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biopython

Comprehensive molecular biology toolkit. Use for sequence manipulation, file parsing (FASTA/GenBank/PDB), phylogenetics, and programmatic NCBI/PubMed access (Bio.Entrez). Best for batch processing, custom bioinformatics pipelines, BLAST automation. For quick lookups use gget; for multi-service integration use bioservices.

69

Quality

86%

Does it follow best practices?

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SecuritybySnyk

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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.

A well-structured, highly actionable skill body with excellent progressive disclosure and executable examples. Its main weaknesses are content redundancy across the example/pattern sections and missing explicit validation checkpoints for batch Entrez/BLAST operations.

Suggestions

Collapse duplication: remove the 'Common Patterns' that re-cover sequence analysis, BLAST+fetch, and phylogenetics already shown in the per-subsection quick examples, or keep patterns only for genuinely distinct multi-module workflows.

Show the Entrez email/API-key setup once (in Installation) and reference it instead of repeating the full block in subsection 3 and again in 'Writing Biopython Code'.

Add an explicit validate-retry checkpoint to the batch Entrez/BLAST guidance (e.g., check the returned record count, retry on HTTP 429 with backoff, verify non-empty results before proceeding) so batch operations meet the workflow-clarity feedback-loop expectation.

DimensionReasoningScore

Conciseness

Mostly efficient with concrete code, but carries real duplication: the per-subsection quick examples reappear in 'Common Patterns' (2-4 re-cover sequence analysis, BLAST+fetch, phylogenetics), the Entrez email setup is shown three times, and the 'Quick Reference' search patterns repeat those in 'Reading Documentation'. This matches the score-2 anchor of mostly efficient with some unnecessary content that could be tightened; not a 1 because there is no concept-padded tutorial prose, and not a 3 because the redundancy is clear.

2 / 3

Actionability

Abundant copy-paste-ready, executable code with concrete imports and arguments (e.g., Entrez.efetch(db='nucleotide', id='EU490707', rettype='gb')) plus real commands (uv pip install 'biopython==1.87', rg -n ...), matching the score-3 anchor of fully executable examples.

3 / 3

Workflow Clarity

The task-to-module-to-reference routing is sequenced, but batch/destructive operations (batch Entrez downloading, BLAST) lack embedded validation checkpoints or feedback loops; guidance mentions rate limiting/batching but not a validate-retry loop, which per the scoring notes caps batch-operation workflows at 2. Not a 1 because steps are clearly listed, and not a 3 because explicit validation checkpoints for batch work are missing.

2 / 3

Progressive Disclosure

A clear overview in SKILL.md with seven well-signaled, one-level-deep references (each under a numbered subsection with 'Reference: references/X.md', a use-list, and a quick example), and all referenced files exist in references/, matching the score-3 anchor of clear overview with well-signaled one-level-deep references.

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, third-person description that names concrete capabilities, supplies explicit 'use for/best for' triggers, and actively disambiguates against adjacent tools. It cleanly satisfies specificity, trigger quality, completeness, and distinctiveness.

DimensionReasoningScore

Specificity

Names a concrete domain plus multiple specific actions ('sequence manipulation, file parsing (FASTA/GenBank/PDB), phylogenetics... NCBI/PubMed access... BLAST automation'), matching the score-3 anchor of listing several specific concrete actions.

3 / 3

Completeness

Explicitly answers both what ('Comprehensive molecular biology toolkit' with capabilities) and when ('Use for...', 'Best for batch processing, custom bioinformatics pipelines, BLAST automation'), matching the score-3 anchor with explicit triggers; not capped at 2 because the 'when' is present and explicit.

3 / 3

Trigger Term Quality

Covers natural user-facing terms a person would actually say ('sequence manipulation', 'FASTA/GenBank/PDB', 'phylogenetics', 'BLAST', 'bioinformatics pipelines', 'batch processing'); these are not jargon-only, so it sits at the score-3 anchor rather than the score-2 'missing common variations' level.

3 / 3

Distinctiveness Conflict Risk

A clear molecular-biology niche with distinct triggers and active disambiguation against competing tools ('For quick lookups use gget; for multi-service integration use bioservices') makes conflict unlikely, matching the score-3 anchor.

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_field

'metadata' should map string keys to string values

Warning

frontmatter_unknown_keys

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

Warning

Total

14

/

16

Passed

Repository
K-Dense-AI/scientific-agent-skills
Reviewed

Table of Contents

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