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ClaudeSkillz

ClaudeSkillz: For when you need skills, but lazier

15estrelas
Atualizado há 11 meses

Ver no GitHub ↗ Licença: MIT

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/plugin marketplace add jackspace/ClaudeSkillz

O comando exato pode variar conforme o repositório. Confira o README no GitHub.

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Cole no README do seu repo

Mostra que sua skill está catalogada na Skillteca, gera backlink e tráfego rastreável.

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Skills Duplicate Detector

Expert skill for identifying duplicate, similar, and overlapping Claude Code skills across your collection using intelligent comparison algorithms.

Purpose

Analyze a collection of Claude Code skills to identify duplicates, near-duplicates, and functionally similar skills. Helps maintain a clean, organized skills collection by detecting redundancy and suggesting consolidation.

When to Use

  • After bulk downloading skills from multiple sources
  • Maintaining an existing skills collection
  • Before committing new skills to a repository
  • Auditing skill collections for redundancy

Capabilities

1. Duplicate Detection Methods

Exact Name Matching

  • Identify skills with identical names
  • Detect name variations with prefixes/suffixes
  • Find skills differing only in case

Semantic Similarity

  • Analyze SKILL.md descriptions
  • Compare stated purposes and capabilities
  • Identify functional overlap
  • Calculate similarity scores

Content Analysis

  • Compare skill file structures
  • Analyze included scripts and tools
  • Check for shared dependencies
  • Detect copy/paste variations

2. Similarity Categories

Perfect Duplicates (100% match)

  • Identical names and content
  • Same functionality and purpose
  • Likely from same source

Near Duplicates (80-99% match)

  • Similar names with minor variations
  • Nearly identical functionality
  • Possible version differences

Functional Overlaps (60-79% match)

  • Different names, similar purpose
  • Overlapping capabilities
  • May serve different use cases

Related Skills (40-59% match)

  • Adjacent functionality
  • Complementary features
  • Worth noting but not duplicates

3. Analysis Outputs

Duplicate Report

# Duplicate Skills Analysis

## Perfect Duplicates (7 found)

### Group 1: Code Review
- **code-review_mrgoonie** (KEEP - most comprehensive)
  - Location: /skills/code-review_mrgoonie
  - Size: 15 KB
  - Features: Requesting, receiving, verification

- **receiving-code-review_obra** (DUPLICATE)
  - Location: /skills/receiving-code-review_obra
  - Similarity: 95%
  - Recommendation: Move to /duplicates

- **requesting-code-review_obra** (DUPLICATE)
  - Location: /skills/requesting-code-review_obra
  - Similarity: 92%
  - Recommendation: Move to /duplicates

**Reason**: All three provide code review functionality. mrgoonie version combines both requesting and receiving in one comprehensive skill.

Usage Instructions

Basic Duplicate Detection

Use the skills-duplicate-detector skill to analyze /skills directory and identify all duplicates.

Detailed Analysis

Use the skills-duplicate-detector skill to:
1. Scan all skills in /skills directory
2. Identify duplicates with 70%+ similarity
3. Generate a detailed report with recommendations
4. Create a DUPLICATES_LOG.md file

Pre-commit Check

Before committing new skills, use skills-duplicate-detector to check if they already exist in the collection.

Detection Algorithm

Phase 1: Name Analysis

# Normalize skill names
def normalize_name(skill_name):
    # Remove source suffixes (_obra, _mrgoonie, etc.)
    # Convert to lowercase
    # Remove special characters
    # Standardize spacing
    return normalized_name

# Find exact and near matches
for skill1, skill2 in pairs:
    name_similarity = levenshtein_distance(
        normalize_name(skill1),
        normalize_name(skill2)
    )

Phase 2: Content Analysis

# Compare SKILL.md descriptions
def compare_descriptions(skill1, skill2):
    # Extract purpose statements
    # Tokenize and compare keywords
    # Calculate semantic similarity
    # Weight by capability overlap
    return similarity_score

