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 body is a lean, well-structured overview with concrete executable commands and genuine safety/validation gates baked into the described evolution loop. It assumes Claude's intelligence and defers deep detail to external package docs, scoring strongly across all dimensions.
| Dimension | Reasoning | Score |
|---|---|---|
Conciseness | The body is dense and information-rich with no basic-concept padding; the benchmarks section is lengthy but consists of measured insights rather than filler, with only minor trims possible. Time-sensitive stats (7.7% -> 15.3%, 31x cheaper) are confined to a dedicated 'What the benchmarks taught us' section that defers full evidence to LEARNINGS.md, so they do not unduly penalize conciseness. | 4 / 5 |
Actionability | It provides copy-paste-ready commands (`npm run evolve`, `npm run evolve:dry`, the `npx` invocation with concrete flags) covering the common cases, with only minor gaps around the advanced selection/statistical flags being mentioned but not demonstrated. | 4 / 5 |
Workflow Clarity | The internal loop (mutate one surface file -> sandbox -> score -> keep only measurably-improving variants) is a clear sequence backed by explicit validation checkpoints (validateGeneratedCode gate, tests must pass, measured-improvement promotion guard), with only minor gaps in presenting it as an explicit numbered user workflow. | 4 / 5 |
Progressive Disclosure | The body is a concise overview (~40 lines) organized into clear sections (Run it, Safety, benchmarks) with well-signaled one-level-deep references to `@metaharness/darwin` and its LEARNINGS.md / bench/results/RESULTS.md for advanced detail; no local bundle files are needed. | 5 / 5 |
Total | 17 / 20 Passed |