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 NickCrew/Claude-Cortex --skill fact-checkergit clone --depth 1 https://github.com/NickCrew/Claude-CortexWrote 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/nickcrew/claude-cortex/fact-checker)<a href="https://agentmods.dev/skills/nickcrew/claude-cortex/fact-checker"><img src="https://agentmods.dev/badge/skills/nickcrew/claude-cortex/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/nickcrew/claude-cortex/fact-checker"><img src="https://agentmods.dev/badge/skills/nickcrew/claude-cortex/fact-checker.svg" alt="Reviewed on agentmods" width="80" height="20"></a>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 | $0.00071 | $0.02979 |
| Opus 5.5 | $0.00028 | $0.01192 |
| Sonnet 5.5 | $0.00014 | $0.00596 |
| Haiku 4.5 | $0.00007 | $0.00298 |
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 1mo 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 — 213 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Fact Checker
Overview
This skill provides a structured approach to evaluating factual claims—assessing whether a statement is accurate, partially accurate, misleading, or false, and explaining why with evidence and reasoning. Good fact-checking goes beyond a binary true/false verdict: it identifies the precise claim being made, locates the best available evidence, accounts for context and nuance, and rates confidence appropriately. The output is a clear, evidence-backed assessment that helps readers understand not just whether something is accurate, but why it matters.
When to Use
- Verifying statistics, quotes, or factual assertions in articles or documents
- Checking whether a viral social media claim holds up to scrutiny
- Assessing whether historical facts cited in writing are accurate
- Auditing factual claims in a draft before publication
- Evaluating whether scientific findings are being accurately reported
- Confirming whether attributed quotes are real and in context
- Vetting claims in speeches, presentations, or marketing copy
When NOT to Use
- Evaluating subjective opinions or value judgments ("X policy is better than Y")
- Providing legal advice or legal interpretations of statutes
- Providing medical diagnoses or treatment recommendations
- Verifying real-time data such as live stock prices, current weather, or breaking news
- Assessing internal business claims that require proprietary data access
- Deciding which of two contested scientific theories is definitively correct (use
literature-reviewerskill for contested scientific debates)
Quick Reference
| Task | Approach |
|---|---|
| Identify the claim | Isolate the precise factual assertion—strip out opinion and framing |
| Primary sources | Seek original studies, official records, or direct quotes over secondary reports |
| Verdict labels | True / Mostly True / Mixed / Mostly False / False / Unverifiable |
| Context matters | Accurate statistics can still mislead if context is stripped away |
| Quotes | Check original source; confirm attribution, date, and surrounding context |
| Statistics | Verify source, date, sample size, and whether the stat is being applied correctly |
| Confidence level | State confidence (High / Medium / Low) based on source quality and evidence volume |
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.
- 1mo ago First seen · 213 lines · 71 tokens per session scan A 584ffbf6c715
fact-checker is a skill published in the GitHub repository NickCrew/Claude-Cortex (61 stars, last pushed 4mo ago), licensed MIT. It adds 71 tokens to every session and 2,979 once invoked, about $0.0003 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 2026-09-03.
Other skills, from other repositories
source-credibility-brief
Assesses the credibility of a source whose claims appear in a draft — expertise, track record, conflicts of interest, and the corroboration needed before publication.
fact-check-prompt
Generates a systematic fact-checking checklist from a draft article, categorizing every verifiable claim by type and priority, with the specific verification question, recommended source type, and appropriate verification strategy for each — across six distinct claim categories with tailored methodologies.
source-verification
Walks through structured verification of sources, claims, images, video, and documents across five verification modes — visual media, documents, anonymous sources, expert credentials, and social media content — using the SIFT framework, forensic metadata inspection, deepfake indicators, C2PA Content Credentials, and…
ai-hallucination-fact-check-protocol
Design a fact-checking protocol for AI-generated text, extending SIFT with AI-specific adaptations for hallucination detection. Use when students need to verify AI claims and citations.
always-verify-numbers-and-links
Verify statistics, contact details, calculations, and URLs against appropriate sources before using them in a deliverable.
flag-speculative-statements
Label verified facts, estimates, heuristics, and predictions distinctly in an analytical response.