intent-debugger: Turn vague product or feature ideas into clear, checkable requirements before planning or coding—mapping rough

by bydtesla1609 · Codex Skill · ★ 122

Last updated: · Indexed by AgentSkillsHub · Auto-synced every 8h

Security audit verdict: SAFE · quality 61/100

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.

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.

ai-agentai-skillclaude-codecodexdeepseekprompt-engineeringrequirements-analysisrequirements-engineering

Quick Facts

Stars122
Forks14
LanguagePython
CategoryCodex Skill
LicenseMIT
Quality Score61/100
Last Updated2026-11-05
Created2026-08-21
Platformsclaude-code, codex, python
Est. Tokens~14k

About intent-debugger

简体中文 &nbsp;·&nbsp; English Intent Debugger 需求澄清与意图对齐 把说不清的想法，整理成清楚、具体、可核对的需求。 &nbsp; &nbsp; <img src="https://img.shields.io/github/stars/bydtesla1609/intent-debugger?style=flat&amp;color=f5a623" alt="

Compatible Skills

These tools work well together with intent-debugger for enhanced workflows:

  • prd-taskmaster — semantic(0.27)+complementary+rare_topics+same_lang+similar_pop+shared_platform (64%)
  • agile_v_skills — semantic(0.19)+complementary+rare_topics+same_lang+similar_pop+shared_platform (61%)
  • deep-project — semantic(0.29)+complementary+same_lang+similar_pop+shared_platform (60%)

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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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