bullshit-detector

Featured

Fact-check and hype-audit content. Extracts the discrete claims from a video, article, tweet, or PDF, verifies each against independent sources via web search, and produces a report card with per-claim verdicts and an overall BS score (0-10). Use when the user asks to fact-check, verify, debunk, or evaluate credibility — "is this true/legit/bullshit", "check this video", "how much of this holds up".

Data & Documents 149 stars 9 forks Updated today MIT

Install

View on GitHub

Quality Score: 87/100

Stars 20%
72
Recency 20%
100
Frontmatter 20%
70
Documentation 15%
100
Issue Health 10%
50
License 10%
100
Description 5%
100

Skill Content

# bullshit-detector Separate what's verifiably true from what's hype in any piece of content. ## Workflow **Start at step 1 now. The steps below are the plan** — they are already ordered, and each one says what it needs. There is nothing to work out in advance, and working it out anyway is measurably expensive: across 35 instrumented runs the phase before the first tool call is almost entirely deliberation, 15% of all the thinking a run does, and the single longest uninterrupted block on record — 421 seconds — sits there, before a claim had been read or a search issued. Read step 1, do step 1. **Two modes, and the user picks.** Default is **full** — every step below as written. Run **quick** only when the user asked for speed in this request ("quick check", "rough read", "gut check", "don't spend 20 minutes"); never choose it silently, and when in doubt, run full. Quick cuts **breadth, never depth** — measured on this exact corpus: capping follow-up searches bought no wall time at all and collapsed the confirm rate, because a claim that gets one search stalls at 🟡 on evidence a second search would have settled. So a claim quick mode checks gets the full treatment, and the cuts are three, named at the point each applies below: only the five most consequential incidental claims are checked (the rest are ⚪ not checked), no `coverage-check`, and no hostile-reader section. **Everything else holds — especially the steelman before any ❌, because a fast false accusation is still...

Details

Author
SerhiiKorniienko
Repository
SerhiiKorniienko/bullshit-detector
Created
2 months ago
Last Updated
today
Language
Python
License
MIT

Bundled in these plugins

Similar Skills

Semantically similar based on skill content — not just same category

AI & Automation Listed

bs-detector

Fact-check a short-form video (Instagram reel, TikTok, YouTube Short, X video) claim by claim — transcribe it, pull out every checkable assertion, verify each one against real sources, and score it. Use whenever the user shares a video link or a transcript and asks whether it's true, accurate, legit, or nonsense; wants claims verified or sources checked; says a video "sounds wrong", "seems like BS", "is this guy lying", "is this real"; or wants a fact-check of anything a creator said. Trigger on "fact check", "BS detector", "is this true", "debunk", "verify this", or any shared short-form video link where accuracy is the question.

0 Updated 2 months ago
chris-jk
Data & Documents Listed

factcheck

Adversarial citation and claim audit for any document — "do these sources actually say what the text claims?" Takes a markdown file, URL, or pasted draft (including this repo's own pulse/verdict briefs), extracts every checkable claim, then fans out verifier sub-agents instructed to refute, not confirm: does the cited link resolve AND assert the claim as stated, is the source primary or a laundered secondary write-up, has the claim gone stale. Emits a graded audit table — VERIFIED / MISATTRIBUTED / UNSUPPORTED / STALE / UNCHECKABLE — with a quoted passage as evidence for every grade, saved to out/factcheck/. Advisory: it grades, the human edits. Use when the user wants to check citations, verify sources, or audit a report, post, or brief — e.g. "/factcheck <doc>", "verify the sources in this", "are these citations real?", "is this actually true?". For researching a fresh topic use pulse; for judging code changes use done.

9 Updated 1 weeks ago
duthaho
Data & Documents Listed

big-if-true

Rigorous, claim-by-claim fact-checking of any article, draft, newsletter, post, press release, or document, in any language: extract every checkable factual claim, verify each against primary records and independent sources (official data APIs, filings, transcripts, archives, the live web, and the browser when pages block fetch), and return calibrated verdicts with citations. Use whenever the user asks to fact-check something, verify claims, stats, or figures before quoting or publishing them, check whether a text is accurate, asks "is this true?", wants a pre-publication accuracy pass on a draft, asks to go through their own or a colleague's piece because something feels off or the numbers seem wrong, wants to know whether a quote, study, or social-media post is real, or shares an article and wants to know if it holds up — even if they never use the words "fact-check." Requires web search; code execution builds the report page and runs the data lookups (falls back to a text report without it).

1 Updated today
Verso-Lab