Content
72%Reviews the quality of instructions and guidance provided to agents. Good implementation is clear, handles edge cases, and produces reliable results.
A tight, well-organized body that conveys the batching design and guardrails without wasted tokens. It would benefit from more executable detail on the key functions and an explicit feedback loop for the batched-inference workflow.
Suggestions
Add brief signatures/usage for the key functions (e.g. snapshotCells(), normalizeAutoAction, adaptAutoSuggestionToCell) so guidance is executable rather than name-only.
Insert an explicit validate->fix->retry checkpoint into the Auto refresh flow, since it is a batch operation where the model output is applied repeatedly.
| Dimension | Reasoning | Score |
|---|---|---|
Conciseness | Lean and efficient — it jumps straight into the intended model and guardrails with named functions and constants, assuming Claude's competence and avoiding padding or concept explanations. | 3 / 3 |
Actionability | Names concrete functions and constants (snapshotCells(), autoSuggestionQueue, normalizeAutoAction, adaptAutoSuggestionToCell) but gives no executable signatures or code, leaving key call details implicit rather than copy-paste ready. | 2 / 3 |
Workflow Clarity | The intended-model steps are sequenced and a validation section exists, but it describes a batch operation without explicit validate->fix->retry checkpoints inside the run flow, capping workflow clarity at 2 per the batch-operations guideline. | 2 / 3 |
Progressive Disclosure | Well under 50 lines with no external references needed; content is organized into clearly labeled sections (intended model, guardrails, validation), which scores 3 for simple skills per the rubric notes. | 3 / 3 |
Total | 10 / 12 Passed |