Content
78%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 content is highly actionable and well-structured with good progressive disclosure, but the repeated scope-discipline scaffolding across several sections adds redundancy that could be tightened.
Suggestions
Merge Scope Boundaries, Input Validation, Error Handling, and Stress-Case Rules into a single consolidated "Scope & Boundaries" section to reduce redundancy.
Add an explicit output-validation checkpoint to the Workflow (e.g. verify matched fellowships against the reference before returning) to strengthen the feedback loop.
Show a brief example of the expected output format rather than only describing it, to make the deliverable fully concrete.
| Dimension | Reasoning | Score |
|---|---|---|
Conciseness | The body is lean and avoids padding with concepts Claude already knows, but scope discipline is restated across Scope Boundaries, Input Validation, Error Handling, Stress-Case Rules, and Response Template, which could be consolidated. | 3 / 5 |
Actionability | Provides copy-paste-ready executable commands (python scripts/main.py with flags) plus complete parameter and field-normalization tables covering common cases, matching the fully-executable anchor. | 5 / 5 |
Workflow Clarity | A clear 5-step workflow includes a scope-validation checkpoint (step 2) and incomplete-input handling (step 5) with an error-handling fallback, but lacks an explicit output-validation feedback loop. | 4 / 5 |
Progressive Disclosure | The body is an overview with a well-signaled one-level-deep reference (references/fellowships.md) and a script, with fellowship detail appropriately split out, matching the clear-overview anchor. | 5 / 5 |
Total | 17 / 20 Passed |