Content
92%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 action-first with executable commands, a clearly sequenced multi-stage workflow, explicit validation/halt checkpoints, and a well-organized single-script bundle. Only minor conciseness slack comes from the legacy Ralph-loop comparison.
Suggestions
Consider condensing or removing the 'UX note' about the retired Ralph loop; it is historical context rather than operational guidance and adds tokens Claude does not need to act.
| Dimension | Reasoning | Score |
|---|---|---|
Conciseness | The body is lean — executable commands up front, terse stage list, compact Safety/Notes — but the 'UX note' paragraph comparing the retired Ralph loop is contextual lore that could be trimmed without losing operational clarity. | 4 / 5 |
Actionability | Copy-paste-ready commands cover the common cases (new loop with args, --resume, --until implement, --validate) and each flag's effect is stated concretely, e.g. '`--until implement` runs plan → implement and stops once validations are green...'. | 5 / 5 |
Workflow Clarity | The plan → implement → pr → review → cycle sequence is explicit, with validation checkpoints (VALIDATION: GREEN sentinel, authoritative --validate, halt conditions on no-progress/failed push/dirty review) and a bounded review→fix feedback loop for this batch/autonomous operation. | 5 / 5 |
Progressive Disclosure | A single bundled script (scripts/prp_loop.py, verified present) is referenced one level deep and appropriately signaled, and the body is organized into clear sections (Run it, Stop after a stage, What it does, Safety, Notes) well within the simple-skill threshold. | 5 / 5 |
Total | 19 / 20 Passed |