Paper Planning
EvoScientist/EvoSkills
Guides pre-writing planning for academic papers with 4 structured steps: story design (task-challenge-insight-contribution-advantage), experiment planning (comparisons + ablations), figure design…
Run the Anti-Autoresearch integrity-forensics sweep (span-anchored evidence ledger → GPT auditors propose findings → a rules-only reporter that lists every proposal with what the auditor said about…
$ npx skills add wanshuiyin/Auto-claude-code-research-in-sleep --skill integrity-forensics -a claude-codeProject install by default; add -g for ~/.claude/skills/.
$ gh skill install wanshuiyin/Auto-claude-code-research-in-sleep integrity-forensics --agent claude-codeProject scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).
$ git clone --depth 1 https://github.com/wanshuiyin/Auto-claude-code-research-in-sleep.git skills-src && mkdir -p .claude/skills && cp -r skills-src/skills/integrity-forensics .claude/skills/integrity-forensics && rm -rf skills-srcUse ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.
Claude Code skills documentation · loads skills from .claude/skills/
Install the "integrity-forensics" agent skill from https://github.com/wanshuiyin/Auto-claude-code-research-in-sleep/tree/main/skills/integrity-forensics into .claude/skills/integrity-forensics/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "integrity-forensics", then confirm the skill loads.Claude Code copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$skill-installer install https://github.com/wanshuiyin/Auto-claude-code-research-in-sleep/tree/main/skills/integrity-forensicsType this inside Codex. $skill-installer <name> installs a curated skill from openai/skills. The installer writes to $CODEX_HOME/skills (default ~/.codex/skills). Restart Codex if the skill does not show up.
$ npx skills add wanshuiyin/Auto-claude-code-research-in-sleep --skill integrity-forensics -a codexProject install goes to .agents/skills/; add -g for ~/.codex/skills/.
$ gh skill install wanshuiyin/Auto-claude-code-research-in-sleep integrity-forensics --agent codexProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/wanshuiyin/Auto-claude-code-research-in-sleep.git skills-src && mkdir -p .agents/skills && cp -r skills-src/skills/integrity-forensics .agents/skills/integrity-forensics && rm -rf skills-srcUse ~/.agents/skills/ instead of .agents/skills for a personal install.
Codex skills documentation · loads skills from .agents/skills/
Install the "integrity-forensics" agent skill from https://github.com/wanshuiyin/Auto-claude-code-research-in-sleep/tree/main/skills/integrity-forensics into .agents/skills/integrity-forensics/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "integrity-forensics", then confirm the skill loads.Codex copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ npx skills add wanshuiyin/Auto-claude-code-research-in-sleep --skill integrity-forensics -a cursorProject install goes to .agents/skills/; add -g for ~/.cursor/skills/.
$ gh skill install wanshuiyin/Auto-claude-code-research-in-sleep integrity-forensics --agent cursorProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/wanshuiyin/Auto-claude-code-research-in-sleep.git skills-src && mkdir -p .cursor/skills && cp -r skills-src/skills/integrity-forensics .cursor/skills/integrity-forensics && rm -rf skills-srcUse ~/.cursor/skills/ instead of .cursor/skills for a personal install.
Cursor skills documentation · loads skills from .cursor/skills/, .agents/skills/, .claude/skills/, .codex/skills/
Install the "integrity-forensics" agent skill from https://github.com/wanshuiyin/Auto-claude-code-research-in-sleep/tree/main/skills/integrity-forensics into .cursor/skills/integrity-forensics/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "integrity-forensics", then confirm the skill loads.Cursor copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ gemini skills install https://github.com/wanshuiyin/Auto-claude-code-research-in-sleep.git --path skills/integrity-forensics--scope user (default) or --scope workspace; --path is the subfolder of the repo that holds the skill; --consent skips the security confirmation prompt.
$ npx skills add wanshuiyin/Auto-claude-code-research-in-sleep --skill integrity-forensics -a gemini-cliProject install goes to .agents/skills/; add -g for ~/.gemini/skills/.
