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 ntaffzii/Skill-Agents --skill claim-citation-checkgit clone --depth 1 https://github.com/ntaffzii/Skill-AgentsWrote 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/ntaffzii/skill-agents/claim-citation-check)<a href="https://agentmods.dev/skills/ntaffzii/skill-agents/claim-citation-check"><img src="https://agentmods.dev/badge/skills/ntaffzii/skill-agents/claim-citation-check/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/ntaffzii/skill-agents/claim-citation-check"><img src="https://agentmods.dev/badge/skills/ntaffzii/skill-agents/claim-citation-check.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 | $0.01259 |
| Opus 5 | $0.00056 | $0.00629 |
| Sonnet 5 | $0.00022 | $0.00252 |
| Haiku 4.5 | $0.00011 | $0.00126 |
Grade A, and why
claim-citation-check 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 12d 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 — 60 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Claim / Citation Integrity Check
Overview
LLM-generated research writing has a well-documented failure mode: citations that don't exist, or citations attached to a claim the source doesn't actually support (topically related but not actually saying that). Neither failure is visible from reading the text alone — the sentence reads as confidently sourced either way. This skill is a pre-finalization gate: before a research output ships, walk every citation and every uncited specific claim through an explicit check instead of trusting that "it has a citation" means "it's verified."
This is a general-purpose research-integrity check, not specific to academic papers — it applies to daily-news-report, github-skill-research, project-discovery, or any output that cites sources.
When to use
- ก่อนส่งมอบ research report, news brief, หรือ summary ที่มี citation/สถิติ
- ตรวจว่า claim แต่ละอันมี source รองรับจริง ไม่ใช่แค่ "ดูน่าเชื่อถือ"
- Reviewing a draft where numbers, dates, or attributed quotes appear — verify each against its actual source before finalizing
- As the last step of any workflow that produces a sourced output (pairs naturally with
markdown-report,daily-news-report,github-skill-research)
When NOT to use
- The output contains no citations, statistics, or specific factual claims — general reasoning/opinion/code doesn't need this check
- The claim is genuinely common knowledge with no realistic chance of being wrong (e.g. "Python is a programming language") — citing every sentence, including trivial ones, is its own failure mode (noise that buries the claims that actually need scrutiny)
Core knowledge
Three questions for every citation, in order:
- Does the source exist? A URL, DOI, paper title, or quote that looks plausible can still be fabricated. If a tool with real web access is available (WebFetch/WebSearch), actually resolve the citation rather than trusting that it looks well-formed.
- Does the source say what the claim attributes to it? A citation can be to a real, existing source that simply doesn't support the specific claim next to it — topically related is not the same as actually supporting the claim. This is the failure mode most likely to slip through casual review, because the citation "checks out" at a glance.
- Is the number/date/quote exact? A citation can correctly support the general claim while misquoting the specific figure (rounding, unit confusion, conflating two different reported numbers). Check the exact figure against the source, not just the general direction.
What ships with it
1 file 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.
- 12d ago First seen · 60 lines · 112 tokens per session scan A 43d2f76aee29
claim-citation-check is a skill published in the GitHub repository ntaffzii/Skill-Agents (4 stars, last pushed 3d ago), licensed MIT. It adds 112 tokens to every session and 1,259 once invoked, about $0.0006 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 2026-08-31.
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