Research novelty review
Run a stringent, adversarial novelty review over a concrete research idea, method, protocol, artifact, or claimed finding. Use when asked to assess novelty, position a paper or project, build a prior-art matrix, decide whether something is incremental, or pressure-test whether the right move is to proceed, reframe, or abandon. Prefer `research-paper-review` for first-pass technical critique of a single paper artifact and `research-rebuttal` when the task is to answer concrete reviewer comments rather than establish novelty positioning from scratch.From its SKILL.md
npx -y skills add kenantang/codex-and-claude-skills --skill research-novelty-reviewAssembled from the repository path, not quoted from the project. Check it against their README if it does not work.
2 things to look at
- no licenseNo license file was found in the repository. Code published without one is not open source by default, so using it at work is a question for whoever answers licensing questions where you are.
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SKILL.md
5.7 KB, ~1.2k tokens by cl100k_base, as published. Nobody here has run it
Research Novelty Review
Quick start
- Start skeptical: treat the contribution as incremental until the evidence says otherwise.
- Decompose the claim into searchable units before looking at any literature.
- Search strongest overlaps first, not flattering long-tail analogies.
- Write down novelty-killing objections explicitly before giving any green light.
- End with a 1-5 novelty decision rating, not a coarse ternary label, plus the narrowest defensible positioning.
Modes
Standalone mode
- Work from the user prompt plus any local notes, citations, or existing review artifacts.
- Do not require a suite root.
- Remain collaboration-friendly: if literature review or review-loop artifacts already exist, consume them; if broader retrieval or a second adversarial pass would materially help, recommend or invoke that workflow rather than staying artificially isolated.
Orchestrated mode
- Prefer the canonical directory
./novelty-review/. - Read upstream context from
research-brief.md,artifact-index.md,./literature-review/, and./zotero/when present. - Keep outputs legible to downstream experiment planning and paper planning.
Input contract
- Minimum: a concrete method, protocol, artifact, finding, or contribution claim.
- Prefer:
- target venue or community
- closest known prior work
- scope of novelty under consideration
- existing literature or review artifacts
- existing Zotero library artifacts
Hard stops
- Stop if the proposed contribution is too vague to search.
- Stop if browsing or a usable corpus is unavailable.
- Stop if the claim bundles so many moving parts that a fair novelty comparison is impossible.
- In standalone mode, do not force suite initialization when a direct adversarial review will do.
Output contract
- Primary files:
novelty-report.mdprior-art-matrix.mdsearch-log.mdnovelty-decision.json
- In orchestrated mode, these live under
./novelty-review/. - In standalone mode, any target directory is valid.
novelty-decision.jsonshould capture the final 1-5 novelty rating, confidence rating, and the exact narrow positioning that survives the review.
Workflow
1) Decompose the claim before searching
- Write the contribution in one sentence.
- Split novelty into:
- framing
- method
- evaluation protocol
- artifact or dataset
- empirical finding
- Reject blended claims that hide which part is allegedly new.
2) Search with a kill-shot mindset
- Use
references/adversarial-query-patterns.mdandreferences/search-log-template.md. - If the user maintains a relevant Zotero library or collection, invoke
research-zoterofirst or consume./zotero/zotero-items.jsonas a curated seed corpus. - Search the strongest plausible overlaps first.
- Prioritize recent literature and venue-appropriate sources before padding with weaker analogies.
- Log exact queries, filters, and what each search was trying to falsify.
3) Build the prior-art matrix
- Use
references/prior-art-matrix-template.md. - Record closest overlaps, not just vaguely related work.
- Score how much each prior work threatens the novelty claim on a 1-5 scale.
- Prefer concrete overlap dimensions over narrative hand-waving.
4) Write the objections first
- Use
references/reviewer-objection-rubric.mdandreferences/overlap-scoring-rubric.md. - State the strongest objections a skeptical reviewer would raise.
- Flag renaming, recombination, routine scaling, and standard-bundle effects aggressively.
- If the novelty is weak but the usefulness is real, say so clearly.
- Keep the ratings explicit:
- overlap threat rating: 1-5
- surviving novelty strength: 1-5
- confidence in the decision: 1-5
5) Decide and position narrowly
- Use
references/decision-scale.md. - End with:
novelty_decision_ratingon a 1-5 scaledecision_confidence_ratingon a 1-5 scale
- Offer the narrowest defensible positioning that survives the objections.
- Use this interpretation:
1: abandon; the core claim is effectively killed by overlap2: major reframe required before proceeding3: narrow proceed only; some novelty survives but only under a sharply reduced claim4: proceed with careful positioning; novelty looks real but vulnerable5: strong novelty position; closest overlaps do not materially undercut the core claim
- If deeper retrieval would materially improve confidence, collaborate with
research-systematic-literature-review. - If a second adversarial pass would help and delegation is explicitly available and permitted, an independent review pass is allowed. Do not assume that permission.
References
references/novelty-checklist.mdreferences/prior-art-matrix-template.mdreferences/search-log-template.mdreferences/adversarial-query-patterns.mdreferences/decision-scale.mdreferences/overlap-scoring-rubric.mdreferences/reviewer-objection-rubric.mdreferences/tabmol-ddi-ood-adapter.md
Script
scripts/init_novelty_pack.py: createnovelty-report.md,prior-art-matrix.md,search-log.md, andnovelty-decision.jsonin a standalone directory or the suite'snovelty-review/directory.
What ships with it: 10 files
6.3 KB alongside SKILL.md, 1 of them executable
agents/
- openai.yaml327 B
references/
scripts/
- init_novelty_pack.pyruns2.4 KB