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Evaluates agent skills against Anthropic's best practices. An agent skill from gotalab/skillport.
Install Skill Evaluator
$ npx skills add gotalab/skillport --skill skill-evaluator -a claude-codeProject install by default; add -g for ~/.claude/skills/.
$ gh skill install gotalab/skillport skill-evaluator --agent claude-codeProject scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).
$ git clone --depth 1 https://github.com/gotalab/skillport.git skills-src && mkdir -p .claude/skills && cp -r skills-src/.skills/experimental/skill-evaluator .claude/skills/skill-evaluator && rm -rf skills-srcUse ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.
Claude Code skills documentation · loads skills from .claude/skills/
Install the "skill-evaluator" agent skill from https://github.com/gotalab/skillport/tree/main/.skills/experimental/skill-evaluator into .claude/skills/skill-evaluator/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "skill-evaluator", then confirm the skill loads.Claude Code copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$skill-installer install https://github.com/gotalab/skillport/tree/main/.skills/experimental/skill-evaluatorType this inside Codex. $skill-installer <name> installs a curated skill from openai/skills. The installer writes to $CODEX_HOME/skills (default ~/.codex/skills). Restart Codex if the skill does not show up.
$ npx skills add gotalab/skillport --skill skill-evaluator -a codexProject install goes to .agents/skills/; add -g for ~/.codex/skills/.
$ gh skill install gotalab/skillport skill-evaluator --agent codexProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/gotalab/skillport.git skills-src && mkdir -p .agents/skills && cp -r skills-src/.skills/experimental/skill-evaluator .agents/skills/skill-evaluator && rm -rf skills-srcUse ~/.agents/skills/ instead of .agents/skills for a personal install.
Codex skills documentation · loads skills from .agents/skills/
Install the "skill-evaluator" agent skill from https://github.com/gotalab/skillport/tree/main/.skills/experimental/skill-evaluator into .agents/skills/skill-evaluator/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "skill-evaluator", then confirm the skill loads.Codex copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ npx skills add gotalab/skillport --skill skill-evaluator -a cursorProject install goes to .agents/skills/; add -g for ~/.cursor/skills/.
$ gh skill install gotalab/skillport skill-evaluator --agent cursorProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/gotalab/skillport.git skills-src && mkdir -p .cursor/skills && cp -r skills-src/.skills/experimental/skill-evaluator .cursor/skills/skill-evaluator && rm -rf skills-srcUse ~/.cursor/skills/ instead of .cursor/skills for a personal install.
Cursor skills documentation · loads skills from .cursor/skills/, .agents/skills/, .claude/skills/, .codex/skills/
Install the "skill-evaluator" agent skill from https://github.com/gotalab/skillport/tree/main/.skills/experimental/skill-evaluator into .cursor/skills/skill-evaluator/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "skill-evaluator", then confirm the skill loads.Cursor copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ gemini skills install https://github.com/gotalab/skillport.git --path .skills/experimental/skill-evaluator--scope user (default) or --scope workspace; --path is the subfolder of the repo that holds the skill; --consent skips the security confirmation prompt.
$ npx skills add gotalab/skillport --skill skill-evaluator -a gemini-cliProject install goes to .agents/skills/; add -g for ~/.gemini/skills/.
$ gh skill install gotalab/skillport skill-evaluator --agent gemini-cliProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/gotalab/skillport.git skills-src && mkdir -p .gemini/skills && cp -r skills-src/.skills/experimental/skill-evaluator .gemini/skills/skill-evaluator && rm -rf skills-srcUse ~/.gemini/skills/ instead of .gemini/skills for a personal install, then run /skills reload.
