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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.

70

Quality

86%

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SKILL.md
Quality
Evals
Security

Quality

Content

72%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.

A well-structured, highly actionable skill with excellent progressive disclosure and executable examples. Its main weakness is redundancy that inflates token cost, and the absence of explicit validation feedback loops for batch Entrez operations.

Suggestions

Remove the 'Common Patterns' section (or the per-module quick examples) — both cover the same ground, and consolidate the Entrez email setup so it appears once instead of four times.

Delete the 'Quick Reference' section; its rg patterns already appear under 'Reading Documentation', and fold the 'Summary' into the existing workflow guidance to avoid restating it.

Add an explicit validate→retry feedback loop for batch Entrez operations (e.g., handle HTTPError/rate-limit, back off, and re-fetch failed IDs) so the batch workflow clears the workflow_clarity cap.

DimensionReasoningScore

Conciseness

Assumes Claude's competence (no basic-concept explanations, third-person voice), but contains several redundant padded sections: 'Common Patterns' duplicates the per-module quick examples, 'Quick Reference' repeats the earlier rg search guidance, 'Summary' restates the workflow, and the Entrez email setup is repeated four times.

3 / 5

Actionability

Provides copy-paste-ready, executable code across every major capability (install pin, Entrez setup, SeqIO, Align, BLAST, PDB, Phylo, SeqUtils) plus concrete common-pattern pipelines covering the typical cases.

5 / 5

Workflow Clarity

A sequenced general workflow (identify module → read reference → extract patterns → combine) and a troubleshooting section are present, but validation checkpoints are only implicit, and batch operations like Entrez batch download lack an explicit validate→fix→retry feedback loop, capping the score at 3 per the batch-operation rubric rule.

3 / 5

Progressive Disclosure

The body is a clear overview with seven well-signaled, one-level-deep references (references/sequence_io.md, alignment.md, databases.md, blast.md, structure.md, phylogenetics.md, advanced.md), all verified to exist, with quick examples inline and bulk detail appropriately deferred to those files.

5 / 5

Total

16

/

20

Passed

Description

100%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.

A strong, specific description that clearly states capabilities, natural trigger terms, and when to use it, while actively disambiguating against adjacent skills. No verbosity or first/second-person voice issues.

DimensionReasoningScore

Specificity

Lists multiple specific concrete actions — 'sequence manipulation, file parsing (FASTA/GenBank/PDB), phylogenetics... programmatic NCBI/PubMed access... batch processing, custom bioinformatics pipelines, BLAST automation' — giving comprehensive coverage rather than vague language.

5 / 5

Completeness

Explicitly answers 'what' (comprehensive molecular biology toolkit with named capabilities) and 'when' ('Use for...', 'Best for...') with concrete trigger phrases, plus boundary guidance redirecting to gget and bioservices.

5 / 5

Trigger Term Quality

Uses natural terms bioinformatics users actually say (FASTA, GenBank, PDB, phylogenetics, NCBI/PubMed, BLAST, batch processing, pipelines), including format names/extensions as synonyms.

5 / 5

Distinctiveness Conflict Risk

Occupies a clear molecular-biology niche with distinct triggers, and explicit redirects ('For quick lookups use gget; for multi-service integration use bioservices') minimize overlap with neighboring skills.

5 / 5

Total

20

/

20

Passed

Validation

93%

Checks the skill against the spec for correct structure and formatting. All validation checks must pass before discovery and implementation can be scored.

Validation15 / 16 Passed

Validation for skill structure

CriteriaDescriptionResult

metadata_field

'metadata' should map string keys to string values

Warning

Total

15

/

16

Passed

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

Table of Contents

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