Content
82%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-organized, highly actionable pipeline skill with executable examples and clear phase sequencing. The main gap is the absence of an explicit validation feedback loop for batch prediction steps.
Suggestions
Add an explicit validate→fix→retry checkpoint in Phase 1/Phase 3 (e.g., re-run binding prediction or coverage calc if the selected epitope set falls below the coverage threshold) to strengthen workflow_clarity.
Tighten the Reasoning Strategy paragraph by trimming explanatory sentences that restate domain knowledge Claude already has, improving token efficiency.
Consider moving the detailed HLA supertype allele lists and IC50 interpretation tables into a bundled reference file to keep SKILL.md as a leaner overview.
| Dimension | Reasoning | Score |
|---|---|---|
Conciseness | Mostly efficient with a tool table and executable code blocks per phase; the Reasoning Strategy and evidence-grading prose add some length beyond strict necessity, though it is domain-specific rather than generic padding. | 4 / 5 |
Actionability | Fully executable copy-paste-ready tool calls with real parameters, allele lists, percentile/IC50 thresholds, and interpretation tables covering the common cases across all six phases. | 5 / 5 |
Workflow Clarity | Clear six-phase sequence with an ASCII diagram and interpretation tables serving as checkpoints, but no explicit validate→fix→retry feedback loop for the batch prediction operations. | 4 / 5 |
Progressive Disclosure | Well-structured overview that references one real one-level-deep bundle file (scripts/population_coverage.py) with inline signaled usage; minor organization gaps but easy to navigate. | 4 / 5 |
Total | 17 / 20 Passed |