Content
85%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 highly actionable with executable commands, explicit validation checkpoints, and clean single-script organization. The main weakness is redundant structural sections that restate scope and output requirements.
Suggestions
Consolidate the overlapping 'Input Validation', 'Output Requirements', 'Stress-Case Rules', and 'Response Template' sections to reduce boilerplate and tighten token efficiency.
If the redundant sections are intentional for audit framing, mark them as cross-references to the canonical Workflow/Error Handling sections instead of restating.
| Dimension | Reasoning | Score |
|---|---|---|
Conciseness | Commands, tables, and examples are mostly efficient, but 'Input Validation', 'Output Requirements', 'Stress-Case Rules', and 'Response Template' overlap with the Workflow and Error Handling sections, adding boilerplate that could be tightened. | 3 / 5 |
Actionability | Copy-paste-ready commands like 'python scripts/main.py --add "Pipette P100" --calibration-date 2024-01-15 --interval 12' plus a full parameter table and JSON output example cover the common cases fully. | 5 / 5 |
Workflow Clarity | The numbered Workflow includes explicit validation ('stop early if unsupported assumptions', 'switch to fallback path') and the Error Handling section gives date-format, missing-field, not-found, and scope-violation feedback loops for destructive/batch operations. | 5 / 5 |
Progressive Disclosure | A single bundled script scripts/main.py is accurately referenced and well-sectioned with no nested references; appropriate one-level structure for a single-script skill. | 5 / 5 |
Total | 18 / 20 Passed |