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 moonlight-lupin/agent-skills --skill fact-checkergit clone --depth 1 https://github.com/moonlight-lupin/agent-skillsWrote 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/moonlight-lupin/agent-skills/fact-checker)<a href="https://agentmods.dev/skills/moonlight-lupin/agent-skills/fact-checker"><img src="https://agentmods.dev/badge/skills/moonlight-lupin/agent-skills/fact-checker/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/moonlight-lupin/agent-skills/fact-checker"><img src="https://agentmods.dev/badge/skills/moonlight-lupin/agent-skills/fact-checker.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 | $0.00054 | $0.02770 |
| Opus 5.5 | $0.00022 | $0.01108 |
| Sonnet 5.5 | $0.00011 | $0.00554 |
| Haiku 4.5 | $0.00005 | $0.00277 |
Grade A, and why
fact-checker 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 20d 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.
How it starts
The opening of the file, as written. The whole thing — 243 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Fact Checker
Overview
Fact Checker is a targeted verification workflow for one factual assertion at a time. It exists because agents often produce claims that sound plausible but may be hallucinated, copied from a weak source, contradicted by later data, or stale after new reporting. A normal research pass can gather useful background while still failing to answer the narrow question: is this specific claim supported, contradicted, outdated, or not verifiable from available sources?
Use this skill to turn a claim into structured search queries, collect confirming and contradicting passages from multiple independent sources, assess source independence and recency, then produce a concise verification report with citations and a calibrated verdict.
Quick Start
From this skill directory:
python scripts/verify.py structure --claim "Singapore's GDP grew 4.1% in 2025"
Or use the compatibility shortcut:
python scripts/verify.py --claim "Singapore's GDP grew 4.1% in 2025"
After collecting source passages with a web search tool and web extraction tool, generate a report:
python scripts/verify.py report \
--claim claim.json \
--sources sources.json \
--output verification-report.md
Completion criterion: the report states a verdict, lists every cited source, surfaces contradictions if present, and includes a source-independence note.
When to Use
- Verify a single factual claim before publishing, sending, or relying on it.
- Check whether a statistic, event, relationship, quote, or date is supported by sources.
- Cross-check an agent-written paragraph by verifying its highest-impact claims one by one.
- Audit a cited claim for source independence and recency.
When NOT to Use
- Broad topic research or literature review → use a deep research workflow.
- Full entity background dossiers → use an entity research workflow.
- Citation database management → use a source tracking workflow.
- Propaganda, bias, or intent analysis → this skill only verifies factual support.
- Real-time market, weather, emergency, legal, medical, or regulatory determinations → use authoritative live systems and human review.
What ships with it
5 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
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.
- 20d ago Changed · +5 tokens per session 034cef59b334
- 1mo ago First seen · 243 lines · 49 tokens per session scan A 1574782672b0
fact-checker is a skill published in the GitHub repository moonlight-lupin/agent-skills (112 stars, last pushed 4d ago), licensed MIT. It adds 54 tokens to every session and 2,770 once invoked, about $0.0002 per session on Opus 5.5. 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 2026-08-30.
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