Content
78%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, actionable playbook: executable SQL/Python templates, a sequenced architecture, an explicit 12-consideration checklist with validation checkpoints, and exemplary progressive disclosure to real one-level reference files. The main improvement areas are trimming narrative sections and making the CUPED/notebook snippets fully executable.
Suggestions
Trim the introductory platform discussion, the 'What this skill is for' sibling listing, and the 'Closing' section to reduce token cost without losing operational guidance.
Replace pseudocode in the CUPED section (pre_period_revenue, undefined metric arrays) with a runnable pandas/numpy snippet that loads pre-period and experiment-period metrics from the warehouse.
Add an explicit validate-retry loop for the SRM check (e.g., 'if SRM p-value < 0.001, stop, audit assignment hash and exposure log, then re-run') to make the framework's checkpoints into feedback loops.
| Dimension | Reasoning | Score |
|---|---|---|
Conciseness | The sections are dense with non-obvious domain guidance (exposure-fire timing, salt isolation, SRM discipline) rather than concepts Claude already knows, but the introductory platform discussion, the sibling-skill listing in 'What this skill is for', and the essayistic 'Closing' section are padding that could be trimmed. Efficient overall with minor over-explanation, so 4 rather than 5. | 4 / 5 |
Actionability | Most guidance is executable: working SQL for hash assignment, the dbt metric model, and the Welch t-test, plus runnable Python for t-tests and power analysis. Minor gaps remain — the CUPED snippet uses undefined pseudocode ('pre = pre_period_revenue(user_id)', 'warehouse.query(...)') and the flag-service SQL references a hypothetical table — keeping it below fully copy-paste-ready. | 4 / 5 |
Workflow Clarity | The architecture section gives a clear data-flow sequence, and the 12-consideration framework provides a checklist with explicit validation checkpoints (SRM check before computing any metric, pre-registered stop criteria, power analysis before running). It falls short of 5 because error-recovery loops (e.g., 'if SRM fails, fix and re-check') are named as pitfalls rather than wired into an explicit validate-retry sequence. | 4 / 5 |
Progressive Disclosure | The body is a well-organized overview with all detail pushed to 8 real, one-level-deep reference files, each signaled inline at the end of its section and consolidated in an annotated 'Reference files' section. All referenced paths exist in the bundle, and navigation is easy. | 5 / 5 |
Total | 17 / 20 Passed |