Content
88%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.
A highly actionable, well-sequenced scaffolding procedure with concrete commands, executable code, explicit validation checkpoints, and recovery loops. Its only weaknesses are minor conciseness padding (internal friction IDs) and a progressive-disclosure design that, while well-signaled, inlines a lot of detail and rests on references that are not bundled here.
| Dimension | Reasoning | Score |
|---|---|---|
Conciseness | Dense and mostly load-bearing — concrete commands, SQL, version-pinned deps, and a copy-paste agent.py — with only minor trimmable padding such as internal friction IDs ('v3 friction P0-V3-N4') and a few rationale sentences, so it is efficient but not perfectly lean. | 4 / 5 |
Actionability | Fully executable guidance throughout: exact CLI commands (onnx2oracle load ... --name MY_MINILM_V1 --dsn ...), ready-to-run SQL smoke checks, a complete copy-paste 2-step agent.py pipeline, and precise file paths/deps covering the common per-idea cases. | 5 / 5 |
Workflow Clarity | Clear sequenced procedure (Steps 0–5 with 3a/3b/3c sub-steps) plus explicit validation checkpoints ('Refuse if target_dir is non-empty', 'Block until OK', expected 'verify: OK'), a feedback loop (shared/verify.md recovery, max 3 retries), and a Stop conditions checklist for error recovery. | 5 / 5 |
Progressive Disclosure | Well-sectioned body with clearly signaled, one-level-deep references to specialized materials (shared/references, shared/snippets, shared/templates, building-block skills), but it inlines substantial detail (full agent.py code, the resolve-choices table, per-idea seeding) and no bundle files are present to confirm the referenced paths resolve, so it is not the lean overview-with-delegation anchor 5. | 4 / 5 |
Total | 18 / 20 Passed |