by russelleNVy · Agent Tool · ★ 953
Last updated: · Indexed by AgentSkillsHub · Auto-synced every 8h
git clone https://github.com/russelleNVy/three-man-team.git .claude/skills/three-man-team
git clone https://github.com/russelleNVy/three-man-team.git ~/.claude/skills/three-man-team
Taken 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 | 953 |
| Forks | 126 |
| Language | Shell |
| Category | Agent Tool |
| License | MIT |
| Quality Score | 67/100 |
| Last Updated | 2026-06-09 |
| Created | 2026-03-31 |
| Platforms | claude-code, cli |
| Est. Tokens | ~348k |
russellenvy.github.io/three-man-team The Problem With AI Coding Tools AI coding tools are powerful but undisciplined. They read entire codebases when they need one function. They add features nobody asked for. They drift mid-task. They burn tokens on every session doing work that didn't need to happen. The solution isn't a better prompt. It's a process.
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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: