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literature-search

Comprehensive scientific literature search across PubMed, arXiv, bioRxiv, medRxiv. Natural language queries powered by Valyu semantic search.

53

Quality

61%

Does it follow best practices?

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SecuritybySnyk

High

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tessl review fix ./skills/literature/literature-search/SKILL.md
SKILL.md
Quality
Evals
Security

Quality

Content

65%

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

The body is highly actionable with concrete commands and clear error handling, but it carries marketing fluff and a tangential SDK-integration section that hurt conciseness, and it references script files that are not present in the bundle. Trimming the marketing section, moving integration examples to a reference file, and adding a guard for the path-resolution step would improve the score.

Suggestions

Remove or drastically shrink the 'Why This Skill is Powerful' marketing section; focus on instructions Claude needs to run searches.

Add an explicit guard after the find command, e.g. 'If LITERATURE_SCRIPT is empty, fall back to ...' or verify the path before invoking.

Move the Python/TypeScript SDK integration examples into a separate reference file (e.g. references/INTEGRATION.md) and link to it, ensuring the referenced scripts/ files actually ship in the bundle.

DimensionReasoningScore

Conciseness

Most of the body is concrete commands and examples, but the 'Why This Skill is Powerful' marketing bullets and the Python/TypeScript SDK integration section are padding that doesn't directly help Claude execute searches.

2 / 3

Actionability

Copy-paste-ready commands like 'scripts/search "query" 15', jq pipelines, a setup flow, and a concrete output JSON schema give fully executable guidance.

3 / 3

Workflow Clarity

The API key setup flow is a clear numbered sequence with a retry step and error handling is documented via success field/exit codes, but the script path-resolution step lacks an explicit validation checkpoint (e.g. failing when LITERATURE_SCRIPT is empty).

2 / 3

Progressive Disclosure

The file is well-sectioned, but the referenced script files (scripts/search, scripts/search.mjs) do not exist in the bundle, and the inline SDK integration examples could be split into a separate reference file.

2 / 3

Total

9

/

12

Passed

Description

57%

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

The description clearly communicates what the skill does and occupies a distinct niche, but it lacks an explicit 'Use when...' trigger clause and stops short of listing multiple concrete actions. Adding when-to-use guidance and a few more natural user phrasings would raise the score.

Suggestions

Add a 'Use when...' clause naming natural triggers, e.g. 'Use when the user asks for a literature review, wants to find papers across PubMed/arXiv/bioRxiv/medRxiv, or needs cross-domain scientific research.'

List concrete actions beyond 'search', such as retrieving full article text, extracting figures/images, and aggregating results from multiple sources.

Include common user phrasings like 'find papers', 'literature review', and 'preprints' alongside the source names.

DimensionReasoningScore

Specificity

Quotes 'Comprehensive scientific literature search across PubMed, arXiv, bioRxiv, medRxiv' and 'Natural language queries powered by Valyu semantic search' name the domain and sources but describe essentially one action (search) rather than multiple concrete actions like retrieve full text or extract figures.

2 / 3

Completeness

The 'what' is clearly stated, but there is no 'Use when...' clause or equivalent explicit trigger guidance, which per the guidelines caps completeness at 2.

2 / 3

Trigger Term Quality

Source names (PubMed, arXiv, bioRxiv, medRxiv) are natural trigger terms, but common user phrasings like 'find papers', 'literature review', 'preprints', and 'research' are missing, so coverage is incomplete.

2 / 3

Distinctiveness Conflict Risk

The named scientific databases and Valyu-powered semantic search define a clear niche with distinct triggers that is unlikely to conflict with other skills.

3 / 3

Total

9

/

12

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.

Validation14 / 16 Passed

Validation for skill structure

CriteriaDescriptionResult

frontmatter_unknown_keys

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

Warning

referenced_paths_exist

Referenced path issues: 10 missing

Warning

Total

14

/

16

Passed

Repository
wu-yc/LabClaw
Reviewed

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