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metabolomics-workbench-database

Access NIH Metabolomics Workbench via REST API (4,200+ studies). Query metabolites, RefMet nomenclature, MS/NMR data, m/z searches, study metadata, for metabolomics and biomarker discovery.

61

Quality

73%

Does it follow best practices?

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SecuritybySnyk

Passed

No findings from the security scan

Fix and improve this skill with Tessl

tessl review fix ./skills/bio/metabolomics-workbench-database/SKILL.md
SKILL.md
Quality
Evals
Security

Quality

Content

65%

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

A well-organized, highly actionable skill body built on real executable REST examples. It loses points for verbose descriptive prose and a promotional section, missing validation checkpoints in workflows, and a referenced file that is not present in the bundle.

Suggestions

Tighten or remove the descriptive lead sentences under each capability and the K-Dense Web promotional section so every token advances instruction.

Add explicit validation/error-handling steps to the workflows (e.g., check the HTTP response status and handle empty or error payloads before proceeding).

Either create references/api_reference.md and move the bulk of the endpoint detail there, or remove the dangling reference so navigation is not broken.

DimensionReasoningScore

Conciseness

Mostly efficient with concrete code, but padded with descriptive prose under each capability, background in the Overview, and a promotional K-Dense Web section that does not advance the skill's function.

2 / 3

Actionability

Provides numerous copy-paste-ready, executable `requests.get` calls against real REST URLs, plus templated placeholders for workflow steps — fully concrete guidance.

3 / 3

Workflow Clarity

The three workflows have clear numbered sequences, but none include explicit validation checkpoints or error-handling (e.g., checking HTTP status, handling empty result sets), leaving checkpoints implicit.

2 / 3

Progressive Disclosure

The body is well-sectioned and signals a one-level reference ('references/api_reference.md'), but that file does not exist in the bundle and a large amount of API detail lives inline in SKILL.md rather than being split out.

2 / 3

Total

9

/

12

Passed

Description

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.

A strong, specific, third-person description with good trigger terms and a clear niche. Its main weakness is the abbreviated 'when' guidance, which reads as a purpose tag rather than explicit use-when trigger enumeration.

Suggestions

Add an explicit 'Use when ...' clause enumerating the scenarios that should trigger this skill (e.g., querying metabolite structures, standardizing names via RefMet, m/z searches, retrieving study metadata).

Expand the trigger terms in the 'when' portion to mirror the breadth of the 'what' portion (e.g., add 'mass spectrometry', 'RefMet names', 'metabolomics studies').

DimensionReasoningScore

Specificity

Lists multiple concrete actions — 'Access NIH Metabolomics Workbench via REST API', 'Query metabolites', 'RefMet nomenclature', 'm/z searches', 'study metadata' — matching the anchor for several specific concrete actions.

3 / 3

Completeness

The 'what' is clearly stated, but the 'when' is only a terse trailing clause ('for metabolomics and biomarker discovery') rather than an explicit, enumerated 'Use when...' trigger of the kind the anchor-3 example shows.

2 / 3

Trigger Term Quality

Covers natural domain terms a metabolomics user would say — 'metabolites', 'RefMet', 'MS/NMR', 'm/z', 'metabolomics', 'biomarker discovery' — with good variation rather than jargon-only phrasing.

3 / 3

Distinctiveness Conflict Risk

The niche is highly specific — 'NIH Metabolomics Workbench via REST API' with RefMet/m/z triggers — making it unlikely to fire for unrelated skills.

3 / 3

Total

11

/

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.

Validation14 / 16 Passed

Validation for skill structure

CriteriaDescriptionResult

metadata_version

'metadata.version' is missing

Warning

referenced_paths_exist

Referenced path issues: 1 missing

Warning

Total

14

/

16

Passed

Repository
wu-yc/LabClaw
Reviewed

Table of Contents

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