Content
100%Weight 40%Scale 1-3Reviews the quality of instructions and guidance provided to agents. Good implementation is clear, handles edge cases, and produces reliable results.
The body exemplifies progressive disclosure: a concise overview mapping each pattern to a one-line summary and a copy-paste skeleton, with complete implementations and the OpenAI-vs-Groq comparison cleanly offloaded to one-level-deep references. It is actionable, well-sequenced, and free of filler.
| Dimension | Reasoning | Score |
|---|---|---|
Conciseness | The body is a lean fast-map of one-line step summaries plus a single essential skeleton, adding Groq-specific knowledge (rate limits, queue_time metadata) rather than restating basics Claude already knows. | 3 / 3 |
Actionability | Provides a copy-paste-ready singleton skeleton, concrete executable examples for completion/streaming/Python, and specific status-code error guidance with full implementations one level deep in references. | 3 / 3 |
Workflow Clarity | The seven numbered steps form a clear layered build-up (client → wrapper → streaming → errors → retry → Python → multi-tenant), and safeComplete/withRetry supply explicit error-recovery feedback loops for API operations. | 3 / 3 |
Progressive Disclosure | SKILL.md is an overview pointing to three well-signaled, one-level-deep reference files (verified to exist and not nest further), with full implementations appropriately split out and easy step-indexed navigation. | 3 / 3 |
Total | 12 / 12 Passed |