Content
90%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 concise, executable, and well-structured with explicit validation gates for the git automation. Adding an explicit verify/retry feedback loop for the MOC generation itself and optionally externalizing shared config derivation would lift it to top marks.
Suggestions
Add an explicit validation/retry step after generation (e.g., verify the generated MOC files exist and are non-empty before reporting) to form a full feedback loop.
Consider moving the shared config-derivation logic (variable definitions in Step 0) into a referenced _shared file so the body stays a pure overview.
| Dimension | Reasoning | Score |
|---|---|---|
Conciseness | The body is lean and fully operational: it lists config variables compactly, gives executable commands, and never explains concepts Claude already knows; every line earns its place. | 5 / 5 |
Actionability | Provides concrete, copy-paste-ready commands (python3 ../_shared/generate_concept_mocs.py, generate_paper_mocs.py) with explicit config file paths covering the common cases. | 5 / 5 |
Workflow Clarity | Steps are clearly sequenced (Step 0 config → execution → reporting) and the git section has explicit validation gates (.git existence, staged-change check), but there is no explicit validate-and-retry feedback loop for the generation itself, leaving a minor validation gap. | 4 / 5 |
Progressive Disclosure | The body is well-organized into clear sections and is appropriately self-contained (no bundle files exist), but the inline config-derivation block could arguably live in a shared reference; structure is good with minor organization gaps. | 4 / 5 |
Total | 18 / 20 Passed |