Gemini CLI skills documentation · loads skills from .gemini/skills/, .agents/skills/
Install the "skill-evaluator" agent skill from https://github.com/gotalab/skillport/tree/main/.skills/experimental/skill-evaluator into .gemini/skills/skill-evaluator/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "skill-evaluator", then confirm the skill loads.Gemini CLI copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ gh skill install gotalab/skillport skill-evaluatorInstalls for Copilot at project scope by default; add --scope user for a personal install. Preview a skill first with gh skill preview. Needs GitHub CLI 2.90.0 or later (public preview).
$ npx skills add gotalab/skillport --skill skill-evaluator -a github-copilotProject install goes to .agents/skills/; add -g for ~/.copilot/skills/.
$ git clone --depth 1 https://github.com/gotalab/skillport.git skills-src && mkdir -p .github/skills && cp -r skills-src/.skills/experimental/skill-evaluator .github/skills/skill-evaluator && rm -rf skills-srcUse ~/.copilot/skills/ instead of .github/skills for a personal install. Commit .github/skills so cloud agent and code review can use it.
GitHub Copilot skills documentation · loads skills from .github/skills/, .claude/skills/, .agents/skills/
Install the "skill-evaluator" agent skill from https://github.com/gotalab/skillport/tree/main/.skills/experimental/skill-evaluator into .github/skills/skill-evaluator/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "skill-evaluator", then confirm the skill loads.GitHub Copilot copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ npx skills add gotalab/skillport --skill skill-evaluator -a opencodeOpenCode documents no install command of its own. Project install goes to .agents/skills/; add -g for ~/.config/opencode/skills/.
$ gh skill install gotalab/skillport skill-evaluator --agent opencodeProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/gotalab/skillport.git skills-src && mkdir -p .opencode/skills && cp -r skills-src/.skills/experimental/skill-evaluator .opencode/skills/skill-evaluator && rm -rf skills-srcUse ~/.config/opencode/skills/ instead of .opencode/skills for a personal install.
OpenCode skills documentation · loads skills from .opencode/skills/, .claude/skills/, .agents/skills/
Install the "skill-evaluator" agent skill from https://github.com/gotalab/skillport/tree/main/.skills/experimental/skill-evaluator into .opencode/skills/skill-evaluator/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "skill-evaluator", then confirm the skill loads.OpenCode copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
Facts
- Skill name
skill-evaluator- GitHub stars
- 414
- Token cost
- ~1.6k tokens
- SKILL.md length
- 551 words
- Files
- 7 (incl. scripts, references)
- Skills in repo
- 3
- Repo updated
- First seen
- Licence
- MIT
At a glance
Evaluates agent skills against Anthropic's best practices. An agent skill from gotalab/skillport.
- Works in 3 steps: Automated Validation → Manual Evaluation → Generate Report
- Asked to review
- SKILL.md covers Quick Start, Evaluation Workflow, Score Interpretation and References, plus 1 more section
- Runs Python scripts from its folder
What it does
Skill Evaluator is an agent skill from gotalab/skillport. Evaluates agent skills against Anthropic's best practices. Use when asked to review, evaluate, assess, or audit a skill for quality. Analyzes SKILL.md structure, naming conventions, description quality, content organization, and identifies anti-patterns. Produces actionable improvement recommendations.
Its SKILL.md is about 1.6k tokens, which your agent loads only when the skill is triggered. The skill folder holds 9 other files, including scripts and reference files (for example `evaluations/README.md`, `evaluations/basic-skill-evaluation.json` and `evaluations/problematic-skill-evaluation.json`).
It sits in Agent Workflows. It works with Model Context Protocol. The repository describes itself as: Bring Agent Skills to Any AI Agent and Coding Agent — via CLI or MCP. Manage once, serve anywhere. The licence is MIT.
When your agent uses it
- Asked to review
- Audit a skill for quality
Example prompts
- “Use the skill-evaluator skill to evaluate agent skills against Anthropic's best practices. An agent skill from gotalab/skillport”
- “/skill-evaluator”
Requirements
- Python 3
Workflow steps
3 steps, taken from the step headings in SKILL.md.
