Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx skills add beita6969/ScienceClaw --skill fact-verificationgit clone --depth 1 https://github.com/beita6969/ScienceClawWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/beita6969/scienceclaw/fact-verification)<a href="https://agentmods.dev/skills/beita6969/scienceclaw/fact-verification"><img src="https://agentmods.dev/badge/skills/beita6969/scienceclaw/fact-verification/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/beita6969/scienceclaw/fact-verification"><img src="https://agentmods.dev/badge/skills/beita6969/scienceclaw/fact-verification.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector pass
What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00016 | $0.00416 |
| Opus 5 | $0.00008 | $0.00208 |
| Sonnet 5 | $0.00003 | $0.00083 |
| Haiku 4.5 | $0.00002 | $0.00042 |
Grade A, and why
fact-verification scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 8d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
What it actually says
Fact Verification
Purpose
Systematically verify factual claims using evidence retrieval, source evaluation, and logical reasoning.
Key Datasets
- PolitiFact (Jinyan1/PolitiFact): Political statements rated on 6-level truth scale (True, Mostly True, Half True, Mostly False, False, Pants on Fire)
- Climate-FEVER (tdiggelm/climate_fever): Climate claims labeled SUPPORTS/REFUTES/NOT_ENOUGH_INFO with evidence sentences
Protocol
- Claim decomposition — Break complex claims into atomic verifiable statements
- Evidence retrieval — Search authoritative sources for each sub-claim
- Source evaluation — Assess source credibility and potential bias
- Evidence-claim alignment — Determine if evidence supports, refutes, or is insufficient
- Verdict synthesis — Aggregate sub-verdicts into overall assessment
Verification Categories
- Scientific claims: Published findings, statistical assertions, causal claims
- Political statements: Policy claims, historical assertions, statistical citations
- Environmental claims: Climate data, pollution metrics, biodiversity assertions
- Health claims: Treatment efficacy, risk factors, epidemiological data
Verdict Scale
- VERIFIED: Multiple independent high-quality sources confirm
- LIKELY TRUE: Evidence supports but limited independent confirmation
- MIXED: Partially true with important caveats or context
- LIKELY FALSE: Evidence contradicts but some ambiguity remains
- FALSE: Clear evidence contradicts the claim
- UNVERIFIABLE: Insufficient evidence to determine
Rules
- Always cite specific evidence for each verdict
- Distinguish between factual errors and misleading framing
- Check for cherry-picked statistics or out-of-context quotes
- Consider temporal context (claim may have been true when made)
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 8d ago First seen · 41 lines · 16 tokens per session scan A 84bbe769da9b
fact-verification is a skill published in the GitHub repository beita6969/ScienceClaw (898 stars, last pushed 3mo ago), licensed MIT. It adds 16 tokens to every session and 416 once invoked, about $0.0001 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-09-03.
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