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fda-database

Query openFDA API for drugs, devices, adverse events, recalls, regulatory submissions (510k, PMA), substance identification (UNII), for FDA regulatory data analysis and safety research.

81

2.17x
Quality

77%

Does it follow best practices?

Impact

85%

2.17x

Average score across 3 eval scenarios

SecuritybySnyk

Advisory

Suggest reviewing before use

Optimize this skill with Tessl

npx tessl skill review --optimize ./scientific-skills/fda-database/SKILL.md
SKILL.md
Quality
Evals
Security

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 skill description with excellent specificity and domain-appropriate trigger terms covering FDA regulatory data. The main weakness is the lack of an explicit 'Use when...' clause, which would help Claude know exactly when to select this skill. The description effectively carves out a distinct niche in FDA/regulatory data querying.

Suggestions

Add an explicit 'Use when...' clause, e.g., 'Use when the user asks about FDA data, drug safety, medical device recalls, or regulatory submissions.'

DimensionReasoningScore

Specificity

Lists multiple specific concrete actions: 'Query openFDA API for drugs, devices, adverse events, recalls, regulatory submissions (510k, PMA), substance identification (UNII)' - these are specific, concrete capabilities.

3 / 3

Completeness

Clearly answers 'what' (query openFDA API for various data types) but lacks an explicit 'Use when...' clause. The purpose is implied ('for FDA regulatory data analysis and safety research') but not framed as explicit trigger guidance.

2 / 3

Trigger Term Quality

Excellent coverage of natural terms users would say: 'FDA', 'drugs', 'devices', 'adverse events', 'recalls', '510k', 'PMA', 'UNII', 'regulatory', 'safety research' - these are terms domain users would naturally use.

3 / 3

Distinctiveness Conflict Risk

Highly distinctive with specific domain focus on openFDA API and regulatory terminology (510k, PMA, UNII). Unlikely to conflict with other skills due to the specialized FDA/regulatory niche.

3 / 3

Total

11

/

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 good progressive disclosure to reference materials. The main weaknesses are moderate verbosity in introductory sections and missing explicit validation checkpoints in multi-step workflows. The skill would benefit from trimming explanatory content and adding validation steps to the query patterns.

Suggestions

Remove or significantly condense the 'When to Use This Skill' section - Claude can infer appropriate use cases from the overview and examples

Add explicit validation/error-checking steps within the Common Query Patterns (e.g., 'Step 1: Query, Step 2: Validate response has results, Step 3: Process')

Trim the Overview section - the 'Key capabilities' bullet list largely duplicates information available in the Database Categories section

DimensionReasoningScore

Conciseness

The skill is comprehensive but includes some unnecessary verbosity, such as explaining what openFDA is and listing capabilities Claude could infer. The 'When to Use This Skill' section is largely redundant given the overview. However, the code examples are appropriately lean.

2 / 3

Actionability

Excellent actionability with fully executable Python code examples throughout. The Quick Start section provides copy-paste ready code, and the Common Query Patterns section offers complete, working functions for real use cases.

3 / 3

Workflow Clarity

While individual code patterns are clear, the skill lacks explicit validation checkpoints. Error handling is mentioned but not integrated into workflows as mandatory steps. The 'Working with Results' section shows error handling but doesn't enforce a validate-then-proceed pattern.

2 / 3

Progressive Disclosure

Excellent structure with clear overview, well-organized sections, and appropriate references to detailed documentation (references/drugs.md, references/devices.md, etc.). Navigation is clear with one-level-deep references properly signaled.

3 / 3

Total

10

/

12

Passed

Validation

81%

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

Validation9 / 11 Passed

Validation for skill structure

CriteriaDescriptionResult

skill_md_line_count

SKILL.md is long (517 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
Reviewed

Table of Contents

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