bullshit-detector: Agent skills that fact-check the internet: claim-by-claim verification with sources and a 0-10 BS score

by SerhiiKorniienko · Agent Tool · ★ 149

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

How to install bullshit-detector

npx skills@latest add SerhiiKorniienko/bullshit-detector
/plugin marketplace add SerhiiKorniienko/bullshit-detector

Taken from the project's README on GitHub.

Security audit verdict: SAFE · quality 72/100

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.

agent-skillsai-agentsclaude-codecontent-analysisfact-checkingmisinformationskillsskills-shyt-dlp

Quick Facts

Stars149
Forks9
LanguagePython
CategoryAgent Tool
LicenseMIT
Quality Score72/100
Open Issues5
Last Updated2026-09-29
Created2026-07-27
Platformsclaude-code, python
Est. Tokens~16k

About bullshit-detector

Bullshit Detector Agent skills that fact-check the internet. Point your agent at a viral YouTube video, article, tweet, or PDF — get a claim-by-claim verification report with sources and a BS score (0–10) instead of taking "10 WAYS TO MAKE MONEY WITH AI 🤯" at face value. Portable Agent Skills — plain markdown + self-contained Python.

Compatible Skills

These tools work well together with bullshit-detector for enhanced workflows:

  • youtube-to-knowledge — semantic(0.25)+complementary+rare_topics+same_lang+similar_pop+shared_platform (63%)

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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:

View on GitHub → Browse Agent Tool tools