Content
81%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 highly actionable, well-sequenced workflow skill with strong validation checkpoints and real bundled scripts. The main weakness is token efficiency from duplicated config blocks and inline detail that could be externalized.
Suggestions
De-duplicate the end2end YAML config and Docker-access check block (repeated in the check, local, and remote sections) by referencing the bundled generate_end2end_config.py or a single shared snippet.
Trim the 'Practical H-cluster lessons' to the actionable rules (workers=2 on 4CPU/8G, GT capitalization, nested markdown/) and drop the narrative framing.
Move the full result-field extraction list and final report template into a references/ file, keeping SKILL.md as an overview with a pointer, to tighten the main body.
| Dimension | Reasoning | Score |
|---|---|---|
Conciseness | Mostly efficient concrete code, but the full end2end YAML config block and the Docker-access check are duplicated across the check, local, and remote sections; the 'Practical H-cluster lessons' add anecdotal prose. Not a 4 because the repeated ~25-line YAML block is more than a minor trim; not a 2 because the bulk is genuinely executable and earns its tokens. | 3 / 5 |
Actionability | Fully executable, copy-paste-ready commands covering local Docker, remote SSH, conda/source, config generation, and result parsing with exact field paths and a complete report template. | 5 / 5 |
Workflow Clarity | Clear 5-step sequence up top plus a dedicated 'Input validation before running' section with concrete checks, interpretation rules, and error-recovery guidance; read-only mounts and no-overwrite rules address the batch/destructive risk that would otherwise cap at 3. | 5 / 5 |
Progressive Disclosure | Bundled scripts (generate_end2end_config.py, parse_results.py — verified present) are clearly signaled with usage examples, and the body is well-sectioned. Not a 5 because the bulk of config/field-extraction detail lives inline in SKILL.md rather than in references/ files. | 4 / 5 |
Total | 17 / 20 Passed |