by Agent-Field · Agent Tool · ★ 649
Last updated: · Indexed by AgentSkillsHub · Auto-synced every 8h
git clone https://github.com/Agent-Field/pr-af
git clone https://github.com/Agent-Field/pr-af.git && cd pr-afTaken from the project's README on GitHub. Check the security audit before running it.
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.
| Stars | 649 |
| Forks | 73 |
| Language | Go |
| Category | Agent Tool |
| Quality Score | 67/100 |
| Open Issues | 4 |
| Last Updated | 2026-09-21 |
| Created | 2026-03-11 |
| Platforms | go |
| Est. Tokens | ~19k |
PR-AF Open-Source Agentic Code Review Built on AgentField Benchmark • One-Call DX • How It Works • Comparison • Quick Start • Architecture PR-AF is the #1 open-source code reviewer on Martian Code-Review-Bench.
Looking for a pr-af alternative? If you're comparing pr-af with other agent tool tools, these 6 projects are the closest alternatives on Agent Skills Hub — ranked by topic overlap, star count, and community traction.
The self-hosted AI workflow automation platform for Git repositories.
Desktop AI Assistant powered by GPT-6, GPT-5, Gemini, Claude, Grok, Ollama, DeepSeek, Perplexity, and more - c
The python library for research and development in NLP, multimodal LLMs, Agents, ML, Knowledge Graphs, and mor
A curated collection of top-tier penetration testing tools and productivity utilities across multiple domains.
The Simple Agent Development Kit.
Flow-Like: Strongly Typed Enterprise Scale Workflows. Built for scalability, speed, seamless AI integration an
Explore other popular agent tool tools:
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: