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.
A well-structured, highly actionable skill body with strong validation checkpoints, real executable examples, and clean progressive disclosure into verified reference files. The only dimension below the top is conciseness, owing to version-pinned dated detail and a few sections that could be tightened.
| Dimension | Reasoning | Score |
|---|---|---|
Conciseness | Mostly lean and assumes Claude's competence; the safety and intake content is domain-specific rather than padded, but there are minor trim opportunities and version-pinned dated information (0.2.1, 2026-03-23, 2026-07-23) that is contained in dedicated snapshot/source sections yet still adds tokens. | 4 / 5 |
Actionability | Fully executable guidance: copy-paste `uv venv`/`uv pip install` commands, five concrete CLI invocations with flags, and a complete runnable Python example with real PyLabRobot imports covering the common software-only case. | 5 / 5 |
Workflow Clarity | Clear sequenced offline workflow with an explicit validation chain (validate_manifest, check_deck_geometry, plan_transfers volume/capacity checks, inspect_backends --strict), checklists (required intake, six-step operator gate), and an error path (produce an assumptions/blockers list and offline draft when info is missing), so the destructive-operation cap does not apply. | 5 / 5 |
Progressive Disclosure | Overview body points to six well-signaled one-level-deep references (all verified to exist), a schema asset, and bundled scripts, each annotated with its scope; no nested reference chains. | 5 / 5 |
Total | 19 / 20 Passed |