What it can do on your machine
Read from SKILL.md and the folder at commit 51334ae. It shows what the files ask for, not the result of running them.
Tool permissions
Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.
From allowed-tools in the SKILL.md frontmatter.
Runs code
Ships 1 file in scripts/ (Python), which the agent can run.
From the folder's file list and the shell code blocks in SKILL.md.
Network
No URLs in SKILL.md.
From URLs in SKILL.md, links to its own repository left out.
Credentials
Names no API keys, tokens, secrets or passwords.
From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.
Context cost
Skill Evaluator loads about 1.6k tokens when it runs, and up to ~6.5k if it reads all its reference files. Until then it costs about 80 tokens; SKILL.md has 551 words of instructions outside code blocks.
Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.
Safety
Auto-check passed
The automated check found no risky patterns in SKILL.md.
Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); the scripts in this folder are not scanned.
SKILL.md
The full file from gotalab/skillport at commit 51334ae, republished under its MIT licence (© gotalab). 551 words, ~1,602 tokens.
Download SKILL.mdSave it as
.claude/skills/skill-evaluator/SKILL.md (or your agent's skills folder). This skill also uses 6 other files; get the full folder from GitHub.- name
- skill-evaluator
- description
- Evaluates agent skills against Anthropic's best practices. Use when asked to review, evaluate, assess, or audit a skill for quality. Analyzes SKILL.md structure, naming conventions, description quality, content organization, and identifies anti-patterns. Produces actionable improvement recommendations.
Skill Evaluator (WIP)
Evaluates skills against Anthropic's official best practices for agent skill authoring. Produces structured evaluation reports with scores and actionable recommendations.
Quick Start
- Read the skill's SKILL.md and understand its purpose
- Run automated validation:
scripts/validate_skill.py <skill-path> - Perform manual evaluation against criteria below
- Generate evaluation report with scores and recommendations
Evaluation Workflow
Step 1: Automated Validation
Run the validation script first:
scripts/validate_skill.py <path/to/skill>This checks:
- SKILL.md exists with valid YAML frontmatter
- Name follows conventions (lowercase, hyphens, max 64 chars)
- Description is present and under 1024 chars
- Body is under 500 lines
- File references are one-level deep
Step 2: Manual Evaluation
Evaluate each dimension and assign a score (1-5):
A. Naming (Weight: 10%)
| Score | Criteria |
|---|---|
| 5 | Gerund form (-ing), clear purpose, memorable |
| 4 | Descriptive, follows conventions |
| 3 | Acceptable but could be clearer |
| 2 | Vague or misleading |
| 1 | Violates naming rules |
Rules: Max 64 chars, lowercase + numbers + hyphens only, no reserved words (anthropic, claude), no XML tags.
Good: processing-pdfs, analyzing-spreadsheets, building-dashboards
Bad: pdf, my-skill, ClaudeHelper, anthropic-tools
B. Description (Weight: 20%)
| Score | Criteria |
|---|---|
| 5 | Clear functionality + specific activation triggers + third person |
| 4 | Good description with some triggers |
| 3 | Adequate but missing triggers or vague |
| 2 | Too brief or unclear purpose |
| 1 | Missing or unhelpful |
Must include: What the skill does AND when to use it. Good: "Extracts text from PDFs. Use when working with PDF documents for text extraction, form parsing, or content analysis." Bad: "A skill for PDFs." or "Helps with documents."
C. Content Quality (Weight: 30%)
| Score | Criteria |
|---|---|
| 5 | Concise, assumes Claude intelligence, actionable instructions |
| 4 | Generally good, minor verbosity |
| 3 | Some unnecessary explanations or redundancy |
| 2 | Overly verbose or confusing |
| 1 | Bloated, explains obvious concepts |
Ask: "Does Claude really need this explanation?" Remove anything Claude already knows.
