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datacommons-client

Work with Data Commons, a platform providing programmatic access to public statistical data from global sources. Use this skill when working with demographic data, economic indicators, health statistics, environmental data, or any public datasets available through Data Commons. Applicable for querying population statistics, GDP figures, unemployment rates, disease prevalence, geographic entity resolution, and exploring relationships between statistical entities.

74

Quality

93%

Does it follow best practices?

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SecuritybySnyk

High

Do not use without reviewing

SKILL.md
Quality
Evals
Security

Quality

Content

86%Weight 40%Scale 1-5

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

A well-organized, actionable reference that pairs a concise overview with executable examples and a clearly signaled reference bundle. Main weakness is minor verbosity in prose sections and the absence of explicit validation checkpoints in the workflow.

Suggestions

Trim the Overview paragraph and consolidate the seven-item 'Tips for Effective Use' list into the most essential 3-4 items to reduce token overhead.

Add an explicit verification step in the Typical Workflow (e.g., checking that response.to_dict() returned expected entities before processing) to strengthen workflow clarity.

Consider moving the 'Finding Statistical Variables' pattern list into references/observation.md to keep SKILL.md focused on the overview.

DimensionReasoningScore

Conciseness

Mostly efficient and code-heavy with minimal concept padding, though sections like the Overview paragraph and the seven-item Tips list include mild over-explanation that could be trimmed. Not below 3 because it largely assumes Claude's competence and avoids explaining basic concepts.

4 / 5

Actionability

Provides copy-paste ready, executable Python examples across all three endpoints plus a full typical-workflow sequence and Pandas integration, covering the common cases concretely.

5 / 5

Workflow Clarity

The 'Typical Workflow' section sequences resolve -> discover -> query -> process steps clearly with code, but lacks explicit validation or verification checkpoints. Not capped at 3 because this is a read-only query skill rather than a destructive or batch operation, and the sequence is otherwise complete.

4 / 5

Progressive Disclosure

SKILL.md serves as a clear overview with well-signaled, one-level-deep references to observation.md, node.md, resolve.md, and getting_started.md — all confirmed to exist as real bundle files — with detailed API content appropriately split out.

5 / 5

Total

18

/

20

Passed

Description

100%Weight 40%Scale 1-5

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, well-structured description that clearly communicates the skill's purpose, concrete capabilities, and explicit usage triggers with rich natural keywords. It avoids vagueness and over-claims while remaining concise.

DimensionReasoningScore

Specificity

Lists multiple concrete actions including 'querying population statistics, GDP figures, unemployment rates, disease prevalence, geographic entity resolution, and exploring relationships between statistical entities', giving comprehensive coverage.

5 / 5

Completeness

Explicitly states what it does ('programmatic access to public statistical data from global sources') and when to use it ('Use this skill when working with demographic data...'), answering both clearly with concrete trigger phrases.

5 / 5

Trigger Term Quality

Covers natural terms users would say with synonyms — 'demographic data, economic indicators, health statistics, environmental data' plus concrete examples like 'GDP figures' and 'unemployment rates', comprehensive coverage.

5 / 5

Distinctiveness Conflict Risk

Named platform 'Data Commons' with a clear niche (public statistical data) and distinct triggers, minimizing conflict risk with other skills.

5 / 5

Total

20

/

20

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

frontmatter_unknown_keys

Unknown frontmatter key(s) found; consider removing or moving to metadata

Warning

Total

14

/

16

Passed

Repository
synthetic-sciences/openscience
Reviewed

Table of Contents

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