$ gh skill install wanshuiyin/Auto-claude-code-research-in-sleep integrity-forensics --agent gemini-cliProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/wanshuiyin/Auto-claude-code-research-in-sleep.git skills-src && mkdir -p .gemini/skills && cp -r skills-src/skills/integrity-forensics .gemini/skills/integrity-forensics && rm -rf skills-srcUse ~/.gemini/skills/ instead of .gemini/skills for a personal install, then run /skills reload.
Gemini CLI skills documentation · loads skills from .gemini/skills/, .agents/skills/
Install the "integrity-forensics" agent skill from https://github.com/wanshuiyin/Auto-claude-code-research-in-sleep/tree/main/skills/integrity-forensics into .gemini/skills/integrity-forensics/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "integrity-forensics", then confirm the skill loads.Gemini CLI copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ gh skill install wanshuiyin/Auto-claude-code-research-in-sleep integrity-forensicsInstalls for Copilot at project scope by default; add --scope user for a personal install. Preview a skill first with gh skill preview. Needs GitHub CLI 2.90.0 or later (public preview).
$ npx skills add wanshuiyin/Auto-claude-code-research-in-sleep --skill integrity-forensics -a github-copilotProject install goes to .agents/skills/; add -g for ~/.copilot/skills/.
$ git clone --depth 1 https://github.com/wanshuiyin/Auto-claude-code-research-in-sleep.git skills-src && mkdir -p .github/skills && cp -r skills-src/skills/integrity-forensics .github/skills/integrity-forensics && rm -rf skills-srcUse ~/.copilot/skills/ instead of .github/skills for a personal install. Commit .github/skills so cloud agent and code review can use it.
GitHub Copilot skills documentation · loads skills from .github/skills/, .claude/skills/, .agents/skills/
Install the "integrity-forensics" agent skill from https://github.com/wanshuiyin/Auto-claude-code-research-in-sleep/tree/main/skills/integrity-forensics into .github/skills/integrity-forensics/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "integrity-forensics", then confirm the skill loads.GitHub Copilot copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ npx skills add wanshuiyin/Auto-claude-code-research-in-sleep --skill integrity-forensics -a opencodeOpenCode documents no install command of its own. Project install goes to .agents/skills/; add -g for ~/.config/opencode/skills/.
$ gh skill install wanshuiyin/Auto-claude-code-research-in-sleep integrity-forensics --agent opencodeProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/wanshuiyin/Auto-claude-code-research-in-sleep.git skills-src && mkdir -p .opencode/skills && cp -r skills-src/skills/integrity-forensics .opencode/skills/integrity-forensics && rm -rf skills-srcUse ~/.config/opencode/skills/ instead of .opencode/skills for a personal install.
OpenCode skills documentation · loads skills from .opencode/skills/, .claude/skills/, .agents/skills/
Install the "integrity-forensics" agent skill from https://github.com/wanshuiyin/Auto-claude-code-research-in-sleep/tree/main/skills/integrity-forensics into .opencode/skills/integrity-forensics/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "integrity-forensics", then confirm the skill loads.OpenCode copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
integrity-forensicsRun the Anti-Autoresearch integrity-forensics sweep (span-anchored evidence ledger → GPT auditors propose findings → a rules-only reporter that lists every proposal with what the auditor said about…
Integrity Forensics is an agent skill from wanshuiyin/Auto-claude-code-research-in-sleep. Run the Anti-Autoresearch integrity-forensics sweep (span-anchored evidence ledger → GPT auditors propose findings → a rules-only reporter that lists every proposal with what the auditor said about it) against a paper via a SHA-pinned thin launcher — then convert the verdict into a typed policy gate (BLOCK/WARN/NONEWBLOCKER) and an append-only obligations ledger. Use when user says "integrity forensics", "forensic audit this paper", "投稿前自查诚信", "审这篇论文的诚信", or says "anti-autoresearch" when the upstream repo's own…
Its SKILL.md is about 4.2k tokens, which your agent loads only when the skill is triggered. It is a single SKILL.md file with no bundled scripts.