D. Structure & Organization (Weight: 25%)
| Score | Criteria |
|---|---|
| 5 | Excellent progressive disclosure, clear navigation, optimal length |
| 4 | Good organization, appropriate file splits |
| 3 | Acceptable but could be better organized |
| 2 | Poor organization, missing references, or bloated SKILL.md |
| 1 | No structure, everything dumped in SKILL.md |
Check:
- SKILL.md under 500 lines
- References are one-level deep (no nested chains)
- Long reference files (>100 lines) have table of contents
- Uses forward slashes in all paths
Show full SKILL.md (191 more words)Show less
E. Degrees of Freedom (Weight: 10%)
| Score | Criteria |
|---|---|
| 5 | Perfect match: high freedom for flexible tasks, low for fragile operations |
| 4 | Generally appropriate freedom levels |
| 3 | Acceptable but could be better calibrated |
| 2 | Mismatched: too rigid or too loose |
| 1 | Completely wrong freedom level for the task type |
Guideline:
- High freedom (text): Multiple valid approaches, context-dependent
- Medium freedom (parameterized): Preferred pattern exists, some variation OK
- Low freedom (specific scripts): Fragile operations, exact sequence required
F. Anti-Pattern Check (Weight: 5%)
Deduct points for each anti-pattern found:
- Too many options without clear recommendation (-1)
- Time-sensitive information with date conditionals (-1)
- Inconsistent terminology (-1)
- Windows-style paths (backslashes) (-1)
- Deeply nested references (more than one level) (-2)
- Scripts that punt error handling to Claude (-1)
- Magic numbers without justification (-1)
Step 3: Generate Report
Use this template:
# Skill Evaluation Report: [skill-name]
## Summary
- **Overall Score**: X.X/5.0
- **Recommendation**: [Ready for publication / Needs minor improvements / Needs major revision]
## Dimension Scores
| Dimension | Score | Weight | Weighted |
|-----------|-------|--------|----------|
| Naming | X/5 | 10% | X.XX |
| Description | X/5 | 20% | X.XX |
| Content Quality | X/5 | 30% | X.XX |
| Structure | X/5 | 25% | X.XX |
| Degrees of Freedom | X/5 | 10% | X.XX |
| Anti-Patterns | X/5 | 5% | X.XX |
| **Total** | | 100% | **X.XX** |
## Strengths
- [List 2-3 things done well]
## Areas for Improvement
- [List specific issues with actionable fixes]
## Anti-Patterns Found
- [List any anti-patterns detected]
## Recommendations
1. [Priority 1 fix]
2. [Priority 2 fix]
3. [Priority 3 fix]
## Pre-Publication Checklist
- [ ] Description is specific with activation triggers
- [ ] SKILL.md under 500 lines
- [ ] One-level-deep file references
- [ ] Forward slashes in all paths
- [ ] No time-sensitive information
- [ ] Consistent terminology
- [ ] Concrete examples provided
- [ ] Scripts handle errors explicitly
- [ ] All configuration values justified
- [ ] Required packages listed
- [ ] Tested with Haiku, Sonnet, OpusScore Interpretation
| Score Range | Rating | Action |
|---|---|---|
| 4.5 - 5.0 | Excellent | Ready for publication |
| 4.0 - 4.4 | Good | Minor improvements recommended |
| 3.0 - 3.9 | Acceptable | Several improvements needed |
| 2.0 - 2.9 | Needs Work | Major revision required |
| 1.0 - 1.9 | Poor | Fundamental redesign needed |
References
- references/evaluation-criteria.md - Detailed evaluation criteria with examples
- references/scoring-rubric.md - Complete scoring rubric and edge cases
Examples
See evaluations/ for example evaluation scenarios.
© gotalab, MIT. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file
Files
SKILL.md and 6 other files (scripts, references) in .skills/experimental/skill-evaluator of gotalab/skillport.
