본문으로 건너뛰기
cccskills
무료GitHub에 공개

integrity-forensics

Check a paper's numerical consistency using fixed rules, then record blocking or warning decisions and outstanding findings. The workflow preserves a traceable correction history, while explicitly leaving broader semantic review unavailable in its Codex mode.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

원문원문 설명 보기

Run the Anti-Autoresearch integrity-forensics DETERMINISTIC slice (numeric core + rules-only reporter) against a paper via a SHA-pinned thin launcher, then convert the verdict into a typed policy gate (BLOCK/WARN/NO_NEW_BLOCKER) and an append-only obligations ledger. Codex-native limitation: upstream ships no Codex-native auditor pack, so the full nine-dimension semantic sweep requires a Claude Code session — this pack runs the honestly-scoped deterministic-only mode (it can flag, it can never say CLEAN). Use when user says "integrity forensics", "forensic audit this paper", "投稿前自查诚信".

설치 방법 보기

이럴 때 유용합니다

  • Check numerical consistency before submitting a paper
  • Record audit findings and required corrections
  • Detect outdated audit reports after paper changes
  • Separate automated checks from reviews requiring human judgment

포함된 파일(1)

  • SKILL.md6.0 KB

SKILL.md(원문)

설치하기 전에 에이전트에게 전달되는 지시 내용을 확인할 수 있습니다.

Integrity Forensics — thin launcher (Codex-native: deterministic slice)

Audit target: $ARGUMENTS

Same launcher doctrine as the mainline skill: SHA-pin, upstream eval-gate validation per pin, delegate unchanged, no vendoring, no forking, no reviewer knobs. The one Codex-native difference: upstream's nine auditor skills are Claude-Code contracts, so this pack runs upstream's deterministic-only mode — the numeric forensic core (GRIM / GRIMMER / statcheck / delta arithmetic) plus the rules-only reporter with an all-review_unavailable coverage map. That mode is honestly scoped by upstream: it can raise HARD/SOFT flags; it can NEVER return CLEAN_GIVEN_EVIDENCE. Translating upstream's reviewer calls into spawn_agent would REWRITE an upstream contract — forbidden.

Constants

  • ANTI_AR_REPO = https://github.com/wanshuiyin/Anti-Autoresearch.git
  • ANTI_AR_COMMIT = b47af6f983b38347b6d2110379e266400597cf66 — never tracks HEAD; bumping is a reviewed change (mainline Pin-bump checklist).
  • CLONE_DIR = ~/.aris/anti-autoresearch — host-neutral. An older clone at ~/.claude/anti-autoresearch is unused; move it and its .aris_eval_ok_* receipt to keep an offline deterministic-only run working — this pack's own mode — otherwise delete it whenever convenient.
  • NO REVIEWER KNOBS — and no — effort: mapping onto upstream settings.

Step 0 — Bootstrap the pin (identical to mainline)

CLONE_DIR="$HOME/.aris/anti-autoresearch"
ANTI_AR_COMMIT="b47af6f983b38347b6d2110379e266400597cf66"
mkdir -p "$HOME/.aris"
if [ ! -d "$CLONE_DIR/.git" ]; then
    git clone --no-checkout https://github.com/wanshuiyin/Anti-Autoresearch.git "$CLONE_DIR"
fi
git -C "$CLONE_DIR" cat-file -e "$ANTI_AR_COMMIT^{commit}" 2>/dev/null \
    || git -C "$CLONE_DIR" fetch -q origin
git -C "$CLONE_DIR" checkout -qf "$ANTI_AR_COMMIT" || { echo "FATAL: cannot checkout pin"; exit 1; }
# pristine tree at the pin — local tampering (incl. nested-repo injections;
# hence double -f) must not run under the pin's name; verify, don't assume
git -C "$CLONE_DIR" reset --hard -q "$ANTI_AR_COMMIT" || { echo "FATAL: reset failed"; exit 1; }
git -C "$CLONE_DIR" clean -ffdxq || { echo "FATAL: clean failed"; exit 1; }
[ -z "$(git -C "$CLONE_DIR" status --porcelain)" ] || { echo "FATAL: tree not pristine"; exit 1; }
# marker OUTSIDE the clone (a marker inside a tamperable tree proves nothing)
MARKER="${CLONE_DIR}.aris_eval_ok_${ANTI_AR_COMMIT}"
if [ ! -f "$MARKER" ]; then
    ( cd "$CLONE_DIR" && python3 eval/run_eval.py ) || {
        echo "FATAL: upstream eval gate FAILED at pin — refusing an unvalidated pin"; exit 1; }
    touch "$MARKER"
fi

Step 1 — Delegate: upstream deterministic-only mode, unchanged

Open $CLONE_DIR/workflows/anti-autoresearch/SKILL.md and follow its deterministic-only path (its own documented degraded mode): Step 0 ingest → Step 1 evidence ledger → deterministic auditors → adjudication with the generated all-review_unavailable coverage map. Wrapper rules: run every upstream bash block with cd "$CLONE_DIR" (upstream self-locates via git rev-parse --show-toplevel); refer to the paper by ABSOLUTE path; never rewrite upstream outputs.

Expected outcome: report.json whose verdict is HARD_FLAGS / SOFT_FLAGS / REVIEW_UNAVAILABLE — by construction never CLEAN_GIVEN_EVIDENCE.

