repomix

Guide for using Repomix - a powerful tool that packs entire repositories into single, AI-friendly files. Use when packaging codebases for AI analysis, generating context for LLMs, creating codebase snapshots, analyzing third-party libraries, or preparing repositories for security audits.

Quality

77%

Does it follow best practices?

Impact

Pending

No eval scenarios have been run

Securityby

Advisory

Suggest reviewing before use

Optimize this skill with Tessl

npx tessl skill review --optimize ./claude/skills/repomix/SKILL.md

Quality

Discovery

89%

Based on the skill's description, can an agent find and select it at the right time? Clear, specific descriptions lead to better discovery.

This is a well-crafted description with excellent completeness and trigger term coverage. The explicit 'Use when' clause with multiple scenarios makes it highly actionable for skill selection. The main weakness is that the 'what' portion could be more specific about concrete capabilities beyond the high-level 'packs repositories' action.

Suggestions

Add 2-3 more specific actions like 'configure ignore patterns', 'select output formats', or 'filter by file type' to improve specificity

Dimension	Reasoning	Score
Specificity	Names the domain (Repomix tool) and describes the general action ('packs entire repositories into single, AI-friendly files'), but lacks multiple specific concrete actions like configuration options, output formats, or filtering capabilities.	2 / 3
Completeness	Clearly answers both what ('packs entire repositories into single, AI-friendly files') and when with explicit 'Use when' clause listing five specific trigger scenarios.	3 / 3
Trigger Term Quality	Includes strong natural keywords users would say: 'packaging codebases', 'AI analysis', 'context for LLMs', 'codebase snapshots', 'third-party libraries', 'security audits', 'repositories'. Good coverage of variations.	3 / 3
Distinctiveness Conflict Risk	Very distinct niche - specifically about Repomix tool for repository packaging. The combination of 'Repomix', 'AI-friendly files', and 'packaging codebases' creates clear, unique triggers unlikely to conflict with other skills.	3 / 3
	Total	11 / 12 Passed

Implementation

64%

Reviews the quality of instructions and guidance provided to agents. Good implementation is clear, handles edge cases, and produces reliable results.

This is a comprehensive and highly actionable skill with excellent executable examples and command-line documentation. However, it suffers from verbosity (explaining concepts Claude knows, redundant use-case lists) and could benefit from better progressive disclosure by splitting into multiple files. The workflow section lacks explicit validation steps and error recovery patterns.

Suggestions

Remove the 'When to Use This Skill' section entirely - this duplicates the YAML description and explains obvious use cases

Add explicit validation commands to the Implementation Workflow (e.g., 'Verify output exists: ls -la repomix-output.xml', 'Check token count is under limit')

Split into multiple files: keep quick-start and common patterns in SKILL.md, move configuration details to CONFIG.md, troubleshooting to TROUBLESHOOTING.md

Remove explanatory text like 'Perfect for when you need to feed codebases to Large Language Models' - Claude knows what LLMs are

Dimension	Reasoning	Score
Conciseness	The skill contains some unnecessary explanations (e.g., 'Perfect for when you need to feed codebases to Large Language Models' and the 'When to Use This Skill' section largely duplicates the description). The content is comprehensive but could be tightened significantly - Claude doesn't need explanations of what LLMs are or extensive use case lists.	2 / 3
Actionability	Excellent executable examples throughout - all commands are copy-paste ready with real flags and options. The configuration file example is complete JSON, and the common patterns section provides immediately usable command combinations for specific scenarios.	3 / 3
Workflow Clarity	The 'Implementation Workflow' section provides a clear 5-step sequence, but lacks explicit validation checkpoints. For example, step 4 'Validate Output' says 'Review generated file' but doesn't specify how to verify success or what to do if validation fails. No feedback loops for error recovery.	2 / 3
Progressive Disclosure	Content is well-organized with clear section headers, but it's a monolithic document (~400 lines) that could benefit from splitting advanced topics (configuration, troubleshooting, use cases) into separate files. The 'Additional Resources' section at the end provides external links but no internal file references for progressive learning.	2 / 3
	Total	9 / 12 Passed

Validation

100%

Warnings & errors only

Checks the skill against the spec for correct structure and formatting. All validation checks must pass before discovery and implementation can be scored.

Validation — 11 / 11 Passed

Validation for skill structure

No warnings or errors.

Repository: einverne/dotfiles
Commit: b1b2fe0

Reviewed: 27 days ago

Table of Contents

Discovery Implementation Validation

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