gene-database

Query the NCBI Gene database via E-utilities and the NCBI Datasets API; use it when you need to search genes by symbol/ID and retrieve annotations (RefSeq, GO, location, phenotype) for single or batch gene lists.

Quality

84%

Does it follow best practices?

Run evals on this skill

Adds up to 20 points to the overall score

View guide

Securityby

Passed

No findings from the security scan

Quality

Content

76%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.

The body is actionable and well-structured with real bundle files and executable commands, but the batch workflow lacks explicit validation/verification feedback loops, capping workflow clarity. Progressive disclosure is good but could signal references more prominently.

Suggestions

Add an explicit validate-fix-retry feedback loop to the batch lookup workflow, including a verification step (e.g., checking for unresolved/failed IDs and retrying them) before declaring the batch complete.

Surface the references/api_reference.md and references/common_workflows.md pointers earlier and unconditionally rather than under an 'If present in the repository' hedge, so navigation is clearly signaled.

Trim the advanced query-string listing and restated dependency basics to tighten token efficiency.

Dimension	Reasoning	Score
Conciseness	The body is efficient with executable command examples and no concept-overexplaining, though minor padding (advanced query string listings, conditional 'If present in the repository' hedging) could be trimmed.	4 / 5
Actionability	Every common case has copy-paste-ready, executable bash commands referencing real scripts (search, retrieve-by-ID, Datasets API, batch-from-file, batch-from-IDs), covering the common cases specifically.	5 / 5
Workflow Clarity	Sections are organized by use case, but the batch workflow ('dozens to thousands of genes') lacks explicit validation/verification checkpoints and a validate-fix-retry feedback loop; per the rubric's batch-operation cap, workflow clarity cannot exceed 3.	3 / 5
Progressive Disclosure	The body is a well-organized overview with one-level-deep references to real, present files (references/api_reference.md, references/common_workflows.md), though the signaling is slightly weakened by being buried at the end under conditional 'If present' phrasing.	4 / 5
	Total	16 / 20 Passed

Description

92%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.

The description is specific, third-person, and clearly pairs concrete capabilities with an explicit use-when trigger phrase. It is highly distinctive with minimal conflict risk, with only minor room to add casual user-facing synonyms.

Dimension	Reasoning	Score
Specificity	Names multiple concrete actions—querying via E-utilities and Datasets API, searching by symbol/ID, retrieving annotations (RefSeq, GO, location, phenotype), and batch gene lists—yielding comprehensive coverage rather than just several actions with minor gaps.	5 / 5
Completeness	It explicitly answers both what (query NCBI Gene via two APIs, search by symbol/ID, retrieve annotations) and when ('use it when you need to search genes by symbol/ID and retrieve annotations... for single or batch gene lists') with concrete trigger phrases.	5 / 5
Trigger Term Quality	Strong, domain-appropriate keywords ('search genes by symbol/ID', 'retrieve annotations', 'gene lists', 'RefSeq, GO') are present, but casual synonyms or lay phrasings a user might say (e.g., 'look up a gene') are missing, keeping it just below comprehensive.	4 / 5
Distinctiveness Conflict Risk	The niche is tightly scoped to NCBI Gene, E-utilities, and the Datasets API with gene-specific annotation triggers, making overlap with other skills minimal.	5 / 5
	Total	19 / 20 Passed

Validation

93%

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 — 15 / 16 Passed

Validation for skill structure

Criteria	Description	Result
frontmatter_unknown_keys	Unknown frontmatter key(s) found; consider removing or moving to metadata	Warning

	Total	15 / 16 Passed

Repository: aipoch/medical-research-skills
Path: scientific-skills/Evidence Insight/gene-database/SKILL.md
Commit: 63c61d3

Reviewed: 8 hours ago

Table of Contents

Discovery Implementation Validation

Is this your skill?

If you maintain this skill, you can claim it as your own. Once claimed, you can manage eval scenarios, bundle related skills, attach documentation or rules, and ensure cross-agent compatibility.