Step 2 — Typed gate + obligations

Resolve forensics_gate.py via the canonical helper chain (shared-references/integration-contract.md §2, Policy A), then:

python3 "$GATE_HELPER" evaluate --report "$PAPER_DIR/report.json" --paper-dir "$PAPER_DIR" \
    --anti-ar-commit "$ANTI_AR_COMMIT" --executor-model "codex-gpt-6-astra"

Policy: HARD_FLAGS → BLOCK · REVIEW_UNAVAILABLE → BLOCK (which a deterministic-only run reports whenever it found no flags — the semantic dimensions never ran, so nothing may wave the paper through) · SOFT_FLAGS → WARN. The gate records same-family proposal provenance for a Codex executor — informational: this gate only raises flags, it grants nothing. The downstream preflight is ONE command: python3 "$GATE_HELPER" fresh --paper-dir "$PAPER_DIR" --anti-ar-commit "$ANTI_AR_COMMIT" — exit 0 ⟺ produced at the current pin ∧ gate exists ∧ paper unchanged since ∧ gate matches the current ledger ∧ decision pass-capable (WARN/NO_NEW_BLOCKER), where the decision is RE-computed from the sha-verified archived report + live ledger (the stored token is display, not authority). Any ledger mutation deletes the standing gate.json, and evaluate refuses a report older than any paper file — neither a stale pass nor a stale report can be replayed.

Step 3 — Fix what it found

Identical obligations discipline to the mainline skill: append-only ledger, UNRESOLVED_DISAPPEARANCE on vanished-but-unresolved findings, typed + hashed resolve receipts (corrected-from-results | claim-narrowed | claim-withdrawn | citation-replaced; --verified-by must be typed provenance — human:<name> / checker:<tool> / cross-family-review:<thread-id> — and the evidence file is RE-hashed on every later gate), human-only waive (never a resolution), and The One Forbidden Loop: never "edit → re-sweep → repeat until it stops flagging". Numeric obligations route to the result files; the rest to the matching audit skill or the human.

리뷰

아직 리뷰가 없습니다. 사용해 본 소감을 남겨 주세요.

댓글

로그인 없이 쓸 수 있습니다. 사용 후기, 질문, 작동하지 않은 환경 등을 편하게 남겨 주세요.

아직 댓글이 없습니다. 첫 댓글을 남겨 보세요.

보내면 바로 공개됩니다. 이메일 주소나 전화번호 같은 개인 정보는 쓰지 마세요. URL은 2개까지입니다.

0 / 1,000자

이 양식은 reCAPTCHA로 보호되며 Google 개인정보처리방침 및 서비스 약관이 적용됩니다.

같은 저장소의 스킬

Plan ablation studies, experiments that remove or replace parts of a machine learning method to test their contribution. Define reviewer questions, expected outcomes, priorities, execution order, and compute estimates, then implement experiments and record findings.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

  • Testing the contribution of individual method components
  • Planning additional experiments before paper submission
  • Prioritizing experiments within a GPU budget
wanshuiyin/Auto-claude-code-research-in-sleep1.8만2026년 10월 22일 업데이트

Plan and run ablation studies, experiments that remove or replace parts of a method to test their contribution. Organize reviewer questions, priorities, expected outcomes, and compute costs, then record results and findings.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

  • Test how much each component contributes
  • Plan experiments that address reviewer questions
  • Prioritize comparisons within a compute budget
wanshuiyin/Auto-claude-code-research-in-sleep1.8만2026년 10월 22일 업데이트

alphaxiv

무료

Understand a single arXiv paper through an AlphaXiv summary, with full text and LaTeX source available when needed. Use it to identify key findings or ask specific questions about methods, experiments, and equations.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

  • Get a quick overview of a paper from its URL
  • Check a paper's methods and experimental results
  • Ask about equations, proofs, or appendix details
wanshuiyin/Auto-claude-code-research-in-sleep1.8만2026년 10월 22일 업데이트

Compare machine learning experiment results from JSON or CSV files. Calculate improvements over a baseline, summarize variation across repeated runs, identify trends and unusual results, and suggest experiments to test possible explanations.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

  • Compare model performance across experimental conditions
  • Check variation across runs with different random seeds
  • Identify trends as a parameter changes
wanshuiyin/Auto-claude-code-research-in-sleep1.8만2026년 10월 22일 업데이트

arxiv

무료

Search arXiv papers by topic or paper ID, review authors and abstracts, and summarize contributions stated in the abstracts. Download selected papers or all search results as PDFs to build a local paper library.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

  • Find arXiv papers on a research topic
  • Retrieve details for a known arXiv paper ID
  • Download all PDFs from a set of search results
wanshuiyin/Auto-claude-code-research-in-sleep1.8만2026년 10월 22일 업데이트

Improve a compiled paper through two rounds of external model review, source edits, and PDF rebuilding. Check claims against evidence, resolve inconsistencies, and refine figures and layout, with optional checkpoints and restrictions on which edits are allowed.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

  • Revising a generated paper before submission
  • Correcting mismatches between claims and evidence
  • Improving notation, figures, tables, and layout
wanshuiyin/Auto-claude-code-research-in-sleep1.8만2026년 10월 22일 업데이트

wanshuiyin의 스킬 모두 보기

이 스킬의 문제 신고