Content
75%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 a well-structured, actionable reference of named decision frameworks with concrete scales, formulas, and worked examples. It is efficient and clearly sequenced, with only minor opportunities to tighten length and add explicit validation checkpoints.
Suggestions
Tighten the Examples and Trigger Phrases sections, or move the worked examples into a separate references file, to reduce token load.
Add an explicit validation/checkpoint step in the Step-by-Step workflow (e.g., 're-score after confirming must-haves') to make the feedback loop explicit.
Make Step 3 ('Collect the Data') more concrete by specifying how to label and weight assumptions versus objective data.
| Dimension | Reasoning | Score |
|---|---|---|
Conciseness | The body is well-organized and avoids explaining concepts Claude already knows, but at ~225 lines the worked examples and trigger-phrase table could be trimmed without losing clarity. | 4 / 5 |
Actionability | Concrete scales (weights 1-5, scores 1-10), an explicit ICE formula, and worked examples with real numbers make the guidance actionable, though a few steps like 'Collect the Data' remain high-level. | 4 / 5 |
Workflow Clarity | A clear 7-step sequence is paired with a 'Quality checks' checklist and bias-mitigation table; validation is implicit rather than an explicit checkpoint, but the skill is non-destructive so no cap applies. | 4 / 5 |
Progressive Disclosure | Sections are well-signaled and self-contained with no nested references, though the six frameworks and examples could optionally be split into one-level-deep reference files. | 4 / 5 |
Total | 16 / 20 Passed |