Getting it into your agent
This one installs as part of its plugin. Adding the marketplace and installing the plugin brings it with everything else the plugin ships.
/plugin marketplace add wenhaochai/claude-plugins/plugin install anti-autoresearchWrote 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/wenhaochai/claude-plugins/citation-forensics)<a href="https://agentmods.dev/skills/wenhaochai/claude-plugins/citation-forensics"><img src="https://agentmods.dev/badge/skills/wenhaochai/claude-plugins/citation-forensics/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/wenhaochai/claude-plugins/citation-forensics"><img src="https://agentmods.dev/badge/skills/wenhaochai/claude-plugins/citation-forensics.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 | $0.00079 | $0.07690 |
| Opus 5.5 | $0.00032 | $0.03076 |
| Sonnet 5.5 | $0.00016 | $0.01538 |
| Haiku 4.5 | $0.00008 | $0.00769 |
Grade A, and why
citation-forensics 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 24d 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.
This is a copy
94% identical to citation-forensics — 346 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.
How it starts
The opening of the file, as written. The whole thing — 493 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Citation Forensics — are the references real and honestly used?
Audit citation integrity for: $ARGUMENTS (requires claims.json from
/evidence-ledger; reasons over its type:"citation" claims). Emit span-anchored
citation-forensics.findings.json. This skill computes no verdict.
🔒 Run once per input change; never wrap in
/loop,/scheduleorCronCreate(${CLAUDE_PLUGIN_ROOT}/support/references/run-cadence.md). Re-run only when the paper, the ledger or the bibliography changes (bibliography finalized → ledger rebuilt → audit once).
Read reference/rationale.md for the ARIS citation-audit lineage and the failure modes this skill exists to catch.
Core principle
Ledger-anchored, span-verified, canonical-fact-checked-or-handed-off, reviewer≠adjudicator, detect-only.
- The cite keys and the citing sentences come from the deterministic ledger
(
claims.json,type:"citation"), never from re-reading the PDF. - The executor assembles a neutral per-key dossier (citing spans + the claimed
.bibmetadata) and gathers a reproducible resolution snapshot of the canonical record (DBLP / arXiv / DOI). It gathers facts, never a judgment — whether a mismatch is fabrication, a typo, or a preprint→venue migration is the reviewer's call. - A fresh cross-model reviewer (gpt-5.5 xhigh, one thread per cited key) proposes findings, judging existence + metadata + context over those facts.
- Every above-info finding cites a ledger
claim_id+ a verbatim span of the citing sentence (references/integrity-forensics-contract.mdrules 1–2). The bib entry, the canonical record, and any URL live in the finding'sdescription, never as the anchor span. - The model proposes;
tools/adjudicate_findings.pydecides (references/reviewer-independence.mdLayer 2). This skill emits findings only. - Fact-or-hand-off honesty. Existence/metadata MUST be settled against a real
source (snapshot record + URL in
description). Cannot settle →verdict_local: needs_external_check— never a guessed "fabricated". A false hallucination flag is a serious error.
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.
- 24d ago Changed · -304 lines 19c5f06c20f0
- 1mo ago Changed · -114 tokens per session e41ec8f7191c
- 1mo ago Changed d7a8b3aef23f
- 1mo ago Changed 64c00079a68a
- 1mo ago First seen · 797 lines · 193 tokens per session scan A 57bcfbebb992
citation-forensics is a skill published in the GitHub repository wenhaochai/claude-plugins (18 stars, last pushed yesterday), licensed MIT. It adds 79 tokens to every session and 7,690 once invoked, about $0.0003 per session on Opus 5.5. A static security scan graded it A with 0 findings. It is 94% identical to citation-forensics, differing in 346 lines, and is treated as a copy.
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