GitHub Skill Analyzer for fast browser-based work
Analyze a public GitHub Skill repository for SKILL.md structure, README signals, maintenance, license, scripts, and common risk patterns directly in the browser.
中文：直接在浏览器里分析公开 GitHub Skill 仓库的 SKILL.md 结构、README 信号、维护状态、许可证、脚本和常见风险模式。
Example: Paste a Nuwa, Darwin, Claude Code, Codex, or Agent Skill repository URL before installing, bookmarking, or recommending it.
Inspect whether a public repository is a real Skill package and what needs manual review.
What you paste
A GitHub Skill repository URL.
What you get
- Skill structure score
- Repository signals
- Script and asset review queue
Next step
Use it before installing third-party Skills or adding them to an agent workflow.
Decide whether this tool fits the job
Fineuralab core tool pages do more than expose an input box. They explain fit, boundaries, and expected output so you can decide whether to continue.
Good fit
- Paste a public GitHub repository URL before installing or recommending a third-party AI Skill.
- Review SKILL.md structure, README context, root files, license, maintenance freshness, and common risk patterns in one pass.
- Use the generated checklist to decide which scripts, references, or install steps need manual reading.
Not a good fit
- High-risk legal, medical, financial, or compliance conclusions.
- Unredacted production secrets, customer records, internal strategy, or private research material.
Privacy boundary
- The analyzer runs without Cloud Functions or a paid backend; the visitor's browser calls public GitHub endpoints.
- GitHub may receive normal web request information such as IP address, browser details, requested repository URLs, and timing.
- GitHub rate limits public unauthenticated requests, so heavy repeated analysis may temporarily fail.
A public repository claiming to be an Agent Skill or Claude/Codex Skill.
Skill structure score plus review queue for SKILL.md, scripts, references, assets, and permissions.
Where this tool fits in real work
Use cases
- Paste a public GitHub repository URL before installing or recommending a third-party AI Skill.
- Review SKILL.md structure, README context, root files, license, maintenance freshness, and common risk patterns in one pass.
- Use the generated checklist to decide which scripts, references, or install steps need manual reading.
Review notes
- The analyzer runs without Cloud Functions or a paid backend; the visitor's browser calls public GitHub endpoints.
- GitHub may receive normal web request information such as IP address, browser details, requested repository URLs, and timing.
- GitHub rate limits public unauthenticated requests, so heavy repeated analysis may temporarily fail.
- A strong score is not a safety guarantee. It means the repository has clearer review signals.
Local-first handling
This page is built as a browser utility. Inputs are processed in the page where possible, with no account requirement and no intentional upload step for the tool workflow.
AI Skill repository review workflow
A repository can look like a Skill package without being safe or useful to install. This analyzer helps visitors inspect Skill structure, scripts, references, assets, maintenance, and review gaps before trusting a third-party repository.
Recommended steps
- Start with the repository purpose, license, README, and SKILL.md structure.
- Inspect scripts, install commands, external downloads, and referenced folders before running anything.
- Use the report as a manual reading queue, not as an install approval.
Real examples
- Checking a Nuwa-style Skill repository before studying it.
- Reviewing a Claude Code Skill collection before installing.
- Comparing two third-party Skills that solve similar tasks.
Common mistakes
- Treating GitHub stars as a security review.
- Running install commands before reading scripts.
- Ignoring network access because the repository has a Skill-looking file structure.
Start with one realistic scenario
Sample input
A public repository claiming to be an Agent Skill or Claude/Codex Skill.
Expected output
Skill structure score plus review queue for SKILL.md, scripts, references, assets, and permissions.
Review point
Use the result to decide what to read manually before installing the Skill.
Open the tool above and try a similar sample. Replace real private or production data with placeholders first.
A stronger way to use this tool
Most tasks do not end with one button press. Use this page as one step in a short review path so the result is easier to trust and reuse.
Understand this tool with real inputs
These examples show inputs, outputs, review checks, and practical judgment points before copying results.
When to use GitHub Skill Analyzer
Good fit
- Paste a public GitHub repository URL before installing or recommending a third-party AI Skill.
- Review SKILL.md structure, README context, root files, license, maintenance freshness, and common risk patterns in one pass.
- Use the generated checklist to decide which scripts, references, or install steps need manual reading.
Before copying results
- The analyzer runs without Cloud Functions or a paid backend; the visitor's browser calls public GitHub endpoints.
- GitHub may receive normal web request information such as IP address, browser details, requested repository URLs, and timing.
- GitHub rate limits public unauthenticated requests, so heavy repeated analysis may temporarily fail.
Use a stricter workflow
If the context includes production secrets, customer records, private research material, or executable scripts, redact first and use a stricter human review workflow.
Keep learning this workflow
Keep working with nearby utilities
GitHub Skill Analyzer questions
Does this send requests to GitHub?
Yes. Your browser requests public GitHub API and raw file URLs for the repository you enter. Fineuralab does not proxy those requests or store the analysis content.
Does this prove a repo is safe?
No. It produces a practical review checklist and risk signals for manual inspection.
Is this tool free?
Yes. The current Toolkits tools are free to use and do not require an account. If advertising is added later, it should be clearly labeled and kept away from primary tool controls.