Content
100%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 tightly written, highly actionable skill body: it provides executable REST and MCP workflows with exact tool signatures and a concrete error table, sequences multi-step flows with validation checkpoints and retry guidance, and pushes per-task detail into well-signaled reference files that all exist. It assumes Claude's competence and wastes few tokens.
| Dimension | Reasoning | Score |
|---|---|---|
Conciseness | Lean and efficient throughout: it assumes Claude's competence (no explanation of what a REST API, FASTA, or DNA language model is) and every section earns its tokens, with the brief intro serving as an orienting frame rather than padding. | 5 / 5 |
Actionability | Fully executable guidance: copy-paste REST Python with a reusable predict() helper, exact MCP tool signatures (e.g. fetch_gene_for_expression(gene=...), predict_expression(sequence_ref=<ref>, description=...)), precise length bounds, and an error-code table mapping each code to a concrete action. | 5 / 5 |
Workflow Clarity | Clear sequences with explicit checkpoints: the async annotation flow shows submit→get job_id→poll-until-200 with sleep and a terminal-state note, and the expression task enforces validation (exactly 9,198 bp + description) with feedback loops for 429 back-off/retry and 422 validation failures. | 5 / 5 |
Progressive Disclosure | SKILL.md is a clear overview with well-signaled, one-level-deep references to four real files (references/tasks.md, api-and-auth.md, mcp.md, sequence-acquisition.md), each described by what it contains, keeping the overview concise while routing detail off-page. | 5 / 5 |
Total | 20 / 20 Passed |