Content
63%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-sequenced, code-first workflow with strong validation checkpoints and an explicit completeness checklist, undermined by a bloated inlined data-source catalog that belongs in a references/ file. The core Steps 1-9 are lean and actionable; the tool-listing sections drag conciseness and structure down.
Suggestions
Move the data-source catalog (euhealth, DiseaseSh, WHO GHO, WAQI, health_disparities sections) into a references/ file such as references/data-sources.md, keeping one-line pointers per source in the body so Step 2 stays lean.
Trim the inline enumeration of ~20 euhealth tool names and the repeated 'verified live' claims; retain only the shared parameter shape, response shape, and gotchas that change behavior.
Relocate the time-sensitive euhealth setup state ('as of this writing, these tools return {"warning": ...}') into a clearly marked 'Setup / known issues' section so the mainline workflow doesn't carry dated information.
| Dimension | Reasoning | Score |
|---|---|---|
Conciseness | The nine workflow steps are lean — code plus one-line decision rules ('complete case if <5% missing; multiple imputation if 5-20%') — but the ~35-line inlined tool catalog (euhealth's enumerated 20 tool names, DiseaseSh, WHO GHO, WAQI, health_disparities) is padded with repeated 'verified live' assertions and dense single-paragraph prose that could be tightened. 'as of this writing' time-sensitive setup state further inflates the mainline body. | 3 / 5 |
Actionability | Mostly executable guidance: a working power-analysis function, a multi-format download helper, sequential regression models printing ORs with 95% CIs, VIF checks, and stratified sensitivity code with try/except. Minor gaps: placeholders like '[exposure] [outcome] [study design]', 'url1', and 'adapt to your variables' are inherent to a domain-generic skill but keep it just short of copy-paste-ready for a concrete case. | 4 / 5 |
Workflow Clarity | A clearly sequenced 9-step process with real checkpoints — power analysis before committing to a dataset, study-design check against temporality, missing-data thresholds, VIF assumption checks, the euhealth 'check for the datastore warning before treating empty as no-match' guard, and a final completeness checklist. Falls short of anchor 5 because the validation steps lack fix-and-retry feedback loops (e.g., no guidance on what to do when a model fails to converge outside the stratified try/except). | 4 / 5 |
Progressive Disclosure | The step headings give good in-file structure, but no references/, scripts/, or assets/ exist and ~40% of the body (the data-source catalog at lines 105-141) is exactly the content that belongs in a separate reference file with one-line pointers from the body. Matches anchor 3: 'some structure but content that should be separate is inline'. | 3 / 5 |
Total | 14 / 20 Passed |