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/anti-autoresearch)<a href="https://agentmods.dev/skills/wenhaochai/claude-plugins/anti-autoresearch"><img src="https://agentmods.dev/badge/skills/wenhaochai/claude-plugins/anti-autoresearch/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/anti-autoresearch"><img src="https://agentmods.dev/badge/skills/wenhaochai/claude-plugins/anti-autoresearch.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 | $0.00275 | $0.16344 |
| Opus 5 | $0.00138 | $0.08172 |
| Sonnet 5 | $0.00055 | $0.03269 |
| Haiku 4.5 | $0.00028 | $0.01634 |
Grade A, and why
anti-autoresearch scanned grade A with 1 finding against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 11d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Makes network callslowCapability
Not a fault in itself. Listed so you know the mod talks to something, and to what.
if curl -fsSL "https://arxiv.org/e-print/$ID" -o "$PAPER_DIR/src.tgz"; then How it starts
The opening of the file, as written. The whole thing — 898 lines — stays where its author put it; the contents beside it link to each section on GitHub.
/anti-autoresearch — the orchestrator
Run a full substantive-integrity forensic pass on $ARGUMENTS and hand a human reviewer / area chair an evidence-first Integrity Forensics Report.
🔒 External cadence: the verdict is not a poll. The pipeline is the verdict-producing path — its output changes only when the paper / repo / ledger changes, not with the clock. Do not wrap
/anti-autoresearch(or any auditor sub-skill) in/loop//schedule/CronCreateto "re-check". A heartbeat may only wait on the external steps that precede the verdict (an arXiv download, a citation web lookup) — never re-fire the adjudicated verdict, and never "decide the paper is fine now." Re-run the sweep when the inputs change; that is the only honest trigger.
🛡️ The dual of ARIS. ARIS ships an internal audit stack so its own autoresearch output stays honest; Anti-Autoresearch is that same audit DNA pointed outward at a third party's submission. This is decision support for a human — it surfaces span-anchored discrepancies to investigate. It is not an AI-text detector and it does not judge misconduct (
DESIGN.md§1;references/).
Why this exists
A machine-driven research pipeline (or rushed human) writes the abstract, the tables, the method section, the bibliography, and the appendix in separate passes and never reconciles them. The result is a paper that disagrees with itself, cites papers that do not exist or argue the opposite, claims SOTA while omitting the obvious baseline, or reports numbers the code never computed. Six LLMs each re-reading the PDF would hallucinate six different structures and invite the obvious dismissal — "an LLM grading another LLM's paper is just slop."
This orchestrator answers that structurally. One deterministic pass turns the paper into a hashed, span-anchored evidence ledger; six auditors read only that ledger and propose findings; a deterministic adjudicator decides the verdict by fixed rules with no model in the loop; and observability levels make it impossible to shout "fraud" from a PDF. Same artifacts → same ledger → same verdict.
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.
- 11d ago First seen · 898 lines · 275 tokens per session scan A b92da66e7348
anti-autoresearch is a skill published in the GitHub repository wenhaochai/claude-plugins (16 stars, last pushed 11d ago), licensed MIT. It adds 275 tokens to every session and 16,344 once invoked, about $0.0014 per session on Opus 5. A static security scan graded it A with 1 finding (makes network calls). No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.
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