adversarial-case-builder

adversarial-case-builder is a skill for Claude Code from wanshuiyin/Anti-Autoresearch. It costs 194 tokens per session (11,691 once invoked), scanned A, original, MIT.

A review workflow that builds one paper-rejection argument from a record of verified claims and confirmed audit findings.

In plain words
What is it for?
Use it after the evidence ledger and auditor checks are complete. It produces a memo that states and defends the strongest evidence-based reason to reject a research paper.
Why use it?
It prevents unsupported criticism by requiring every objection to be tied to evidence already collected by the review process.

Skill for Claude Code

Written for Claude Code: allowed-tools in frontmatter. Also seen: mentions subagents; mentions Codex.

Good fit Use it after the evidence ledger and auditor checks are complete. It produces a memo that states and defends the strongest evidence-based reason to reject a research paper.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/wanshuiyin/anti-autoresearch/adversarial-case-builder
Install

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.

Any agent
npx skills add wanshuiyin/Anti-Autoresearch --skill adversarial-case-builder
Clone the repo
git clone --depth 1 https://github.com/wanshuiyin/Anti-Autoresearch

Made for: Claude Code.

Wrote 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.

agentmods badge for adversarial-case-builder

README.md
[![agentmods](https://agentmods.dev/badge/skills/wanshuiyin/anti-autoresearch/adversarial-case-builder/github.svg)](https://agentmods.dev/skills/wanshuiyin/anti-autoresearch/adversarial-case-builder)
Your own site
<a href="https://agentmods.dev/skills/wanshuiyin/anti-autoresearch/adversarial-case-builder"><img src="https://agentmods.dev/badge/skills/wanshuiyin/anti-autoresearch/adversarial-case-builder/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.

agentmods 80×15 button for adversarial-case-builder

Your own site · 80×15
<a href="https://agentmods.dev/skills/wanshuiyin/anti-autoresearch/adversarial-case-builder"><img src="https://agentmods.dev/badge/skills/wanshuiyin/anti-autoresearch/adversarial-case-builder.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 194 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 11,691 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe. Third-party audits
  • NVIDIA SkillSpector pass 7 Sept 2026
How audits are shown
Origin original No closer match found in the catalogue.
Token cost

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.

ModelPer sessionOnce invoked
Fable 5.1 $0.00194 $0.11691
Opus 5 $0.00097 $0.05846
Sonnet 5 $0.00039 $0.02338
Haiku 4.5 $0.00019 $0.01169

Measured 12d ago against content hash d47af199de44, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-11, from the pricing page.

Security

Grade A, and why

adversarial-case-builder 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.

Origin

Copies of this mod

1 near-identical copy found in the catalogue:

skills/adversarial-case-builder/SKILL.md · 746 lines

How it starts

The opening of the file, as written. The whole thing — 746 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Adversarial Case Builder — the strongest evidence-bound objection

Build the single strongest evidence-bound case to reject $ARGUMENTS, then defend it point-by-point. Emit adversarial-case-builder.memo.md. Run LAST, AFTER /evidence-ledger (so claims.json exists) and AFTER the auditor skills (so the merged *.findings.json exist).

🔒 Do not wrap this skill in /loop, /schedule, or CronCreate. It runs LAST and synthesizes the ledger + the other auditors' findings into one memo. Even though it is memo-only (the adjudicator caps it at info, so it adds no verdict weight), the no-new-signal cadence rule still applies: its output changes only when the ledger / the findings / the paper change, never with the wall clock. Schedule the work that precedes it — ledger + auditors done → run this once. (Mirrors ARIS's external-cadence doctrine.)

Adapted from ARIS kill-argument, with one deliberate downgrade: memo-only. In a forensics pipeline the headline-attack is most useful as a synthesis of already-anchored evidence, not a free-floating LLM critique — that free-floating mode is exactly the "LLM slop grading LLM slop" failure this repo exists to refuse. So here every attack point must cite an existing ledger claim_id or finding_id, and the skill never emits verdict-bearing findings: tools/adjudicate_findings.py lists adversarial-case-builder in ZERO_WEIGHT_SKILLS and caps anything from it at info. The deterministic adjudicator owns the verdict; this skill owns the memo.

Why this exists

The standard auditors (consistency-audit, citation-forensics, …) fan out and each flags discrepancies in its own dimension. They produce a balanced list — each discrepancy at its own severity, none committing to "this is the one that sinks the paper." That misses a specific failure mode: the single most damaging paragraph a senior area chair would write in a rejection. A balanced reviewer lists "scope-overclaim" as one major among several and never commits; an adversarial reviewer must commit — their whole job is to convince the AC to reject in ~200 words.

Read the full file on GitHub · 746 lines

Changes

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.

  1. 12d ago First seen · 746 lines · 194 tokens per session scan A d47af199de44

Subscribe to this mod's changes

adversarial-case-builder is a skill published in the GitHub repository wanshuiyin/Anti-Autoresearch (153 stars, last pushed 2d ago), licensed MIT. It adds 194 tokens to every session and 11,691 once invoked, about $0.0010 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 2026-08-30.

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