alphafold-database
Access AlphaFold 200M+ AI-predicted protein structures. Retrieve structures by UniProt ID, download PDB/mmCIF files, analyze confidence metrics (pLDDT, PAE), for drug discovery and structural biology.
Install with Tessl CLI
npx tessl i github:K-Dense-AI/claude-scientific-skills --skill alphafold-databaseOverall
score
79%
Does it follow best practices?
If you maintain this skill, you can automatically optimize it using the tessl CLI to improve its score:
npx tessl skill review --optimize ./path/to/skillValidation for skill structure
Discovery
83%Based on the skill's description, can an agent find and select it at the right time? Clear, specific descriptions lead to better discovery.
This is a strong, technically specific description that clearly identifies the domain (AlphaFold protein structures) and lists concrete capabilities with appropriate technical terminology. The main weakness is the absence of an explicit 'Use when...' clause, which would help Claude know exactly when to select this skill over others.
Suggestions
Add an explicit 'Use when...' clause, e.g., 'Use when the user asks about protein structures, AlphaFold predictions, UniProt lookups, or needs structural biology data.'
| Dimension | Reasoning | Score |
|---|---|---|
Specificity | Lists multiple specific concrete actions: 'Retrieve structures by UniProt ID, download PDB/mmCIF files, analyze confidence metrics (pLDDT, PAE)' with clear domain context (drug discovery, structural biology). | 3 / 3 |
Completeness | Clearly answers 'what' (access structures, retrieve by ID, download files, analyze metrics) but lacks an explicit 'Use when...' clause or equivalent trigger guidance for when Claude should select this skill. | 2 / 3 |
Trigger Term Quality | Excellent coverage of natural terms users would say: 'AlphaFold', 'protein structures', 'UniProt ID', 'PDB', 'mmCIF', 'pLDDT', 'PAE', 'drug discovery', 'structural biology' - these are exactly what domain experts would use. | 3 / 3 |
Distinctiveness Conflict Risk | Highly distinctive with specific domain (AlphaFold, protein structures) and technical identifiers (UniProt ID, PDB/mmCIF, pLDDT, PAE) that are unlikely to conflict with other skills. | 3 / 3 |
Total | 11 / 12 Passed |
Implementation
73%Reviews the quality of instructions and guidance provided to agents. Good implementation is clear, handles edge cases, and produces reliable results.
This is a comprehensive, highly actionable skill with excellent executable code examples covering multiple access patterns for AlphaFold DB. The main weaknesses are some verbosity in introductory sections and missing validation checkpoints in multi-step workflows like batch processing and bulk downloads. The progressive disclosure is well-handled with clear navigation to advanced reference materials.
Suggestions
Remove or significantly condense the 'When to Use This Skill' section - Claude can infer appropriate use cases from the capabilities described
Add explicit validation steps to batch processing workflow (e.g., verify downloaded file integrity, check response status codes before proceeding)
Trim the 'Overview' paragraph which explains what AlphaFold DB is - this is context Claude already knows
| Dimension | Reasoning | Score |
|---|---|---|
Conciseness | The skill contains some unnecessary explanations (e.g., 'AlphaFold DB is a public repository of AI-predicted 3D protein structures' is context Claude knows) and could be tightened, but most content is functional code examples. The 'When to Use This Skill' section is verbose and largely redundant. | 2 / 3 |
Actionability | Excellent executable code examples throughout - all Python snippets are complete, copy-paste ready with proper imports, and cover multiple access methods (Biopython, direct API, Google Cloud). Includes concrete URLs, file formats, and working examples. | 3 / 3 |
Workflow Clarity | While individual operations are clear, multi-step workflows lack explicit validation checkpoints. The batch processing section has basic error handling but no verification that downloaded files are valid or complete. The bulk download workflow doesn't include validation steps. | 2 / 3 |
Progressive Disclosure | Well-organized with clear sections progressing from simple (Biopython) to advanced (Google Cloud bulk access). References external 'references/api_reference.md' for detailed API documentation. Content is appropriately split between overview and detailed examples. | 3 / 3 |
Total | 10 / 12 Passed |
Validation
75%Checks the skill against the spec for correct structure and formatting. All validation checks must pass before discovery and implementation can be scored.
Validation — 12 / 16 Passed
Validation for skill structure
| Criteria | Description | Result |
|---|---|---|
skill_md_line_count | SKILL.md is long (513 lines); consider splitting into references/ and linking | Warning |
description_trigger_hint | Description may be missing an explicit 'when to use' trigger hint (e.g., 'Use when...') | Warning |
metadata_version | 'metadata.version' is missing | Warning |
body_steps | No step-by-step structure detected (no ordered list); consider adding a simple workflow | Warning |
Total | 12 / 16 Passed | |
- Reviewed
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