Content
87%Reviews the quality of instructions and guidance provided to agents. Good implementation is clear, handles edge cases, and produces reliable results.
A well-structured overview that uses token-efficient tables, actionable URLs, and a clean one-level reference hierarchy covering all linked protocols. Its one weakness is the ordering workflow, which lists steps but omits the explicit verification and feedback-loop checkpoints that a high-stakes batch submission warrants.
Suggestions
Add an explicit input-verification checkpoint before submission in the ordering workflow (e.g., confirm every sequence/sample in the uploaded template matches the configured count and passes FASTA/CSV format checks).
Add a brief validate→fix→resubmit feedback loop describing what to do when Ginkgo's feasibility report rejects inputs or returns a price/turnaround different from the catalog quote.
Note a pre-submit cost check (replicates × price × samples) so users confirm the quote before adding to cart, treating the order as the batch/destructive operation it is.
| Dimension | Reasoning | Score |
|---|---|---|
Conciseness | A lean catalog of tables, a decision guide, a numbered ordering flow, and compact infrastructure notes; it does not explain concepts Claude already knows and every section earns its place. | 3 / 3 |
Actionability | Gives concrete URLs, exact input file types (FASTA/CSV/XLSX), specific prices/turnarounds per protocol, and a precise 5-step ordering workflow rather than abstract direction. | 3 / 3 |
Workflow Clarity | The ordering workflow is a clear numbered sequence but lacks explicit input-verification checkpoints and a validate→fix→resubmit feedback loop; for a batch submission to an external lab this gap caps clarity below 3. | 2 / 3 |
Progressive Disclosure | SKILL.md is a concise overview whose catalog links each protocol to a one-level-deep reference file; all 17 referenced files resolve and content is appropriately split for navigation. | 3 / 3 |
Total | 11 / 12 Passed |