CtrlK
BlogDocsLog inGet started
Tessl Logo

bioservices

Unified Python interface to 40+ bioinformatics services. Use when querying multiple databases (UniProt, KEGG, ChEMBL, Reactome) in a single workflow with consistent API. Best for cross-database analysis, ID mapping across services. For quick single-database lookups use gget; for sequence/file manipulation use biopython.

69

Quality

86%

Does it follow best practices?

Run evals on this skill

Adds up to 20 points to the overall score

View guide

SecuritybySnyk

Low

Low-risk findings worth noting

SKILL.md
Quality
Evals
Security

Quality

Content

72%

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

Highly actionable and well-structured with verified bundle references and executable examples throughout. Main gaps are mild verbosity in overview/integration prose and missing validation checkpoints for batch and write operations.

Suggestions

Tighten the Overview, 'When to Use' bullets, and 'Integration with Other Tools' list — these restate domain knowledge Claude already has and can be trimmed without losing actionability.

Add explicit validation/verification steps to batch and write workflows (e.g., verify mapped IDs resolve, confirm output CSV/SIF rows before treating results as final) to lift workflow_clarity.

Move the per-service method enumerations that duplicate references/services_reference.md into the reference file, keeping SKILL.md to the most-used examples.

DimensionReasoningScore

Conciseness

Mostly efficient with executable snippets and key-method lists, but the Overview, When-to-Use bullet list, and Integration-with-Other-Tools prose add context Claude largely already knows and could be trimmed to be fully lean.

2 / 3

Actionability

Fully executable, copy-paste-ready code blocks with real method calls, plus runnable script invocations with concrete arguments — matching the 'fully executable / copy-paste ready' anchor.

3 / 3

Workflow Clarity

Script-driven pipelines give clear sequences and the BLAST section notes async status-checking, but batch operations (batch_id_converter, compound_cross_reference) and data-writing steps lack explicit validation/verification checkpoints, capping this at 2.

2 / 3

Progressive Disclosure

SKILL.md is an overview with one-level-deep references to real files (services_reference.md, workflow_patterns.md, identifier_mapping.md) and a Resources section listing four scripts; all referenced paths exist and navigation is clearly signaled.

3 / 3

Total

10

/

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.

A strong description: concrete actions, natural trigger terms, an explicit Use-when clause, and clear negative-trigger disambiguation against adjacent tools. It is concise yet complete on both what and when.

DimensionReasoningScore

Specificity

Names concrete actions ('querying multiple databases', 'cross-database analysis, ID mapping across services') and four specific databases (UniProt, KEGG, ChEMBL, Reactome), matching the 'multiple specific concrete actions' anchor.

3 / 3

Completeness

Explicit 'Use when querying multiple databases...' clause answers when, and 'Unified Python interface to 40+ bioinformatics services' answers what — both clearly present.

3 / 3

Trigger Term Quality

Natural user terms ('querying multiple databases', 'ID mapping', 'cross-database analysis') plus negative triggers ('For quick single-database lookups use gget') give good coverage of phrasing users would actually say.

3 / 3

Distinctiveness Conflict Risk

Explicit disambiguation against gget (single-DB lookups) and biopython (sequence/file manipulation) carves a clear niche unlikely to trigger the wrong skill.

3 / 3

Total

12

/

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

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
Reviewed

Table of Contents

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.