Phase 3: Structural Analysis

# Compare file structures
def compare_structure(skill1, skill2):
    # List files and directories
    # Compare organization
    # Check for shared patterns
    # Identify clones vs. variations
    return structure_score

Comparison Heuristics

Name-Based Detection

  • Exact match: Same name after normalization → 100%
  • Prefix/suffix variation: skill vs skill_source → 95%
  • Hyphen/underscore: code-review vs code_review → 90%
  • Abbreviations: db-helper vs database-helper → 80%

Purpose-Based Detection

  • Identical purpose: Same goals stated → 95%
  • Overlapping functionality: 80%+ feature overlap → 85%
  • Complementary: Different aspects of same domain → 60%
  • Related: Adjacent problem spaces → 40%

Quality Assessment

When duplicates are found, recommend keeping the version with:

  1. ✅ Most comprehensive documentation
  2. ✅ Largest feature set
  3. ✅ Most recent updates
  4. ✅ Better code quality
  5. ✅ More complete examples

Output Formats

Console Report

Duplicate Detection Results
===========================

Total skills scanned: 161
Unique skills: 154
Duplicates found: 7
Similarity threshold: 70%

Perfect Duplicates (3 groups):
  - Code review skills (3 items)
  - Debugging skills (2 items)
  - Skill creation tools (3 items)

Near Duplicates (2 groups):
  - Brainstorming skills (2 items)
  - Document skills (2 items)

Recommendations:
  - Move 7 skills to /duplicates
  - Keep 154 unique skills in /skills
  - Estimated disk space saved: 2.3 MB

Markdown Report (DUPLICATES_LOG.md)

  • Detailed analysis of each duplicate group
  • Side-by-side comparison tables
  • Recommendations with reasoning
  • Links to source repositories

JSON Export

{
  "analysis_date": "2025-11-07",
  "total_skills": 161,
  "unique_skills": 154,
  "duplicates": [
    {
      "group_id": 1,
      "group_name": "code-review",
      "members": [
        {
          "path": "/skills/code-review_mrgoonie",
          "keep": true,
          "reason": "Most comprehensive"
        },
        {
          "path": "/skills/receiving-code-review_obra",
          "keep": false,
          "similarity": 0.95
        }
      ]
    }
  ]
}

Configuration Options

Similarity Thresholds

thresholds:
  perfect_duplicate: 0.95      # 95%+ similarity
  near_duplicate: 0.80         # 80-94% similarity
  functional_overlap: 0.60     # 60-79% similarity
  related: 0.40                # 40-59% similarity
  report_minimum: 0.60         # Only report 60%+ matches

Comparison Weights

weights:
  name_similarity: 0.30        # 30% weight on name matching
  purpose_similarity: 0.40     # 40% weight on purpose/description
  structure_similarity: 0.20   # 20% weight on file structure
  feature_overlap: 0.10        # 10% weight on feature comparison

Output Options

output:
  console_report: true
  markdown_report: true
  json_export: false
  auto_move_duplicates: false  # Require confirmation
  create_backups: true         # Before moving files

Detection Patterns

Common Duplicate Patterns

  1. Source-Suffixed Variants

`` skill-name_obra skill-name_mrgoonie skill-name_diet103 ``

  1. Naming Convention Differences

`` code-review code_review codeReview ``

  1. Scope Variations

`` document-skills (broad) scientific-document-skills (specialized) pdf-document-skills (narrow) ``

  1. Feature Splits

`` code-review (combined) requesting-code-review (split) receiving-code-review (split) ``

Special Cases

Not Duplicates

  • Specialized vs. General: Scientific brainstorming vs. general brainstorming
  • Different Frameworks: React testing vs. Vue testing
  • Language-Specific: Python debugging vs. JavaScript debugging
  • Platform-Specific: AWS deployment vs. GCP deployment

Borderline Cases

  • Related Workflows: Git branching vs. Git worktrees
  • Tool Variations: Docker basics vs. Docker Compose
  • Complementary: API client vs. API server

Integration with Other Skills

Works Well With

  • bulk-github-skills-downloader: De
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