It sits in Research & Science, covering Autonomous loops, Scientific writing and Peer review. The repository describes itself as: ARIS ⚔️ (Auto-Research-In-Sleep) — Lightweight Markdown-only skills for autonomous ML research: cross-model review loops, idea discovery, and experiment automation. No framework… The licence is MIT.
4 steps, taken from the step headings in SKILL.md.
Read from SKILL.md and the folder at commit 26b95cf. It shows what the files ask for, not the result of running them.
Pre-approves these tools, so the agent can use them without asking each time:
Bash(*)ReadWriteGrepGlobmcp__codex__codexFrom allowed-tools in the SKILL.md frontmatter.
Shell commands in SKILL.md call:
gitpython3From the folder's file list and the shell code blocks in SKILL.md.
Hosts in commands or code, which the agent is likely to contact:
github.comFrom URLs in SKILL.md, links to its own repository left out.
Names no API keys, tokens, secrets or passwords.
From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.
Integrity Forensics loads about 4.2k tokens when it runs. Until then it costs about 173 tokens; SKILL.md has 1,719 words of instructions outside code blocks.
Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.
The automated check noted patterns worth knowing about, such as sudo or a known installer.
allowed-tools: Bash(*), Read, Write, Grep, Glob, mcp__codex__codexAutomated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); files beside SKILL.md are not scanned.
The full file from wanshuiyin/Auto-claude-code-research-in-sleep at commit 26b95cf, republished under its MIT licence (© wanshuiyin). 1,719 words, ~4,243 tokens.
.claude/skills/integrity-forensics/SKILL.md (or your agent's skills folder).Audit target: $ARGUMENTS
What this is. ARIS generates papers; Anti-Autoresearch is its outward-pointed dual — reviewer-side integrity forensics (46 patterns across 8 families, deterministic GRIM/GRIMMER/statcheck core, span-anchored claims, a rules-only reporter that summarizes rather than adjudicates). This skill is a thin launcher: it pins an upstream commit, validates the pin with the upstream eval gate, delegates execution unchanged, and post-processes the verdict into ARIS's policy vocabulary. It vendors nothing and forks nothing.
🔁 Cadence fence (
shared-references/external-cadence.md): this skill is verdict-bearing decision support. Do not wrap it in/loop//schedule— and NEVER as "iterate edits until it stops flagging" (see The One Forbidden Loop below).
https://github.com/wanshuiyin/Anti-Autoresearch.gitb47af6f983b38347b6d2110379e266400597cf66 — the SHA-pin.
The launcher NEVER tracks upstream HEAD; bumping this constant is a reviewed
change (see Pin-bump checklist).~/.aris/anti-autoresearch — the pinned working copy. Host-neutral
on purpose: ARIS also runs on DeepSeek Harness, Codex CLI, Cursor, Trae,
Antigravity and Copilot CLI, where ~/.claude/ would name an installation the
user does not have. An older clone at ~/.claude/anti-autoresearch is unused;
move it and its .aris_eval_ok_* receipt only to keep an offline
deterministic-only run working, otherwise delete it whenever convenient.— effort: onto upstream settings. The
pinned upstream runs exactly what it pins (gpt-6-astra + xhigh, its own
design decision). Overriding upstream review policy from a launcher would
create a second, unauditable configuration surface.forensics_gate.py — resolved via the canonical chain
(shared-references/integration-contract.md §2): .aris/tools/ →
tools/ → $ARIS_REPO/tools/ → $ARIS_REPO/tools/ via ~/.aris/repo.
Failure policy A (required): if it cannot be resolved at
assurance: submission, STOP — never improvise the gate.CLONE_DIR="$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 "$CLONE_DIR"
fi
# fetch ONLY if the pin isn't already present — a cached, validated pin works offline
git -C "$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 pinned commit $ANTI_AR_COMMIT"; exit 1; }
# Force a PRISTINE tree at the pin — local tampering with the clone (edited
# adjudicator, injected module, even one hidden inside a NESTED git repo,
# which single-f clean skips) must not survive bootstrap and run under the
# official pin's name. Every step is checked; then the tree is verified.
git -C "$CLONE_DIR" reset --hard -q "$ANTI_AR_COMMIT" || {
echo "FATAL: reset to pin failed"; exit 1; }
git -C "$CLONE_DIR" clean -ffdxq || {
echo "FATAL: clean failed"; exit 1; }
[ -z "$(git -C "$CLONE_DIR" status --porcelain)" ] || {
echo "FATAL: clone is not pristine after reset+clean — refusing to run"; exit 1; }
