Content
80%Reviews 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 and token-efficient, with executable code for every sub-command and clear output formats. Its weaknesses are the absence of validation/feedback loops around write operations and a monolithic structure with no progressive disclosure into reference files.
Suggestions
Add an explicit validation step after 'record' and 'exception' (e.g. re-query the decision_id to confirm it was persisted) to introduce a feedback loop for write operations.
Split the per-sub-command API detail into a referenced file (e.g. DECISION_API.md) and keep SKILL.md as a concise overview with one-level-deep links.
Factor out the repeated AgentContext setup into a short shared snippet so each section stays copy-paste ready without the boilerplate repetition.
| Dimension | Reasoning | Score |
|---|---|---|
Conciseness | The body is lean: minimal prose, executable code blocks, and inline comments that earn their place, with no padding explaining concepts Claude already knows; it assumes competence throughout. | 3 / 3 |
Actionability | Each sub-command ships concrete, copy-paste-ready Python with real imports, method calls, arguments, and a stated output format — fully executable rather than pseudocode. | 3 / 3 |
Workflow Clarity | Sub-commands are independently clear but write operations ('record', 'exception') lack any validation or verification checkpoints, so per the rubric workflow clarity is capped at 2 for destructive/batch-style operations. | 2 / 3 |
Progressive Disclosure | The file is a well-sectioned single document (~190 lines, no bundle files) but everything is inline with no quick-start/advanced split or one-level-deep references, so it stops at 'some structure' rather than a true overview-with-references layout. | 2 / 3 |
Total | 10 / 12 Passed |