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aris-novelty-check

Verify research idea novelty against recent literature. Use when user says "查新", "novelty check", "有没有人做过", "check novelty", or wants to verify a research idea is novel before implementing.

Quality

87%

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SecuritybySnyk

Low

Low-risk findings worth noting

SKILL.md
Quality
Evals
Security

Quality

Content

88%Weight 40%Scale 1-5

Reviews the quality of instructions and guidance provided to agents. Good implementation is clear, handles edge cases, and produces reliable results.

A well-engineered, self-contained workflow skill: phases are clearly sequenced with fallbacks and validation checkpoints, and the guidance is concrete down to executable curl commands and a verbatim reviewer prompt. The only meaningful improvements are trimming minor redundancy and optionally splitting the report template or API snippets into a reference file.

DimensionReasoningScore

Conciseness

The body is dense and assumes competence — no space is spent explaining concepts Claude already knows, and the curl snippets, Codex config, and report template all earn their tokens. It is not a 5 because of minor redundancy: 'always include the last 6 months of arXiv' appears in both Phase B and the Important Rules, and the Constants/optional-Codex notes repeat the fallback twice.

4 / 5

Actionability

Guidance is fully executable: exact curl commands for the arXiv and Semantic Scholar APIs, a copy-paste Codex config ("model_reasoning_effort": "xhigh"), a verbatim sub-agent brief, minimum search counts ('at least 3 different query formulations per claim'), and a complete output report template. This matches the anchor for copy-paste-ready commands covering the common cases.

5 / 5

Workflow Clarity

Phases A–D are clearly sequenced with explicit checkpoints and error handling: an availability check gates C1 vs C2, a WebSearch-unavailable fallback gives direct API calls, C2 includes reconciliation ('every overlap raised must be answered with a concrete difference or accepted as prior work'), and a confidence cap (never above 7/10 on the same-model path) guards the weaker route. Clear sequence with explicit validation and feedback loops, matching anchor 5.

5 / 5

Progressive Disclosure

A single well-sectioned file (Constants, Phases A–D, Important Rules) where all inline content is directly needed for the workflow, so it sits above anchor 3. It is not a 5: the ~120-line body keeps everything inline (report template, API snippets) with no split into reference files, and the only nod to external material is a passing mention of the 'aris-arxiv' and 'aris-semantic-scholar' skills rather than well-signaled one-level-deep references.

4 / 5

Total

18

/

20

Passed

Description

82%Weight 40%Scale 1-5

Based on the skill's description, can an agent find and select it at the right time? Clear, specific descriptions lead to better discovery.

A strong description with an explicit 'Use when' clause and natural bilingual trigger phrases covering both English and Chinese users. Its main gap is specificity — it states only the top-level action rather than the concrete steps the skill actually performs (search, adversarial review, report).

Suggestions

Enumerate the concrete actions in the description, e.g. 'Search arXiv and Semantic Scholar, run an adversarial cross-model review, and produce a scored novelty report' to raise specificity.

Add common English trigger variants such as 'has anyone done this', 'is this idea new', or 'find prior work' to broaden natural keyword coverage.

DimensionReasoningScore

Specificity

"Verify research idea novelty against recent literature" names the domain and one concrete action but does not enumerate the sub-actions performed (multi-source search, cross-model review, structured report). It fits the '1-2 concrete actions, not comprehensive' anchor; a 4 would require several specific actions listed.

3 / 5

Completeness

Clearly answers both questions: what ("Verify research idea novelty against recent literature") and when ("Use when user says ... or wants to verify a research idea is novel before implementing") with concrete trigger phrases. This matches anchor 5; it is above anchor 4 because the 'when' clause is explicit and specific rather than generic.

5 / 5

Trigger Term Quality

Includes natural bilingual trigger phrases — "查新", "novelty check", "有没有人做过", "check novelty" — that users would actually say, but misses common English variants like "has anyone done this", "is this new", or "prior work". Good coverage with a few natural terms missing, matching anchor 4 rather than the comprehensive anchor 5.

4 / 5

Distinctiveness Conflict Risk

Research-novelty verification is a distinct niche with dedicated triggers ("查新", "novelty check", "有没有人做过") that are unlikely to fire for generic literature-search or paper-writing skills. Clear niche with distinct triggers and minimal conflict risk, matching anchor 5.

5 / 5

Total

17

/

20

Passed

Validation

87%

Checks the skill against the spec for correct structure and formatting. All validation checks must pass before discovery and implementation can be scored.

Validation — 14 / 16 Passed

Validation for skill structure

CriteriaDescriptionResult

allowed_tools_field

'allowed-tools' contains unusual tool name(s)

Warning

frontmatter_unknown_keys

Unknown frontmatter key(s) found; consider removing or moving to metadata

Warning

Total

14

/

16

Passed

Repository

OpenLAIR/dr-claw

Path

skills/aris-novelty-check/SKILL.md

Reviewed

Table of Contents

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