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.
An exemplary instruction-only skill: lean, imperative, and sequenced with an explicit evidence-verification gate and a precise component routing table to real reference files. The remaining gaps are minor — no mechanics for obtaining the diff or example finding format, and framework-specific frontend references require one extra navigation hop.
| Dimension | Reasoning | Score |
|---|---|---|
Conciseness | The body is lean and purely operational: it never explains concepts Claude already knows (no OpenVINO primers, no library tutorials), and every line — the workflow, conditional modes, priority checklist, and routing table — carries task-specific instruction. This matches the 5 anchor: every token earns its place. | 5 / 5 |
Actionability | Guidance is consistently concrete and imperative — exact path globs ("src/common/transformations/", "tests/layer_tests/"), explicit directives ("Require validation before unsafe arithmetic", "prefer fail-fast errors"), and a defined finding format. It falls short of the 5 anchor because it omits concrete mechanics such as commands for fetching the diff or an example of a well-formed finding. | 4 / 5 |
Workflow Clarity | The numbered four-step review workflow includes an explicit verification gate ("Before reporting a finding, confirm that the claimed problem exists in the source code... If the available evidence does not establish a defect, omit the finding"), a feedback loop against false positives, plus conditional modes and a priority checklist — matching the 5 anchor's explicit validation, error recovery, and checklist criteria. | 5 / 5 |
Progressive Disclosure | The body is a well-organized overview with a clear component-routing table, and all six referenced files (runtime, transformations, plugins, frontend, bindings, ci) exist in references/. It sits between the 4 and 5 anchors: onnx.md and pytorch.md are only reachable via a second hop through frontend.md, and the table does not route src/frontends/onnx/ or PyTorch decoder paths directly to their framework-specific references. | 4 / 5 |
Total | 18 / 20 Passed |