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alphafold-db

Access over 200M protein structures from AlphaFold DB; use when you need to retrieve predicted 3D structures (PDB/mmCIF), confidence metrics (pLDDT/PAE), or protein metadata by UniProt accession.

68

Quality

84%

Does it follow best practices?

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SecuritybySnyk

Passed

No findings from the security scan

SKILL.md
Quality
Evals
Security

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.

A clean, executable single-task skill with good structure and appropriately offloaded API reference. Its main weakness is the absence of validation/verification steps for a batch-capable, file-writing workflow.

Suggestions

Add validation checkpoints to the workflow: verify each downloaded file is non-empty and valid, and handle missing or invalid UniProt accessions explicitly rather than silently writing empty artifacts.

Trim the redundancy between the 'When to Use' and 'Key Features' sections to tighten the token budget.

Add a brief error-recovery note (e.g., what to do when the API returns 404 or a network error) to complete the feedback loop for batch runs.

DimensionReasoningScore

Conciseness

Lean and assumes Claude's competence with no concept over-explanation, but 'Key Features' partially restates 'When to Use', a minor redundancy that keeps it just below a 5.

4 / 5

Actionability

Two fully executable copy-paste bash commands with real flags and documented expected outputs cover the common cases, matching the 5 anchor.

5 / 5

Workflow Clarity

The single-action flow is clear, but this batch-capable, file-writing skill has no validation or verification steps (no success check, no file-validity check, no handling of missing/invalid accessions), so workflow clarity is capped at 3 per the batch-operation guideline.

3 / 5

Progressive Disclosure

Well-organized sections with API detail correctly offloaded to a real, clearly-signaled one-level-deep reference (references/api_reference.md) and a bundled script; falls just short of the 5 anchor's multi-reference clarity.

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.

A strong, specific description with concrete actions and an explicit trigger clause; it clearly answers both what and when. Minor room for improvement in synonym breadth of trigger terms.

DimensionReasoningScore

Specificity

Names multiple concrete actions—retrieve 3D structures (PDB/mmCIF), confidence metrics (pLDDT/PAE), and protein metadata by UniProt accession—with comprehensive coverage, matching the 5 anchor.

5 / 5

Completeness

Explicitly states both what it does (retrieve structures, confidence metrics, metadata) and when to use it via a concrete 'use when you need to retrieve...' trigger clause.

5 / 5

Trigger Term Quality

Strong natural keywords (protein structures, AlphaFold DB, pLDDT/PAE, UniProt accession) plus file-format extensions, but limited synonym variation keeps it just below comprehensive.

4 / 5

Distinctiveness Conflict Risk

Targets a clear niche (AlphaFold DB protein structures by UniProt accession) with distinct triggers and minimal overlap risk with other skills.

5 / 5

Total

19

/

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

frontmatter_unknown_keys

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

Warning

Total

15

/

16

Passed

Repository
aipoch/medical-research-skills
Reviewed

Table of Contents

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