# One-time-per-pin validation: the upstream eval gate (8 injected-defect
# classes, 100% recall + zero clean false positives) must PASS before this
# pin is allowed to produce a verdict. NEVER skip; NEVER proceed on failure.
# The marker lives OUTSIDE the clone: a marker inside a tamperable tree proves
# nothing (and `git clean` above would erase it, forcing re-eval every run).
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 $ANTI_AR_COMMIT — refusing to"
echo " use an unvalidated forensics pin for verdicts."; exit 1; }
touch "$MARKER"
fi
echo "anti-autoresearch pinned at $ANTI_AR_COMMIT (eval gate: validated)"Open and follow $CLONE_DIR/workflows/anti-autoresearch/SKILL.md end to
end on the target. Two wrapper rules — the ONLY things this launcher adds:
git rev-parse --show-toplevel.
Run every upstream bash block with cd "$CLONE_DIR" first — ALWAYS the cd,
never just an exported ROOT (upstream blocks re-derive ROOT themselves
and would overwrite it) — and refer to the paper by absolute path,
otherwise upstream resolves ROOT to the ARIS repo and finds the wrong
Python spine.approval-policy: never + sandbox: read-only
(session hygiene; upstream already specifies fresh-thread-per-dimension,
serial execution, and its own model pins — do not alter them).Everything else — the evidence ledger, coverage.json state machine, the nine
auditor dimensions, the refutation pass, the deterministic summary — is
upstream's contract. Never rewrite, soften, or re-map its outputs
(report.json + REPORT.md, verdict ∈ CLEAN_GIVEN_EVIDENCE / SOFT_FLAGS /
HARD_FLAGS / REVIEW_UNAVAILABLE). The observability level (L0/L1/L2) is
whatever upstream derives from the artifacts present — do not promise L2.
# Resolve $GATE_HELPER via the canonical chain (integration-contract §2), then
# ONE atomic call (update + gate in a single locked transaction — the gate only
# ever speaks for the report the ledger has folded, sha-bound):
python3 "$GATE_HELPER" evaluate --report "$PAPER_DIR/report.json" --paper-dir "$PAPER_DIR" \
--anti-ar-commit "$ANTI_AR_COMMIT" --executor-model "<this pipeline's executor>"
# exit 0 = WARN / NO_NEW_BLOCKER · exit 1 = BLOCKThe gate translates the verdict into policy WITHOUT re-labeling it:
| upstream verdict | policy |
|---|---|
HARD_FLAGS | BLOCK — an auditor proposed something critical and it is on the table for you to read; never "the machine found fraud" |
REVIEW_UNAVAILABLE | BLOCK — an incomplete sweep cannot wave a paper through |
SOFT_FLAGS | WARN — human disposition. Read the never-ran list too: the upstream verdict folds incompleteness in only when it would otherwise be clean, so a WARN can sit on top of a sweep where verdict-bearing dimensions never ran. evaluate and fresh both print those dimensions |
CLEAN_GIVEN_EVIDENCE | NO_NEW_BLOCKER — never called PASS or accepted: it means "no flag found in the evidence at hand", not an acquittal |
| anything else | BLOCK (fail closed) |
plus: any OPEN critical obligation → BLOCK; any OPEN obligation → at least
WARN; a closed-without-receipt or unknown-status ledger entry → BLOCK (a
hand-edited "status": "RESOLVED" does not open the gate).
