Content
72%Reviews the quality of instructions and guidance provided to agents. Good implementation is clear, handles edge cases, and produces reliable results.
Well-structured and token-efficient with good progressive disclosure to real reference files. The main gaps are the lack of executable code in the body and missing validation feedback loops in the workflow.
Suggestions
Add a short executable SDL or resolver code snippet in the body so the core steps are copy-paste ready rather than only described.
Insert an explicit validation checkpoint (e.g. introspect/schema-validate the SDL, then fix and re-validate) into the workflow for schema design and resolver implementation.
Add a validate→fix→retry feedback loop around the integration-test step (step 9) to make error recovery explicit.
| Dimension | Reasoning | Score |
|---|---|---|
Conciseness | The body is lean and assumes GraphQL competence — it names libraries and concrete parameters (depth 7, complexity 1000) without explaining basic concepts, so every token earns its place. | 3 / 3 |
Actionability | Steps give specific library and parameter guidance, but the SKILL.md body contains no executable code or copy-paste commands — code lives in referenced files, leaving the main instructions descriptive rather than executable. | 2 / 3 |
Workflow Clarity | A clear 9-step sequence is present, but for complex/batch operations like schema design and authorization there are no explicit validation checkpoints or validate→fix→retry feedback loops in the main flow. | 2 / 3 |
Progressive Disclosure | A concise overview points to one-level-deep, well-signaled references (implementation.md, errors.md, examples.md), all of which are real bundle files, with content appropriately split. | 3 / 3 |
Total | 10 / 12 Passed |