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.
npx skills add wanshuiyin/Anti-Autoresearch --skill novelty-duplication-advisorygit clone --depth 1 https://github.com/wanshuiyin/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/wanshuiyin/anti-autoresearch/novelty-duplication-advisory)<a href="https://agentmods.dev/skills/wanshuiyin/anti-autoresearch/novelty-duplication-advisory"><img src="https://agentmods.dev/badge/skills/wanshuiyin/anti-autoresearch/novelty-duplication-advisory/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/wanshuiyin/anti-autoresearch/novelty-duplication-advisory"><img src="https://agentmods.dev/badge/skills/wanshuiyin/anti-autoresearch/novelty-duplication-advisory.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector pass
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 | $0.00284 | $0.18206 |
| Opus 5 | $0.00142 | $0.09103 |
| Sonnet 5 | $0.00057 | $0.03641 |
| Haiku 4.5 | $0.00028 | $0.01821 |
Grade A, and why
novelty-duplication-advisory 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.
Copies of this mod
1 near-identical copy found in the catalogue:
- novelty-duplication-advisory — 100% identical, 55 lines differ
How it starts
The opening of the file, as written. The whole thing — 1,107 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Novelty & Duplication Advisory — the overlap a reviewer should weigh
Lay out, for $ARGUMENTS (a paper-dir or a claims.json from /evidence-ledger), the
candidate prior-work overlap a human reviewer should weigh for two reviewer-judgment signals
— trivial combination ("standard A+B+C") and duplicate publication ("repackaged prior
work"). Retrieve candidates, map them side-by-side against the paper's ledger-anchored
contribution, and emit novelty-duplication-advisory.memo.md. Run AFTER /evidence-ledger
(so claims.json exists). This skill decides nothing — it never rules "trivial" or
"duplicate", and the deterministic adjudicator caps it at info.
🔒 Do not wrap this skill in
/loop,/schedule, orCronCreate. It retrieves external prior work once and synthesizes it into one advisory memo. Even though it is memo-only (the adjudicator caps it atinfo, so it adds no verdict weight), the no-new-signal cadence rule still applies: its output changes only when the ledger / the paper / the literature change, never with the wall clock. It is tempting to re-fire on a timer "to catch newly-posted prior work," but a wall-clock loop burns real DBLP + web + cross-model budget on every tick for a paper that has not changed. Schedule the work that precedes it — ledger built → run this once. (Mirrors ARIS's external-cadence doctrine:/loop·/scheduleare fire-control, not a judge.)
Adapted from ARIS
novelty-check, with one deliberate reframing and one deliberate downgrade. The reframing: ARISnovelty-checkasks "is MY idea novel — should I PROCEED / ABANDON?" and hands the author aScore: X/10+ a recommendation; this skill asks "here is the overlap a third-party reviewer should weigh" and hands the human candidates, not a verdict. The downgrade: it is memo-only. Novelty is the textbook example of a judgment that is not decidable from the paper alone, and not decidable at any observability level — it depends on a corpus you can never prove you searched exhaustively. So this skill retrieves and lays out overlap; it refuses to grade it.tools/adjudicate_findings.pylistsnovelty-duplication-advisoryinZERO_WEIGHT_SKILLSand caps anything it emits atinfo. The memo informs; the human judges; the deterministic adjudicator owns the report verdict — and this skill never moves it.
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.
- 12d ago First seen · 1,107 lines · 284 tokens per session scan A fe335ab9fec2
novelty-duplication-advisory is a skill published in the GitHub repository wanshuiyin/Anti-Autoresearch (153 stars, last pushed 3d ago), licensed MIT. It adds 284 tokens to every session and 18,206 once invoked, about $0.0014 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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