gate.json also records a paper_fingerprint (sha over the paper's compile
inputs AND deliverables — .tex/.bib/.sty/.cls/figures/PDF). The
downstream preflight is ONE command:
python3 "$GATE_HELPER" fresh --paper-dir "$PAPER_DIR" --anti-ar-commit "$ANTI_AR_COMMIT"
— exit 0 ⟺ the gate was produced at the CURRENT pin ∧ a gate
exists ∧ nothing in the paper changed after it ∧ the gate matches the current
obligations ledger ∧ the decision — re-computed from the sha-verified
archived report (last_report.json) + the live ledger, never read from the
gate's stored token — is pass-capable (WARN / NO_NEW_BLOCKER). Anything
else — missing gate, post-gate edit or recompile, unbound ledger or archive,
recompute mismatch, BLOCK, unknown token — exits 1: re-run the sweep +
evaluate. Every ledger mutation (update/resolve/waive) deletes the
standing gate.json, so an interrupted run can never leave a stale pass; and
evaluate refuses a report OLDER than any paper file (a stale report cannot
be folded onto text it never audited). Run evaluate immediately after the
sweep, before touching any paper file.
The gate artifact also records honest provenance: upstream's auditors are
GPT-family, so for a Claude executor the findings carry cross-family
proposal provenance; for a Codex executor they are same-family. Either
way this gate only raises flags — it has no acceptance to grant, so the
distinction is informational, not a loophole.
Every OPEN obligation gets DISPOSITIONED — fixed, or explicitly waived. Upstream now
reports every proposal an auditor made rather than deciding which ones do not count, so
expect more obligations than a pre-2026-08 sweep opened, and expect some of them to be
proposals you disagree with. waive is a first-class, expected outcome — "a model
proposed this and I, the human, judge it wrong" is a normal disposition here, not a last
resort. Weigh each one against the report's columns: Anchored, Observability,
FP-risk, Surface, Ext-check.
For the ones that are real, use the right door:
| Finding family | Repair route |
|---|---|
| A — numeric self-consistency | recompute from the RESULT FILES (/paper-claim-audit evidence chain); fix the number, not the sentence |
| D — experiment integrity | back to /experiment-audit / rerun |
| E — citations | /citation-audit KEEP/FIX/REPLACE machinery |
| G — proof & derivation | /proof-checker's fix loop |
| B / C / H — scope, baselines, eval design | science-level: feed the finding to /auto-review-loop as reviewer INPUT, or to the human |
| AIS / advisory (zero-weight) | optional context for /auto-paper-improvement-loop; never gates |
Close each obligation explicitly — the receipt is typed and hashed:
python3 "$GATE_HELPER" resolve --paper-dir "$PAPER_DIR" --obligation-id <id> \
--fix-type corrected-from-results|claim-narrowed|claim-withdrawn|citation-replaced \
--evidence <path-to-the-ground-truth-that-backs-the-fix> \
--verified-by "human:<name>" | "checker:<tool>" | "cross-family-review:<thread-id>"
# or, with HUMAN sign-off only:
python3 "$GATE_HELPER" waive --paper-dir "$PAPER_DIR" --obligation-id <id> \
--approver "human:<name>" --reason "<why this stands as-is>"Rules the ledger enforces mechanically (tests/test_forensics_gate.py):
UNRESOLVED_DISAPPEARANCE — rewording the span is not a fix;claim-withdrawn is an honest fix (deleting an unsupported claim is a
legitimate resolution — with the deletion diff as evidence);fix_type label is a receipt, not a verdict — closure of a
critical needs a family checker, a fresh cross-family review, or a human
(--verified-by requires TYPED provenance and is recorded; naming a human
who did not approve is a false record with a permanent paper trail);resolve/waive (like update) invalidate the standing gate.json —
finish Step 3 by re-running the sweep + evaluate, so the gate that
downstream preflights read reflects the post-fix state.Never run "edit → re-sweep → repeat until CLEAN". That objective function teaches the editor to defeat the detector — deleting an anchored span kills a flag faster than fixing the number, and the result is a paper laundered against its own audit. The re-run after fixes exists to confirm the DISCREPANCY is gone (and to catch new ones); the obligations ledger — not the verdict — decides whether the gate opens.
fresh never trusts a stored token).human: / checker: / cross-family-review: labels are
accountability, not authentication: a false label is an explicit,
permanent false record..aris/ artifacts consistently with
shell access has owner power (they could delete the directory outright).
