Content
72%Reviews the quality of instructions and guidance provided to agents. Good implementation is clear, handles edge cases, and produces reliable results.
A well-structured, actionable skill with executable code and clean one-level reference navigation. It is held back by section redundancy and a lack of explicit validation checkpoints in its batch and multi-step workflows.
Suggestions
De-duplicate the 'When to Use' list against the per-capability 'Common Use Cases' blocks to tighten token usage.
Add explicit validate/retry checkpoints to the batch and multi-step pipeline patterns (e.g., check job state, handle failures before proceeding) so workflow clarity can score higher.
Trim the generic 'Best Practices' list to DNAnexus-specific guidance that Claude would not already infer.
| Dimension | Reasoning | Score |
|---|---|---|
Conciseness | Mostly efficient and avoids explaining concepts Claude already knows, but the 'When to Use' list overlaps the 'Core Capabilities' sections, each capability repeats a 'Common Use Cases' block, and the generic 10-item 'Best Practices' list adds padding that could be trimmed. | 2 / 3 |
Actionability | Provides multiple complete, executable dxpy code examples (upload/run/download, search, app entry point, batch, multi-step pipeline, data organization) plus concrete install/login commands — copy-paste ready. | 3 / 3 |
Workflow Clarity | A clear decision tree routes tasks and the pipeline example chains jobs, but batch/destructive operations lack explicit validation or failure-handling checkpoints, capping workflow clarity at 2 per the rubric's feedback-loop guideline. | 2 / 3 |
Progressive Disclosure | The body is an overview that points to five real, one-level-deep reference files (verified in references/), each clearly signaled with a 'See references/X.md for:' list, enabling easy navigation. | 3 / 3 |
Total | 10 / 12 Passed |