pr-reviewer: Use LLM to help you with PR review

by truskovskiyk · AI Tool · ★ 73

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Security audit verdict: SAFE · quality 60/100

None of the 42 rules matched — no credential harvesting, no data exfiltration, no curl-pipe-shell installer. Scanned against 42 published rules built on the SlowMist agent-security taxonomy, refreshed every 8 hours. Full audit →

The quality score combines nine heuristic checks of the repo and its README: completeness, clarity, specificity, examples, structure, agent readiness, step-by-step content, instruction quality and security notes. It rates how well the project explains itself to an agent, not the code.

Quick Facts

Stars73
Forks4
LanguagePython
CategoryAI Tool
LicenseApache-2.0
Quality Score60/100
Open Issues2
Last Updated2023-04-18
Created2023-04-16
Platformspython
Est. Tokens~8k

About pr-reviewer

pr-reviewer Streamline Your GitHub Pull Requests with AI, co-authored with GPT4. 🚀 Excited to announce our new open-source project: PR Review Bot, a GitHub Pull Request review bot powered by OpenAI's GPT-3.5-turbo! 🤖 PR Review Bot automatically reviews open PRs in your GitHub repository, providing helpful feedback and even approving or requesting changes based on the analysis of the PR text and...

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How this security grade is produced

Grades come from a rule-based scan built on the SlowMist agent-security taxonomy: 42 published rules, covering credential harvesting, data exfiltration, curl | sh installers and more. It is a first-layer scan, not a manual audit — we say so rather than overstate it.

The scale of the problem is documented independently: Liu et al. (2026), in a study of 31,132 agent skills, report that 26.1% contain security vulnerabilities. Our own full-catalog census is published as a citable open dataset.

Sources & who's responsible:

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