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 strong, dense body: fully executable commands, a sequenced workflow with real validation feedback loops, and clean one-level progressive disclosure into verified bundle files. The only weakness is conciseness — scattered version/date provenance and a few redundant sentences could be trimmed.
Suggestions
Consolidate the pinned-version and last-tested provenance (Python 3.12, pycalphad 0.11.2, NumPy 2.5.3, 2026-10-01) into a single short line or the frontmatter metadata instead of repeating it across the 'Execute the tested example' and 'Boundaries and upstream contracts' sections.
Cut the redundant restatement "It does not silently remove requested phases" — the preceding sentence ("incompatible or automatically filtered order/disorder phase sets produce an explicit error") already conveys it.
Tighten the upstream-drift paragraph to its essential warning (latest docs describe 0.11.3 dev builds; helper verified against stable 0.11.2), dropping the source-vs-wheel checking detail.
| Dimension | Reasoning | Score |
|---|---|---|
Conciseness | The body is dense and skill-specific — no explaining of concepts Claude already knows, and version-specific facts ("pycalphad clips independent mole fractions to [1e-10, 1-1e-10]") earn their tokens. Below score 5 because time-sensitive material ("Tested on Python 3.12, pycalphad 0.11.2, and NumPy 2.5.3", "exercised against stable 0.11.2 on 2026-10-01", "Upstream latest documentation currently describes 0.11.3 development builds") is woven through the body rather than isolated, and a few sentences are trimmable ("It does not silently remove requested phases" restates the prior sentence). | 4 / 5 |
Actionability | Fully executable, copy-paste-ready command with pinned versions and exact paths (uv run ... scripts/equilibrate.py ... ideal-cu-ni.tdb ... equilibrium.json equilibrium-result), a concrete settings file to copy, and an expected-results table covering the common case (900/1100/1300 K with phase fractions and X(Ni) values). Not score 4 because no key execution detail is missing. | 5 / 5 |
Workflow Clarity | The six-step workflow is clearly sequenced with explicit validation checkpoints and feedback loops: "Check finite Gibbs energies, phase fractions summing to one, reconstructed bulk composition, and stability to doubled pdens. Near transitions, refine temperatures and sampling density further." Failures are surfaced ("Failed checks remain visible in the report rather than being relabeled as convergence"), and step 6 is a delivery checklist. Matches the anchor-5 validate/fix/retry pattern. | 5 / 5 |
Progressive Disclosure | SKILL.md is an organized overview with well-signaled, one-level-deep references that all exist in the bundle: [references/model-and-validation.md], [assets/ideal-cu-ni.tdb], [assets/equilibrium.json], plus scripts/equilibrate.py invoked by the exact command. Deep material (native Model/Workspace contracts, miscibility-gap handling) is correctly pushed to the reference file, not inlined. | 5 / 5 |
Total | 19 / 20 Passed |