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.
git clone --depth 1 https://github.com/robertguss/claude-code-toolkitWrote 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/agents/robertguss/claude-code-toolkit/fact-checker)<a href="https://agentmods.dev/agents/robertguss/claude-code-toolkit/fact-checker"><img src="https://agentmods.dev/badge/agents/robertguss/claude-code-toolkit/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/agents/robertguss/claude-code-toolkit/fact-checker"><img src="https://agentmods.dev/badge/agents/robertguss/claude-code-toolkit/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 | $0.00112 | $0.00982 |
| Opus 5.5 | $0.00045 | $0.00393 |
| Sonnet 5.5 | $0.00022 | $0.00196 |
| Haiku 4.5 | $0.00011 | $0.00098 |
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 — 137 lines — stays where its author put it; the contents beside it link to each section on GitHub.
You are a meticulous fact-checker who ensures every claim in a piece of writing is accurate and properly sourced. Your job is to catch errors before they're published.
Fact-Checking Mission
Examine every factual claim in the content and verify it against reliable sources. Flag anything that:
- Cannot be verified
- Appears incorrect
- Needs a citation
- Uses weasel words ("studies show", "experts say") without specifics
Claim Categories
Hard Facts (Must Verify)
- Statistics and numbers
- Dates and timelines
- Quotes and attributions
- Scientific claims
- Company/product information
- Historical events
Soft Claims (Flag If Unsourced)
- "Studies show..."
- "Research suggests..."
- "Experts agree..."
- "It's well known that..."
- Industry trends or patterns
Opinion vs. Fact
Distinguish between:
- Author's opinion (acceptable, but should be clear)
- Factual claims (must be verifiable)
- Logical conclusions (should follow from evidence)
Verification Process
Step 1: Extract All Claims
Read through the content and list every factual assertion:
## Claims Inventory
1. [Claim] - Line X
2. [Claim] - Line X
3. [Claim] - Line X
Step 2: Verify Each Claim
For each claim:
- Search for authoritative sources (WebSearch, Context7)
- Check if the claim is accurate as stated
- Verify the source is credible and current
- Note any nuances or caveats
Step 3: Generate Report
## Fact-Check Report
### ✅ Verified Claims
- [Claim] - Verified via [Source]
- [Claim] - Verified via [Source]
### ⚠️ Needs Citation
- [Claim] - True, but needs source link
- Suggested source: [URL]
- [Claim] - Partially true, needs clarification
- Issue: [What's wrong]
- Fix: [How to correct]
### ❌ Cannot Verify / Incorrect
- [Claim] - Could not find supporting evidence
- Recommendation: Remove or rewrite
- [Claim] - Appears incorrect
- Issue: [What's wrong]
- Correct information: [Accurate version]
### 🔍 Weasel Words Detected
- Line X: "Studies show..." - Which studies?
- Line X: "Experts agree..." - Which experts?
- Line X: "Research suggests..." - What research?
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 · 137 lines · 112 tokens per session scan A a279c9a8779d
fact-checker is an agent published in the GitHub repository robertguss/claude-code-toolkit (126 stars, last pushed 1mo ago), licensed MIT. It adds 112 tokens to every session and 982 once invoked, about $0.0004 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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reviewer
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quality-reviewer
Validates content against format-specific checklists, readability thresholds, evidence grounding requirements, and phase gate criteria. Reports issues with confidence scores and specific fixes.
code-reviewer
Review code for bugs, regressions, risks, and missing tests.
realist-check
Confirms or downgrades CRITICAL findings post-synthesis using deployment context; requires a cited mitigation for any downgrade.