- SKILL.md
- evaluations/README.md
- evaluations/basic-skill-evaluation.json
- evaluations/problematic-skill-evaluation.json
- references/evaluation-criteria.md
- references/scoring-rubric.md
- scripts/validate_skill.py
Open the folder on GitHubat commit 51334ae
Compare with similar skills
Skill Evaluator next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.
| Skill | Stars | Used in | Tokens | Auto-check | Licence | Repo updated |
|---|---|---|---|---|---|---|
| Skill Evaluator this skillgotalab/skillport | 414 | — | ~1.6k | Automated safety check: Pass | MIT | |
| AutoRAG Lite SetupMarker-Inc-Korea/AutoRAG | 5.1k | — | ~3.3k | Automated safety check: Pass | MIT | |
| Setting Up Papergraphlotchuazzz-crypto/papergraph-mcp | 285 | — | ~3.3k | Automated safety check: Pass | MIT | |
| Control Chromewxtsky/byob | 132 | — | ~1.5k | Automated safety check: Warn | MIT | |
| Tapd Iteration AnalysisTencentBlueKing/bk-bcs | 840 | — | ~1.2k | Automated safety check: Pass | Custom licence | |
| Investigate To Confluencetestdouble/han | 279 | — | ~2.3k | Automated safety check: Pass | MIT |
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Questions about Skill Evaluator
What does Skill Evaluator do?
Evaluates agent skills against Anthropic's best practices. An agent skill from gotalab/skillport. Skill Evaluator is an agent skill from gotalab/skillport. Evaluates agent skills against Anthropic's best practices.
When should I use Skill Evaluator?
Skill Evaluator fits situations like: asked to review; audit a skill for quality.
How do I install Skill Evaluator in Claude Code?
Run `npx skills add gotalab/skillport --skill skill-evaluator -a claude-code`. Or copy the skill folder (.skills/experimental/skill-evaluator in gotalab/skillport) into .claude/skills/skill-evaluator in your project. Claude Code loads it when a task matches its description.
How do I install Skill Evaluator in Codex?
Run `npx skills add gotalab/skillport --skill skill-evaluator -a codex`. Or copy the skill folder (.skills/experimental/skill-evaluator in gotalab/skillport) into .agents/skills/skill-evaluator in your project. Codex loads it when a task matches its description.
Can I use Skill Evaluator in Cursor, Gemini CLI or GitHub Copilot?
Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add gotalab/skillport --skill skill-evaluator -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/skill-evaluator, .gemini/skills/skill-evaluator, .github/skills/skill-evaluator and .opencode/skills/skill-evaluator in your project.
What does Skill Evaluator need to run?
Going by SKILL.md and its folder, Skill Evaluator needs Python for the scripts in its folder. Our summary lists: Python 3.
Does Skill Evaluator access the network?
SKILL.md contains no URLs. Any network use would come from the scripts or tools the agent runs. This is read from the text; nothing was executed.
Is Skill Evaluator safe to install?
Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. The check reads SKILL.md only: the scripts in the folder are not scanned, so read them before running anything.
What licence does Skill Evaluator use?
Skill Evaluator is published under the MIT licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.
How many tokens does Skill Evaluator use?
About 1.6k tokens (SKILL.md is roughly 6.4k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full. Its references folder adds about 4.9k tokens, read only when the agent opens those files.
What are the alternatives to Skill Evaluator?
Skills that share tags, products or a category with Skill Evaluator: AutoRAG Lite Setup (Marker-Inc-Korea/AutoRAG, 5.1k stars), Setting Up Papergraph (lotchuazzz-crypto/papergraph-mcp, 285 stars), Control Chrome (wxtsky/byob, 132 stars) and Tapd Iteration Analysis (TencentBlueKing/bk-bcs, 840 stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.
Who maintains Skill Evaluator?
gotalab (a GitHub user) maintains it in gotalab/skillport, which has 414 GitHub stars. The repository holds 3 skills in this directory. The repository was last updated on June 24, 2026.
Source: gotalab/skillport on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.