The gate defends against the sloppy or corner-cutting executor and against
honest crashes/races/resumes — not against the machine's owner.ANTI_AR_COMMIT; delete no markers (the eval gate re-runs
automatically for the new SHA).schemas/report.schema.json + verdict vocabulary against
the gate's policy table; extend tools/forensics_gate.py BEFORE bumping if
they moved.fresh
rejects every stored gate.json at the old pin with PIN_MISMATCH, so a
bump already forces a re-sweep for everyone — bundle upstream changes behind
ONE bump rather than two, or the re-sweep cost is paid twice.2026-08 bump (
98a75fc) — expect more open obligations. Upstream moved from adjudicating proposals to reporting them: findings its FP-risk, observability, surface and needs-external-check gates used to demote toinfonow arrive above info, so they open obligations. Nothing got worse in the paper; more of what the auditors said is now visible. Waiving a proposal you judge wrong is the expected disposition, and the report's per-finding columns (Anchored,Observability,FP-risk,Surface,Ext-check) are what you weigh. Upstream also deleted its report self-binding hashes in the same window — nothing here ever consumed them.
Upstream ships no Codex-native pack; its auditor skills are Claude-Code
contracts. A Codex-native session may run upstream's deterministic-only
mode (numeric core + adjudicator with an all-review_unavailable coverage
map — honestly scoped: it can flag, it can never say CLEAN). The full
nine-dimension sweep requires a host that can execute upstream's Claude-Code
contracts unchanged — Claude Code and the dsh-aris bundle on DeepSeek Harness
are the known ones. Translating upstream's
reviewer calls into spawn_agent on the fly is REWRITING an upstream
contract — forbidden.
Upstream saves its own per-dimension traces under the paper's
.aris/traces/. The launcher adds only the .aris/forensics/ artifacts:
gate.json (pins anti_ar_commit + report/ledger hashes + the paper-text
fingerprint), obligations.json (the append-only ledger), and
last_report.json (the sha-verified archive of the folded report that
fresh recomputes from).
© wanshuiyin, MIT. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file
Just SKILL.md in skills/integrity-forensics of wanshuiyin/Auto-claude-code-research-in-sleep.
Open the folder on GitHubat commit 26b95cf
Integrity Forensics next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.
| Skill | Stars | Used in | Tokens | Auto-check | Licence | Repo updated |
|---|---|---|---|---|---|---|
| Integrity Forensics this skillwanshuiyin/Auto-claude-code-research-in-sleep | 17k | — | ~4.2k | Automated safety check: Notes | MIT | |
| Paper PlanningEvoScientist/EvoSkills | 478 | 3 repos | ~2.4k | Automated safety check: Pass | Apache-2.0 | |
| Autodecisionharshilmathur/autodecision | 102 | — | ~2.8k | Automated safety check: Pass | MIT | |
| Scholarpeer Econfranklee16/academic-research-skills | 223 | — | ~2k | Automated safety check: Notes | None | |
| Deli Autoresearchrongxinzy/RongxinAI | 154 | — | ~3.2k | Automated safety check: Pass | AGPL-3.0 | |
| Academic Paper Writing PipelineImbad0202/academic-research-skills | 51k | — | ~16k | Automated safety check: Pass | Custom licence |
EvoScientist/EvoSkills
Guides pre-writing planning for academic papers with 4 structured steps: story design (task-challenge-insight-contribution-advantage), experiment planning (comparisons + ablations), figure design…
harshilmathur/autodecision
Auto-Decision Engine: iterative decision simulation using autoresearch principles and a persona council.
franklee16/academic-research-skills
Multi-agent peer review simulation for finance/economics manuscripts.
rongxinzy/RongxinAI
A protocol framework for long-horizon autonomous research tasks.
Imbad0202/academic-research-skills
Runs a 12-agent pipeline that plans, drafts, cites, reviews and formats academic papers, with modes for revision, rebuttals, abstracts and citation checks.
