Getting it into your agent
This one installs as part of its plugin. Adding the marketplace and installing the plugin brings it with everything else the plugin ships.
/plugin marketplace add wenhaochai/claude-plugins/plugin install 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/wenhaochai/claude-plugins/novelty-duplication-advisory)<a href="https://agentmods.dev/skills/wenhaochai/claude-plugins/novelty-duplication-advisory"><img src="https://agentmods.dev/badge/skills/wenhaochai/claude-plugins/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/wenhaochai/claude-plugins/novelty-duplication-advisory"><img src="https://agentmods.dev/badge/skills/wenhaochai/claude-plugins/novelty-duplication-advisory.svg" alt="Reviewed on agentmods" width="80" height="20"></a>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 | $0.00285 | $0.18115 |
| Opus 5 | $0.00143 | $0.09057 |
| Sonnet 5 | $0.00057 | $0.03623 |
| Haiku 4.5 | $0.00028 | $0.01811 |
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 11d 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.
This is a copy
100% identical to novelty-duplication-advisory — 55 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.
How it starts
The opening of the file, as written. The whole thing — 1,104 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-advisoryinMEMO_ONLY_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.
- 11d ago First seen · 1,104 lines · 285 tokens per session scan A 692bc961d3fd
novelty-duplication-advisory is a skill published in the GitHub repository wenhaochai/claude-plugins (16 stars, last pushed 11d ago), licensed MIT. It adds 285 tokens to every session and 18,115 once invoked, about $0.0014 per session on Opus 5. A static security scan graded it A with 0 findings. It is 100% identical to novelty-duplication-advisory, differing in 55 lines, and is treated as a copy.
Other skills, from other repositories
instrument-data-to-allotrope
Convert laboratory instrument output files (PDF, CSV, Excel, TXT) to Allotrope Simple Model (ASM) JSON format or flattened 2D CSV. Use this skill when scientists need to standardize instrument data for LIMS systems, data lakes, or downstream analysis. Supports auto-detection of instrument types. Outputs include full…
exploratory-data-analysis
Perform bounded, local exploratory analysis of explicitly supported scientific files. Use for redacted CSV/TSV/JSON profiles; optional NumPy, HDF5, FASTA/FASTQ, and basic image metadata inspection; missingness/leakage audits; outlier and transformation sensitivity; and rigorous EDA report scaffolds. Other domain…
matlab
Build, review, migrate, and safely plan MATLAB or GNU Octave numerical workflows, including arrays, tabular/time data, tests, projects, graphics, MAT files, and explicit Python interoperability.
phylogenetics
Build and analyze phylogenetic trees using MAFFT (multiple alignment), IQ-TREE 2 (maximum likelihood), and FastTree (fast NJ/ML). Visualize with ETE3 or FigTree. For evolutionary analysis, microbial genomics, viral phylodynamics, protein family analysis, and molecular clock studies.
research-engineer
An uncompromising Academic Research Engineer. Operates with absolute scientific rigor, objective criticism, and zero flair. Focuses on theoretical correctness, formal verification, and optimal implementation across any required technology.
mapping-to-snomed
Maps clinical concept spans extracted by OpenMed to SNOMED CT concepts through a USER-SUPPLIED terminology server (the user's own Ontoserver, Snowstorm, or UMLS/UTS), never a bundled vocabulary. Use when the user wants to code findings, disorders, procedures, body structures, or substances to SNOMED CT, run an ECL…