Content
72%Reviews the quality of instructions and guidance provided to agents. Good implementation is clear, handles edge cases, and produces reliable results.
A highly actionable, well-structured API client skill with strong progressive disclosure, somewhat weakened by modest verbosity and a workflow that omits validation checkpoints.
Suggestions
Trim the Overview's background on what Data Commons aggregates and consolidate the inline "Common patterns" into the reference files to reduce duplication with references/.
Add explicit validation checkpoints to the Typical Workflow, e.g. "If a name resolves to no candidates, retry with a more specific name or entity_type" and "If observations are empty, verify the variable DCID via fetch_available_statistical_variables()."
Shorten or fold the Tips for Effective Use section into the relevant workflow steps so the body stays lean.
| Dimension | Reasoning | Score |
|---|---|---|
Conciseness | Mostly efficient with concrete code, but the Overview explains domain context Claude largely knows and inline "Common patterns" plus the seven-item Tips section duplicate material already covered by the reference files. | 2 / 3 |
Actionability | Provides fully executable install commands and copy-paste-ready Python examples for every endpoint, with specific parameter values and expected outputs. | 3 / 3 |
Workflow Clarity | The Typical Workflow is clearly sequenced (resolve → discover → query → process), but it lacks explicit validation or error-recovery checkpoints such as handling unresolved names or empty observation results. | 2 / 3 |
Progressive Disclosure | Offers a clear overview with well-signaled, one-level-deep references (observation.md, node.md, resolve.md, getting_started.md — all real files) and a dedicated Reference Documentation navigation section. | 3 / 3 |
Total | 10 / 12 Passed |