Content
81%Weight 40%Scale 1-5Reviews the quality of instructions and guidance provided to agents. Good implementation is clear, handles edge cases, and produces reliable results.
The body is highly actionable with complete executable examples and a well-sequenced, validation-backed workflow including a retry feedback loop. Conciseness is the main weakness due to some explanatory prose that assumes less competence than Claude has.
Suggestions
Trim explanatory asides that restate what Claude already knows (e.g. the 'bare sentiment: str' contrast in step 4) to push conciseness toward 4-5.
Consider moving the per-provider schema snippets or the Edge Cases into a reference file so the SKILL.md overview stays leaner.
The Examples are strong; keep them but ensure surrounding prose does not re-explain library basics.
| Dimension | Reasoning | Score |
|---|---|---|
Conciseness | Mostly efficient with concrete code and well-organized sections, but includes some over-explanatory prose Claude already knows (e.g. 'Models use these descriptions as implicit prompt instructions — a field described as… produces better results than a bare sentiment: str'). | 3 / 5 |
Actionability | Three complete, copy-paste-ready executable examples (OpenAI+Pydantic, Anthropic tool_use, TypeScript+Zod) plus concrete per-step guidance cover the common provider cases fully. | 5 / 5 |
Workflow Clarity | A 10-step sequenced Core Workflow includes an explicit validation step (step 8) and a retry feedback loop (step 9: send error back, cap at 3), matching the anchor for clear sequence with validation and error-recovery loops. | 5 / 5 |
Progressive Disclosure | Content is cleanly partitioned into well-signaled sections (When to Use, Core Workflow, Examples, Never Do This, Edge Cases, Best Practices) with no nested references, though some material (provider-specific details, examples) is inlined rather than split into reference files. | 4 / 5 |
Total | 17 / 20 Passed |