fact-checking

fact-checking is a skill for Claude Code, Codex from github/gh-aw. It costs 36 tokens per session (469 once invoked), scanned A, original, MIT.

A review method for checking whether technical claims, references, API endpoints, and other deliverables are supported by evidence. It tests alternative explanations and labels confidence.

In plain words
What is it for?
Use it to verify claims, challenge assumptions, check URLs and package names, and produce a structured review verdict.
Why use it?
It reduces the risk of publishing incorrect information or relying on links and interfaces that do not exist.

Skill for Claude CodeCodex

About the project

GitHub Agentic Workflows is a GitHub CLI extension that lets developers define AI-assisted repository automation in Markdown and run it through GitHub Actions. It is intended for tasks requiring interpretation or reasoning, such as issue triage, pull-request review, CI investigation, documentation maintenance, and dependency analysis. The catalogue entries provide skills and agents for working with these workflows.

github/gh-aw · 5,104 stars · on GitHub

Install

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.

agentmods
npx agentmods add skills/github/gh-aw/fact-checking
Any agent
npx skills add github/gh-aw --skill fact-checking
Clone the repo
git clone --depth 1 https://github.com/github/gh-aw

Made for: Claude Code, Codex.

Wrote 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.

agentmods badge for fact-checking

README.md
[![agentmods](https://agentmods.dev/badge/skills/github/gh-aw/fact-checking.svg)](https://agentmods.dev/skills/github/gh-aw/fact-checking)
Your own site
<a href="https://agentmods.dev/skills/github/gh-aw/fact-checking"><img src="https://agentmods.dev/badge/skills/github/gh-aw/fact-checking.svg" alt="Measured on agentmods" height="20"></a>
Per session 36 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 469 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. Scan, not verified.
Origin original No closer match found in the catalogue.
Token cost

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.

ModelPer sessionOnce invoked
Fable 5 $0.00036 $0.00469
Opus 5 $0.00018 $0.00234
Sonnet 5 $0.00007 $0.00094
Haiku 4.5 $0.00004 $0.00047

Measured yesterday against content hash f03e598d6790, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade A, and why

fact-checking 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 yesterday.

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.

Origin

Copies of this mod

2 near-identical copies found in the catalogue:

.squad/templates/skills/fact-checking/SKILL.md · 61 lines

What it actually says

Skill: Fact Checking

Context

Codifies the challenger agent review output format and methodology so any agent performing fact-checking or review produces consistent, structured output.

Pattern

Review Methodology

For every claim or deliverable under review:

  1. Ask: "What evidence supports this? What would disprove it?"
  2. Generate counter-hypotheses and test them against available data
  3. Verify URLs, package names, API endpoints, and external references actually exist
  4. Flag confidence levels: ✅ Verified, ⚠️ Unverified, ❌ Contradicted

Review Output Format

When reviewing another agent's work, use this template:

### Fact Check — {deliverable name}
**Claims verified:** {count}
**Issues found:** {count}

| # | Claim | Status | Evidence/Notes |
|---|-------|--------|---------------|
| 1 | {claim} | ✅/⚠️/❌ | {supporting or contradicting evidence} |

**Counter-hypotheses tested:**
- {alternative explanation + result}

**Verdict:** {PASS / PASS WITH NOTES / NEEDS REVISION}

Confidence Levels

  • Verified — evidence confirms the claim
  • ⚠️ Unverified — cannot confirm or deny; suggest verification method
  • Contradicted — evidence disproves the claim

Ceremony Integration

Auto-trigger this skill before any architecture decision, or when an agent claim contains superlatives or percentage thresholds (e.g., "saves 75%", "always", "never"). The coordinator spawns the challenger agent with:

Challenger — fact-check {agent}'s claim: "{claim}"
Cite evidence for every verdict. Max 3 investigation cycles.
Changes

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.

  1. yesterday First seen · 61 lines · 36 tokens per session scan A f03e598d6790

Subscribe to this mod's changes

fact-checking is a skill published in the GitHub repository github/gh-aw (5,104 stars, last pushed today), licensed MIT. It adds 36 tokens to every session and 469 once invoked, about $0.0002 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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