brenda-database

Access BRENDA enzyme database via SOAP API. Retrieve kinetic parameters (Km, kcat), reaction equations, organism data, and substrate-specific enzyme information for biochemical research and metabolic pathway analysis.

3.47x

Quality

58%

Does it follow best practices?

Impact

73%

3.47x

Average score across 3 eval scenarios

Securityby

Advisory

Suggest reviewing before use

Optimize this skill with Tessl

npx tessl skill review --optimize ./scientific-skills/brenda-database/SKILL.md

Quality

Discovery

82%

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 data source (BRENDA), access method (SOAP API), and detailed capabilities (kinetic parameters, reaction equations, etc.). The main weakness is the absence of an explicit 'Use when...' clause, which would help Claude know exactly when to select this skill. The domain-specific terminology provides excellent trigger coverage for biochemistry users.

Suggestions

Add an explicit 'Use when...' clause, e.g., 'Use when the user asks about enzyme kinetics, needs Km/kcat values, queries BRENDA, or analyzes metabolic pathways.'

Dimension	Reasoning	Score
Specificity	Lists multiple specific concrete actions: 'Retrieve kinetic parameters (Km, kcat), reaction equations, organism data, and substrate-specific enzyme information' - these are precise, domain-specific capabilities.	3 / 3
Completeness	Clearly answers 'what' (access BRENDA, retrieve various enzyme data) but lacks an explicit 'Use when...' clause or equivalent trigger guidance. The use cases are implied through the listed capabilities but not explicitly stated.	2 / 3
Trigger Term Quality	Includes strong natural keywords users would say: 'BRENDA', 'enzyme database', 'kinetic parameters', 'Km', 'kcat', 'reaction equations', 'organism data', 'substrate', 'biochemical research', 'metabolic pathway analysis' - excellent coverage of domain terminology.	3 / 3
Distinctiveness Conflict Risk	Highly distinctive with clear niche: BRENDA enzyme database via SOAP API is very specific. The technical domain (biochemistry, enzymology) and specific database name make conflicts with other skills extremely unlikely.	3 / 3
	Total	11 / 12 Passed

Implementation

35%

Reviews the quality of instructions and guidance provided to agents. Good implementation is clear, handles edge cases, and produces reliable results.

This skill is comprehensive but severely over-engineered for Claude's context window. It explains concepts Claude already knows, provides extensive code examples for helper scripts that aren't actually included, and lacks the validation checkpoints needed for API operations. The content would benefit from aggressive trimming and splitting into focused reference files.

Suggestions

Reduce the main skill to ~100 lines with a quick start example and links to separate reference files for workflows, helper scripts, and API details

Either include the actual implementation of brenda_client and helper scripts, or remove the code examples that reference them and provide only the raw SOAP API usage

Add explicit validation steps to workflows (e.g., 'Verify authentication succeeded before proceeding', 'Check if results are empty before parsing')

Remove the 'When to Use This Skill' section and 'Overview' paragraph - Claude can infer these from the content itself

Dimension	Reasoning	Score
Conciseness	The skill is extremely verbose at ~600+ lines, with extensive explanations Claude doesn't need (e.g., 'BRENDA is the world's most comprehensive enzyme information system'), redundant 'When to Use This Skill' sections listing obvious use cases, and massive code examples that could be condensed significantly.	1 / 3
Actionability	Code examples appear executable but reference non-existent modules like 'brenda_client' and 'scripts.brenda_queries' without providing their implementations. The examples show function calls but the actual helper scripts are only described, not provided, making them pseudocode in practice.	2 / 3
Workflow Clarity	The 'Common Workflows' section provides step sequences but lacks validation checkpoints. For API operations that can fail (rate limits, auth errors, missing data), there are no explicit 'validate before proceeding' steps or feedback loops for error recovery.	2 / 3
Progressive Disclosure	References 'references/api_reference.md' for detailed documentation which is good, but the main file is a monolithic wall of text with 9 core capabilities, 6 workflows, and extensive inline content that should be split into separate files for different use cases.	2 / 3
	Total	7 / 12 Passed

Validation

81%

Warnings & errors only

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

Validation — 9 / 11 Passed

Validation for skill structure

Criteria	Description	Result
skill_md_line_count	SKILL.md is long (718 lines); consider splitting into references/ and linking	Warning
metadata_version	'metadata.version' is missing	Warning

	Total	9 / 11 Passed

Repository: K-Dense-AI/claude-scientific-skills
Commit: 71add64

Reviewed: 7 days ago

Table of Contents

Discovery Implementation Validation

Is this your skill?

If you maintain this skill, you can claim it as your own. Once claimed, you can manage eval scenarios, bundle related skills, attach documentation or rules, and ensure cross-agent compatibility.