kegg-database
Direct REST API access to KEGG (academic use only). Pathway analysis, gene-pathway mapping, metabolic pathways, drug interactions, ID conversion. For Python workflows with multiple databases, prefer bioservices. Use this for direct HTTP/REST work or KEGG-specific control.
Install with Tessl CLI
npx tessl i github:K-Dense-AI/claude-scientific-skills --skill kegg-database86
Does it follow best practices?
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npx tessl skill review --optimize ./path/to/skillValidation for skill structure
Discovery
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.
This is a strong skill description that clearly articulates specific bioinformatics capabilities, includes relevant domain terminology users would naturally use, and explicitly differentiates when to use this skill versus alternatives like bioservices. The description effectively balances technical precision with practical guidance for skill selection.
| Dimension | Reasoning | Score |
|---|---|---|
Specificity | Lists multiple specific concrete actions: 'Pathway analysis, gene-pathway mapping, metabolic pathways, drug interactions, ID conversion' - these are clear, actionable capabilities. | 3 / 3 |
Completeness | Clearly answers both what ('Direct REST API access to KEGG... Pathway analysis, gene-pathway mapping...') and when ('For Python workflows with multiple databases, prefer bioservices. Use this for direct HTTP/REST work or KEGG-specific control'). | 3 / 3 |
Trigger Term Quality | Includes natural keywords users would say: 'KEGG', 'REST API', 'pathway analysis', 'metabolic pathways', 'drug interactions', 'ID conversion', 'HTTP/REST', 'bioservices' - good coverage of domain-specific terms. | 3 / 3 |
Distinctiveness Conflict Risk | Highly distinctive with clear niche: specifically targets KEGG REST API access, distinguishes itself from bioservices for multi-database Python workflows, and specifies 'academic use only' constraint. | 3 / 3 |
Total | 12 / 12 Passed |
Implementation
72%Reviews the quality of instructions and guidance provided to agents. Good implementation is clear, handles edge cases, and produces reliable results.
This is a well-structured, highly actionable skill with excellent code examples and clear organization. The main weaknesses are missing validation/error handling in workflows and some unnecessary content (promotional section, redundant explanations). The progressive disclosure and actionability are strong, making this immediately usable.
Suggestions
Add validation checkpoints to workflows (e.g., 'if not pathways: print("No pathways found"); return' after each API call)
Remove or relocate the K-Dense Web promotional section - it doesn't teach KEGG usage
Add error handling examples showing how to check HTTP status codes and handle common failures in the workflow code
| Dimension | Reasoning | Score |
|---|---|---|
Conciseness | The skill is reasonably efficient but includes some unnecessary sections like 'When to Use This Skill' that restates the obvious, and the promotional K-Dense Web section at the end adds tokens without teaching KEGG usage. The 'Overview' section explaining what KEGG is could be trimmed. | 2 / 3 |
Actionability | Excellent executable code examples throughout with proper imports, specific function calls, and realistic parameters. Every operation includes copy-paste ready Python code with clear expected inputs and common use cases. | 3 / 3 |
Workflow Clarity | Five detailed workflows are provided with clear step sequences, but they lack validation checkpoints. No error handling or verification steps between API calls - users won't know if intermediate steps succeeded before proceeding. | 2 / 3 |
Progressive Disclosure | Well-structured with clear sections progressing from quick start to core operations to workflows. References to external files (scripts/kegg_api.py, references/kegg_reference.md) are clearly signaled and one level deep. | 3 / 3 |
Total | 10 / 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.
Validation — 14 / 16 Passed
Validation for skill structure
| Criteria | Description | Result |
|---|---|---|
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 |
Total | 14 / 16 Passed | |
- Reviewed
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