adversarial-case-builder

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Synthesize the single strongest EVIDENCE-BOUND reviewer case to reject a paper, built ONLY from the evidence ledger (claims.json) + the other auditors' confirmed findings — never free-floating LLM critique. Two fresh cross-model codex threads: an attack writes the ~200-word rejection paragraph (every accusation tagged to an existing claim_id/finding_id), a defense decomposes it and rules each point against the anchored evidence. MEMO-ONLY: emits adversarial-case-builder.memo.md (fed to the adjudicator via --memo) and carries NO verdict weight — tools/adjudicate_findings.py lists it in ZERO_WEIGHT_SKILLS and caps it at info. Honest-null allowed (the paper may survive). Run LAST. Detect-only. Adapted from ARIS kill-argument. Triggers: "adversarial case", "strongest objection", "rejection memo", "kill argument", "最强拒稿点".

AI & Automation 153 stars 8 forks Updated 2 days ago MIT

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# 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 > `in...

Details

Author
wanshuiyin
Repository
wanshuiyin/Anti-Autoresearch
Created
2 months ago
Last Updated
2 days ago
Language
Python
License
MIT

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evidence-ledger

Build the deterministic evidence ledger (artifact_manifest.json + claims.json) that every other Anti-Autoresearch auditor reads. One pass inventories artifacts, derives the observability level (L0 PDF-only / L1 +LaTeX / L2 +repo+results) by fixed rule, and extracts span-anchored, hashed, checkable claims (numbers, comparisons, scope, method, baselines, citations, captions, table cells) into claims.json. An OPTIONAL additive cross-model pass ADDS span-anchored semantic claims — method, theorem statements with their assumptions, definitions, proof/derivation steps and equations, scope, baselines, conclusions, the motivation span, and reproducibility-artifact references (the proof, derivation, and structure anchors the family B/D/G auditors need) — it never invents a number, emits a finding, or computes a verdict. Run FIRST, before any audit skill. Triggers: "build the ledger", "extract claims", "prep for integrity audit", "evidence ledger", "建证据账本".

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AI & Automation Listed

kill-argument

Adversarial attack-defense exercise on a near-final paper - a fresh reviewer writes the single strongest 200-word rejection memo, a second fresh reviewer defends point-by-point, and an adjudicator classifies each attack point as answered / partially answered / still unresolved. Use once before submission after standard reviews have stabilized, or when the user says kill argument, hostile review, or asks what would make an area chair reject this paper.

2 Updated 1 months ago
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