Content
86%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 concise, well-structured skill body that assumes Claude's competence and points at concrete identifiers. It sequences the Auto-batching workflow with validation steps and organizes content cleanly, with only minor room to add executable examples and an explicit retry loop.
| Dimension | Reasoning | Score |
|---|---|---|
Conciseness | Lean and efficient with no padding or explanation of concepts Claude already knows; every line earns its place using concrete identifiers like `snapshotCells()` and `autoSuggestionQueue`. | 5 / 5 |
Actionability | Concrete, specific guidance referencing real function names and schemas (`AUTO_SUGGESTIONS_SCHEMA`, `adaptAutoSuggestionToCell(action, x, z)`, `normalizeAutoAction`), but no executable code examples, which is acceptable for an instruction-only skill yet leaves minor gaps. | 4 / 5 |
Workflow Clarity | The 'Current intended model' section sequences capture→ask→spend→refresh→place, and a dedicated Validation section verifies the stub-once and no-network behaviors; minor gap is the absence of an explicit fix→retry feedback loop. | 4 / 5 |
Progressive Disclosure | Under 50 lines with no external references needed; content is organized into three clear, well-signaled sections (intended model, guardrails, validation), meeting the simple-skill exception for a top score. | 5 / 5 |
Total | 18 / 20 Passed |