skill-evaluator

A guide for assessing Claude Code skills against criteria such as size, structure, examples, scope, and prompt quality.

In plain words
What is it for?
Use it to find a skill, inspect its SKILL.md file, detect weaknesses, and produce an evaluation report.
Why use it?
It turns a broad skill review into a repeatable checklist with specific improvement suggestions.

Skill for Claude CodeCodex

Install

Getting it into your agent

One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.

agentmods
npx agentmods add skills/lhohan/claude-code-plugins/skill-evaluator
Any agent
npx skills add lhohan/claude-code-plugins --skill skill-evaluator
Clone the repo
git clone --depth 1 https://github.com/lhohan/claude-code-plugins

Made for: Claude Code, Codex.

Per session 30 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 1,785 The whole file, excluding the scripts and references it only reads on demand.
Security scan B 1 finding. Scan, not verified.
Origin original No closer match found in the catalogue.
Token cost

What it costs to keep this loaded

Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.

ModelPer sessionOnce invoked
Fable 5 $0.00030 $0.01785
Opus 5 $0.00015 $0.00892
Sonnet 5 $0.00006 $0.00357
Haiku 4.5 $0.00003 $0.00178

Measured yesterday against content hash ac72535225f8, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade B, and why

skill-evaluator scanned grade B with 1 finding against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured yesterday.

A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.

Enumerates other installed skillsmediumAgent snooping

Other skills' SKILL.md files reveal prompts, capabilities and secrets that should be invisible to peers.

Identify the skill passed in the directory passed to you or find all in the user's `~/.claude/skills/` directory. For each directory (excluding hidden files), verify it contains a `SKILL.md` file.
skill-evaluator/skills/skill-evaluator/SKILL.md · 219 lines

How it starts

The opening of the file, as written. The whole thing — 219 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Claude Code Skill Evaluator

Systematically evaluate Claude Code skills for quality, compliance with best practices, and optimization opportunities. Provides detailed assessment with actionable suggestions for improvement.

Table of Contents

Instructions

1. Find Skill

Identify the skill passed in the directory passed to you or find all in the user's ~/.claude/skills/ directory. For each directory (excluding hidden files), verify it contains a SKILL.md file.

Present the user with:

  • List of available skills
  • Ask which skill to evaluate (or accept skill name as input)

2. Read the Skill File

Once a skill is selected, read its SKILL.md file and extract:

  • Frontmatter metadata (name, description)
  • Total line count
  • Word count
  • Character count
  • Structure and sections

3. Analyze Against Best Practices

Evaluate the skill across 8 dimensions:

Dimension 1: Size & Length

Guidelines:

  • Body: Under 500 lines (hard maximum)
  • Name: Maximum 64 characters
  • Description: Maximum 1024 characters (200 char summary preferred)
  • Table of Contents: Include if over 100 lines

Read the full file on GitHub · 219 lines

Changes

What this file has done since we first saw it

Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.

  1. yesterday First seen · 219 lines · 30 tokens per session scan B ac72535225f8

Subscribe to this mod's changes

skill-evaluator is a skill published in the GitHub repository lhohan/claude-code-plugins (2 stars, last pushed 9mo ago), licensed MIT. It adds 30 tokens to every session and 1,785 once invoked, about $0.0002 per session on Opus 5. A static security scan graded it B with 1 finding (enumerates other installed skills). No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-31.

Related

Other skills, from other repositories

systematic-debugging

Use when encountering any bug, test failure, or unexpected behavior, before proposing fixes.

obra/superpowers · 21 tokens

next-cache-components-adoption

Turn on Cache Components in a Next.js app and resolve the blocking routes it surfaces. Use when the user wants to enable, adopt, or migrate to Cache Components, flip the cacheComponents flag, work through a flood of blocking-prerender / instant validation errors, run the cache-components-instant-false codemod, or…

vercel/next.js · 95 tokens

babysit-pr

Babysit a GitHub pull request after creation by continuously polling review comments, CI checks/workflow runs, and mergeability state until the PR is merged/closed or user help is required. Diagnose failures, retry likely flaky failures up to 3 times, auto-fix/push branch-related issues when appropriate, and keep…

openai/codex · 114 tokens

imagegen

Generate or edit raster images when the task benefits from AI-created bitmap visuals such as photos, illustrations, textures, sprites, mockups, or transparent-background cutouts. Use when Codex should create a brand-new image, transform an existing image, or derive visual variants from references, and the output…

openai/codex · 113 tokens

cpu-profile-analysis

Analyze V8/Chrome CPU profiles (.cpuprofile) and DevTools trace files (Trace-.json). Use when: profiling performance, investigating slow functions, comparing code paths, finding bottlenecks, analyzing timeToRequest, understanding call trees from sampling profiler data, analyzing layout/paint/rendering, investigating…

microsoft/vscode · 71 tokens

next-cache-components-optimizer

Drive a Next.js route to instant navigation by setting up an agentic loop, under Cache Components / PPR, on initial load (hard navigation) and client-side navigation (soft navigation). Encode the goal as a failing @next/playwright instant() e2e and work it to green, one verified route at a time; the shipped test then…

vercel/next.js · 170 tokens