by nurettincoban · Claude Skill · ★ 298
Last updated: · Indexed by AgentSkillsHub · Auto-synced every 8h
git clone https://github.com/nurettincoban/ai-prd-workflow.git
Taken from the project's README on GitHub.
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.
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.
One of 14 tools we ran end to end on the same task for our Open-Source Vibe Coding Tools page (2026-10-27).
Result: At the 45-minute limit the ledger had no budget and no export. · one-sentence page: 4 of 4 checks · family ledger: 6 of 8 · opens by double-click · stopped to ask 6 times · 30.0 + 45.0 min, 13.5× the usage of no tool
| Stars | 298 |
| Forks | 34 |
| Language | Python |
| Category | Claude Skill |
| License | MIT |
| Quality Score | 70/100 |
| Last Updated | 2026-10-08 |
| Created | 2025-03-09 |
| Platforms | claude-code, cli, codex, gemini, python |
| Est. Tokens | ~17k |
📋 AI PRD Workflow RFC-driven development for AI coding agents Vague idea → verified PRD → features → rules → sequenced RFCs → reviewed, tested code Quick Start · Workflow · Commands · Why RFCs? · Examples RFC-driven since March 2025 — before planning modes existed in any AI coding agent. A lightweight RFC-driven development workflow for AI coding tools.
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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: