Content
70%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 delivers an exceptionally clear sequenced workflow with real validation gates, executable code, and useful templates. Its weaknesses are token weight — textbook ML explanations and two large inlined tables that belong in reference files — and the absence of any progressive-disclosure bundle structure.
Suggestions
Move the "Reuse the SWE Surface" and "Ten MLE Task Simulations" tables into a references/ file (e.g. references/ecc-surface-mapping.md), keeping only a 3–5 line summary and a clearly signaled link in SKILL.md.
Cut sections that restate ML fundamentals Claude already knows — the precision/recall/F1/AUC guidance in "Metric and Mistake Economics" and the missing-values/outliers/imbalance bullets in "Data and Feature Hypotheses" — down to the non-obvious project-specific rules (mistake economics framing, leakage checks, train/serve equivalence).
Add executable snippets or commands for the lanes that currently have only prose direction — e.g. a point-in-time join check, a train/serve feature-equivalence test, and a drift-check command — to match the standard set by the promotion-gate example.
| Dimension | Reasoning | Score |
|---|---|---|
Conciseness | Mostly efficient bullet and checklist form, but sections like "Favor precision when the cost of an incorrect positive decision dominates" and the missing-values/outliers/imbalance bullets in "Data and Feature Hypotheses" restate ML fundamentals Claude already knows, and the two dense 10–20 row tables add bulk that could be tightened. Not a 2 because the prose is compact rather than padded. | 3 / 5 |
Actionability | Two complete, executable Python examples (frozen dataclass with artifact naming, promotion-gate assertion that fails closed) plus copy-paste templates (Iteration Compact, Observation Ledger) and concrete contract field lists. Most lanes are actionable, but the eval, serving, and monitoring steps get directive prose with no commands or code, leaving minor gaps versus the fully copy-paste-ready 5 anchor. | 4 / 5 |
Workflow Clarity | The Core Workflow is a clearly numbered six-step sequence (prediction contract, data contract, reproducible pipeline, evaluate before promotion, package for serving, operate) with explicit validation ("Promotion gates are automated and fail closed", "do not ship" thresholds, equivalence tests), a feedback loop (mistake → cluster → hypothesis → experiment → evidence), a 12-item Review Checklist, and named rollback triggers — matching the anchor with validation steps, error-recovery loops, and checklists. | 5 / 5 |
Progressive Disclosure | A single ~340-line SKILL.md with no bundle files; the 20-row "Reuse the SWE Surface" table and 10-row "Ten MLE Task Simulations" table are reference material inlined in the overview rather than split into one-level-deep reference files. Section headers keep it above a 2, but content that clearly belongs in separate files is inline, fitting the 3 anchor. | 3 / 5 |
Total | 15 / 20 Passed |