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 | $0.00082 | $0.09225 |
| Opus 5.5 | $0.00033 | $0.03690 |
| Sonnet 5.5 | $0.00016 | $0.01845 |
| Haiku 4.5 | $0.00008 | $0.00923 |
Grade A, and why
anti-autoresearch 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.
How it starts
The opening of the file, as written. The whole thing — 492 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.
Read reference/rationale.md for background: why this orchestrator exists and how it is the outward-facing dual of ARIS.
Pipeline role (what this run does, and never does)
The one-page stage diagram (ingest → ledger → auditors → memos → adjudicate → present) is in reference/pipeline-diagram.md.
- Auditors propose; the adjudicator decides. No auditor (and not this orchestrator)
ever computes
overall_verdict; onlytools/adjudicate_findings.pydoes, by fixed rules (references/reviewer-independence.mdLayer 2;DESIGN.md§3). - Detect-only. No step ever edits the audited paper or repo. This is a third-party
forensics tool, never a co-author (no
Editis granted; the reviewer sandbox isread-only). - Observability caps everything. L0 (PDF-only) / L1 (source) cannot assert
code/result-level fraud — those need L2 (repo + results). The adjudicator demotes any
finding above the run's level (
references/observability-levels.md;DESIGN.md§4).
Constants & conventions
REVIEWER_MODEL = gpt-5.5 (via mcp__codex__codex) — a DIFFERENT model family from the executor (Claude)
REVIEWER_REASONING = xhigh — always; the effort knob never lowers reviewer quality
REVIEWER_SANDBOX = read-only — detect-only; the reviewer never mutates the paper
THREAD_POLICY = FRESH mcp__codex__codex per dimension / per cited key; NEVER codex-reply across them
(codex-reply is deliberately NOT in allowed-tools — the bias guard)
RUN_THREADS = serial — one codex thread at a time; concurrent codex MCP calls can hang
LEDGER_VERSION = 0.1 (stamped by tools/build_claim_ledger.py)
TAXONOMY_VERSION = 0.5 (references/hack-pattern-taxonomy.md; 46 integrity patterns A–H + 13 AIS impressions + 2 ADV advisory; stamped into every report)
OBSERVABILITY = derived L0 (pdf/text) · L1 (latex, no results) · L2 (repo + results); L3 NEVER (no reproduction)
ADJUDICATOR = deterministic-rules-v0 (tools/adjudicate_findings.py — the ONLY verdict source)
DETECT_ONLY = true · EMITS_VERDICT = true (computed by code, not by a model)
REAL TOOLS (resolve ROOT="${CLAUDE_PLUGIN_ROOT}/support"):
tools/build_manifest.py · tools/build_claim_ledger.py · tools/check_numeric_consistency.py
· tools/check_presentation.py · tools/adjudicate_findings.py (confirm flags with --help; never invent flags)
OUTPUTS (in PAPER_DIR) — artifact_manifest.json · claims.json · <skill>.findings.json (+ *.deterministic.findings.json)
· adversarial-case-builder.memo.md · report.json · REPORT.md · .aris/traces/<skill>/<date>_run<NN>/
What ships with it
9 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 · -406 lines bcba62b196b3
- 1mo ago Changed · -193 tokens per session 119dba519939
- 1mo ago Changed 5f001fda1403
- 1mo ago Changed affcf064f6f1
- 1mo 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 (18 stars, last pushed yesterday), licensed MIT. It adds 82 tokens to every session and 9,225 once invoked, about $0.0003 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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