No red flags found in any of the 11 categories — no credential harvesting, no data exfiltration, no curl-pipe-shell installer. Scanned against the SlowMist agent-security taxonomy, refreshed every 8 hours. Full audit →
by netresearch · Agent Tool · ★ 78
Last updated: · Indexed by AgentSkillsHub · Auto-synced every 8h
🔒 Is agent-rules-skill safe to install? View the security audit →
AGENTS.md Generator Skill Netresearch AI skill for generating and maintaining AGENTS.md files following the agents.md specification. What is AGENTS.md? A context file written for AI coding agents, not humans. Human readability is a side effect, not a goal. Adopted by 60,000+ open-source projects. See the official specification and best practices from 2,500+ repositories. Standards Compliance This skill implements two complementary standards: agents.md - The file format this skill generates. A simple Markdown convention for guiding AI coding agents, supported by Claude Code, GitHub Copilot, Cursor, and 60,000+ open-source projects. Agent Skills - How this skill is packaged and distributed. A portable format for procedural knowledge that works across AI agents.
| Stars | 78 |
| Forks | 6 |
| Language | Shell |
| Category | Agent Tool |
| Quality Score | 70.531148512969/100 |
| Open Issues | 1 |
| Last Updated | 2026-09-22 |
| Created | 2025-10-18 |
| Platforms | claude-code, cli, go, node |
| Est. Tokens | ~12k |
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agent-rules-skill is Agent Skill for generating AGENTS.md files following the agents.md convention | Claude Code compatible. It is categorized as a Agent Tool with 78 GitHub stars.
agent-rules-skill is primarily written in Shell. It covers topics such as agent-skills, agents-md, ai-agent.
You can find installation instructions and usage details in the agent-rules-skill GitHub repository at github.com/netresearch/agent-rules-skill. The project has 78 stars and 6 forks, indicating an active community.
The top alternatives to agent-rules-skill on Agent Skills Hub include bria-skill, nelson, google-analytics-mcp. Each offers a different approach to the same problem space — compare them side-by-side by stars, quality score, and community activity.
Grades come from a rule-based scan built on the SlowMist agent-security taxonomy, covering 11 red-flag categories including credential harvesting, data exfiltration, and curl | sh installers. 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: