Content
100%Reviews the quality of instructions and guidance provided to agents. Good implementation is clear, handles edge cases, and produces reliable results.
The body is a well-structured, lean instruction set with concrete parameters, a sequenced workflow with validation feedback loops, and clean one-level-deep references to real files. It assumes Claude's competence and keeps detail behind clearly signaled references. No suggestions needed.
| Dimension | Reasoning | Score |
|---|---|---|
Conciseness | The body is lean and instructional throughout, assuming Claude's competence without explaining what calls, transcripts, or coaching are; every section (workflow steps, rules, output format) earns its place with no padded concept explanations. | 3 / 3 |
Actionability | Concrete executable guidance is pervasive: "limit of about 25 per slice", "score_threshold=0", "three non-overlapping slices: 0-30 days, 31-60 days, and 61-90 days", "three coaching actions" each with a skill, if/then play, 5-10 minute drill, and observable check, plus a copy-paste-ready output format template. | 3 / 3 |
Workflow Clarity | A clear five-step sequence (Resolve -> Collect -> Compare -> Fetch validation -> Turn into action) with explicit validation checkpoints and error-recovery feedback loops: sparse-sample handling, "return a limited trend readout rather than overgeneralizing", and a dedicated Failure Handling section naming the smallest missing input. | 3 / 3 |
Progressive Disclosure | SKILL.md acts as a concise overview with well-signaled, one-level-deep references to real bundle files (references/request-schema.yaml for input normalization and references/rubric.md for behavior categories), each gated to "when their extra detail matters"; no nested reference chains. | 3 / 3 |
Total | 12 / 12 Passed |