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.
A well-structured, actionable instruction skill with a clear sequenced workflow, explicit validation, and properly separated references. The main improvement area is tightening repetitive disambiguation guidance to improve token efficiency.
Suggestions
Consolidate the repeated clarification/ask-the-user bullets in 'Resolve the rep and comparison basis' into a single decision rule to reduce token cost.
Consider moving the detailed behavior-category list in Step 3 wholly into references/rubric.md and keeping only the core categories inline, since the rubric already covers the technical extensions.
The Output Format block is long; a brief pointer to a compact template could let the body focus on workflow logic, though the current inline template is genuinely copy-paste ready.
| Dimension | Reasoning | Score |
|---|---|---|
Conciseness | The body is dense and task-specific without explaining concepts Claude already knows, though several repetitive disambiguation bullets in Step 1 could be tightened. | 4 / 5 |
Actionability | Concrete guidance throughout — fixed limits (25/slice, 30-60 calls, score_threshold=0), explicit time slices, a copy-paste output template, and exactly-three coaching actions each with skill/if-then/drill/check — with minor reliance on judgment calls. | 4 / 5 |
Workflow Clarity | A clearly sequenced 5-step workflow with an explicit validation checkpoint (Step 4) and a failure-handling/limited-readout feedback loop for sparse or uneven samples. | 5 / 5 |
Progressive Disclosure | SKILL.md owns the workflow while two clearly signaled, one-level-deep references (request-schema.yaml, rubric.md) hold the extra detail; the body is well-sectioned but dense enough that minor organization gaps remain. | 4 / 5 |
Total | 17 / 20 Passed |