biorxiv-database

Efficient database search tool for bioRxiv preprint server. Use this skill when searching for life sciences preprints by keywords, authors, date ranges, or categories, retrieving paper metadata, downloading PDFs, or conducting literature reviews.

Quality

82%

Does it follow best practices?

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Securityby

Passed

No findings from the security scan

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 content is highly actionable with executable, well-verified examples, but it is verbose and repetitive, and its multi-step workflows omit validation feedback loops for batch operations. Restructuring would significantly improve token efficiency and navigation.

Suggestions

Collapse the five near-identical search sections into one parameterized example plus a compact flag reference; remove the mock emoji test transcript and the duplicated 'Reference Documentation' description.

Move the full JSON output schema and the complete categories list into references/ files, leaving only a representative example and a pointer in SKILL.md.

Add an explicit validate/retry checkpoint to the batch PDF-download workflow (e.g., check the saved file exists and is non-empty, retry on HTTP failure) before declaring the download complete.

Dimension	Reasoning	Score
Conciseness	The ~480-line body is repetitive — five near-identical 'Basic Usage' search sections, a full category list, a complete JSON schema, a mock test-suite transcript, and a re-explanation of the reference file — and could be cut substantially despite being mostly actionable rather than conceptual padding.	2 / 3
Actionability	It provides copy-paste-ready executable CLI commands and Python API calls tied to the real scripts/biorxiv_search.py, with concrete examples for every capability.	3 / 3
Workflow Clarity	The literature-review workflow is sequenced, but batch PDF downloads and other batch operations lack explicit validation checkpoints or error-recovery feedback loops, which caps clarity at 2 per the rubric.	2 / 3
Progressive Disclosure	It signals the real references/api_reference.md one level deep, but the body keeps a large amount of detail (full output schema, category list, mock test output) inline that could be split into referenced files.	2 / 3
	Total	9 / 12 Passed

Description

100%

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 is exemplary: it is concise, third-person, lists concrete capabilities, and provides an explicit 'Use when' trigger clause. It clearly distinguishes the skill and would surface naturally for relevant user requests.

Dimension	Reasoning	Score
Specificity	The description enumerates multiple concrete actions — keyword/author/date/category search, metadata retrieval, PDF download, and literature reviews — rather than vague language.	3 / 3
Completeness	It states both what it does ('Efficient database search tool for bioRxiv preprint server') and an explicit 'Use this skill when' trigger clause covering several scenarios.	3 / 3
Trigger Term Quality	It surfaces natural terms a user would say ('searching for life sciences preprints by keywords, authors, date ranges', 'downloading PDFs', 'literature reviews') with broad coverage.	3 / 3
Distinctiveness Conflict Risk	It is tightly scoped to the bioRxiv preprint server with niche-specific triggers (preprints, DOIs, PDF download), making conflict with other skills unlikely.	3 / 3
	Total	12 / 12 Passed

Validation

87%

Warnings & errors only

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

Criteria	Description	Result
metadata_version	'metadata.version' is missing	Warning
frontmatter_unknown_keys	Unknown frontmatter key(s) found; consider removing or moving to metadata	Warning

	Total	14 / 16 Passed

Repository: synthetic-sciences/openscience
Path: backend/cli/skills/databases/biorxiv-database/SKILL.md
Commit: 52845c3

Reviewed: about 10 hours ago

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