Content
100%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 dense, well-structured operational skill: actionable tool calls and parameters, an explicit validation-gated procedure with recovery loops for destructive/batch operations, and a clean one-level reference split. No concept-padding and easy to navigate.
| Dimension | Reasoning | Score |
|---|---|---|
Conciseness | Lean and directive throughout — no padding about what data tables or CSVs are; every line is actionable guidance or decision rationale that changes behavior (e.g. "Keep nested JSON out of normal columns", "Infer conservatively"). | 5 / 5 |
Actionability | Fully executable instruction-only guidance: concrete tool calls (data-tables(action="list"), parse-file with maxRows=20), specific filter operators (eq/neq/like/gt/...), batch limits (100 rows), safety limits (10 pages), and exact column-naming/type rules. Specific examples cover the common cases. | 5 / 5 |
Workflow Clarity | A 6-step Default Procedure checklist with explicit validation checkpoints (inspect schema before writes/deletes, query matching rows first, show match count before broad mutations) and feedback loops (stop and report on admin block or denied approval) — meeting the destructive/batch bar rather than falling under the cap. | 5 / 5 |
Progressive Disclosure | Clear overview with well-signaled one-level-deep reference: the body holds core operational guidance while "Use references/data-table-playbook.md for tool recipes, schema patterns, import edge cases, and output examples" points to the verified reference file with a contents description. | 5 / 5 |
Total | 20 / 20 Passed |