Content
50%Reviews the quality of instructions and guidance provided to agents. Good implementation is clear, handles edge cases, and produces reliable results.
The body is information-rich and domain-specific with concrete analysis code, but is weakened by a non-executable placeholder URL, missing workflow validation checkpoints, and an orphaned reference file that is never surfaced from the main document.
Suggestions
Replace the literal "..." figshare placeholder URL with a concrete, working download link so the download code is executable as written.
Add explicit validation/verification checkpoints to the workflows (e.g., confirm cell-line alignment, check n before statistical tests, apply FDR correction and flag when it changes significance).
Link to references/dependency_analysis.md from the body (e.g., under Core Concepts) so the existing reference file is discoverable rather than orphaned.
| Dimension | Reasoning | Score |
|---|---|---|
Conciseness | The ~290-line body is mostly operational domain content (thresholds, file names, code) but includes explanation Claude largely knows (Overview prose, "Co-essential genes often share biological complexes or pathways"), so it is efficient overall yet could be tightened. | 2 / 3 |
Actionability | Substantial concrete pandas code is provided, but a non-executable placeholder URL ("figshare.com/ndownloader/files/...") and live API endpoints ("/gene", "/data/gene_dependency") of uncertain accuracy prevent full copy-paste readiness. | 2 / 3 |
Workflow Clarity | Three workflows are sequenced as numbered steps, but none include validation or verification checkpoints for batch/genome-wide operations, which the rubric caps at 2. | 2 / 3 |
Progressive Disclosure | A references/dependency_analysis.md bundle exists but is never linked from the body, and the ~290-line body inlines API and file-reference tables that could be split out, so structure is present but the reference is not signaled. | 2 / 3 |
Total | 8 / 12 Passed |