Value analysis - Section-by-section justification
- Before/after metrics - Lines reduced, value preserved
- Updated references - CLAUDE.md or README with pointer to new location
More by daymade
View allConverts documents to markdown (PDFs, Word docs, PowerPoint, Confluence exports) with Windows/WSL path handling. Activates when converting .doc/.docx/PDF/PPTX files to markdown, processing Confluence exports, handling Windows/WSL path conversions, extracting images from PDFs, or working with markitdown utility.
Configures and runs LLM evaluation using Promptfoo framework. Use when setting up prompt testing, creating evaluation configs (promptfooconfig.yaml), writing Python custom assertions, implementing llm-rubric for LLM-as-judge, or managing few-shot examples in prompts. Triggers on keywords like "promptfoo", "eval", "LLM evaluation", "prompt testing", or "model comparison".
This skill should be used when users want to create animated CLI demos, terminal recordings, or command-line demonstration GIFs. It supports both manual tape file creation and automated demo generation from command descriptions. Use when users mention creating demos, recording terminal sessions, or generating animated GIFs of CLI workflows.
Provides comprehensive GitHub operations using gh CLI and GitHub API. Activates when working with pull requests, issues, repositories, workflows, or GitHub API operations including creating/viewing/merging PRs, managing issues, querying API endpoints, and handling GitHub workflows in enterprise or public GitHub environments.