Imbad0202/academic-research-skills
Simulates a journal peer review of a manuscript with a five-seat reviewer panel, an editorial synthesizer and several review modes.
wanshuiyin/Auto-claude-code-research-in-sleep
Builds an academic conference poster as a single HTML and CSS file with measurement-based gates, real paper figures and a print-ready PDF rendered through headless Chromium.
wanshuiyin/Auto-claude-code-research-in-sleep
Runs a mathematical proof project as a stateful pipeline of run directories: a local attempt first, then a manual GPT Pro handoff package, with an optional DeepSeek audit.
wanshuiyin/Auto-claude-code-research-in-sleep
Render an ARIS Markdown / JSON artifact (IDEAREPORT, AUTOREVIEW, KILLARGUMENT, PAPERPLAN, research-wiki state, etc.) into a single-file HTML view designed for human reading.
wanshuiyin/Auto-claude-code-research-in-sleep
Audit experiment integrity before claiming results. An agent skill from wanshuiyin/Auto-claude-code-research-in-sleep.
wanshuiyin/Auto-claude-code-research-in-sleep
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…
wanshuiyin/Auto-claude-code-research-in-sleep
Generate a long-form Chinese interview-prep cheat sheet on a specific ML/LLM topic — formulas with derivations, from-scratch PyTorch code, comparison tables, and 25 高频面试题 (L1 必会 / L2 进阶 / L3 顶级 lab).
Categories
Run the Anti-Autoresearch integrity-forensics sweep (span-anchored evidence ledger → GPT auditors propose findings → a rules-only reporter that lists every proposal with what the auditor said about…. Integrity Forensics is an agent skill from wanshuiyin/Auto-claude-code-research-in-sleep. Run the Anti-Autoresearch integrity-forensics sweep (span-anchored evidence ledger → GPT auditors propose findings → a rules-only reporter that lists every proposal with what the auditor said about it) against a paper via a SHA-pinned thin launcher — then convert the verdict into a typed policy gate (BLOCK/WARN/NONEWBLOCKER) and an append-only obligations ledger.
Integrity Forensics fits situations like: user says integrity forensics; forensic audit this paper; says anti-autoresearch when the upstream repos own skills are not installed.
Run `npx skills add wanshuiyin/Auto-claude-code-research-in-sleep --skill integrity-forensics -a claude-code`. Or copy the skill folder (skills/integrity-forensics in wanshuiyin/Auto-claude-code-research-in-sleep) into .claude/skills/integrity-forensics in your project. Claude Code loads it when a task matches its description.
Run `npx skills add wanshuiyin/Auto-claude-code-research-in-sleep --skill integrity-forensics -a codex`. Or copy the skill folder (skills/integrity-forensics in wanshuiyin/Auto-claude-code-research-in-sleep) into .agents/skills/integrity-forensics in your project. Codex loads it when a task matches its description.
Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add wanshuiyin/Auto-claude-code-research-in-sleep --skill integrity-forensics -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/integrity-forensics, .gemini/skills/integrity-forensics, .github/skills/integrity-forensics and .opencode/skills/integrity-forensics in your project.
Going by SKILL.md and its folder, Integrity Forensics needs the command-line tools its instructions call (git and python3). Our summary lists: Python 3. Its frontmatter pre-approves these tools: Bash(*), Read, Write, Grep, Glob, mcp__codex__codex.
SKILL.md names 1 domain. In commands or code: github.com; the agent is likely to contact it when it follows the instructions. This is read from the text; nothing was executed.
Our automated static check of SKILL.md found notes only (pre-approves every shell command (allowed-tools: bash)), nothing it rates as a warning. It is not a guarantee. Review the folder before installing.
Integrity Forensics is published under the MIT licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.
About 4.2k tokens (SKILL.md is roughly 17k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full.
Skills that share tags, products or a category with Integrity Forensics: Paper Planning (EvoScientist/EvoSkills, 478 stars), Autodecision (harshilmathur/autodecision, 102 stars), Scholarpeer Econ (franklee16/academic-research-skills, 223 stars) and Deli Autoresearch (rongxinzy/RongxinAI, 154 stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.
wanshuiyin (a GitHub user) maintains it in wanshuiyin/Auto-claude-code-research-in-sleep, which has 17,205 GitHub stars. The repository holds 26 skills in this directory. The repository was last updated on October 7, 2026.
Source: wanshuiyin/Auto-claude-code-research-in-sleep on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.