Content
77%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.
The body is a well-structured, actionable, multi-phase workflow with strong validation feedback loops and clean progressive disclosure; its main weakness is mild redundancy from repeated reference path listings and shared boilerplate.
Suggestions
De-duplicate the reference file listings (lines 79–88 and 181–192) into a single '参考资料' section to reduce token cost.
Inline the key config.yaml values referenced by the workflow (e.g. mode/style defaults, run_dir_pattern) or point to one config reference instead of scattering config.yaml:… keys throughout.
Specify the concrete rendering invocation for the detected build chain rather than only naming the tools.
| Dimension | Reasoning | Score |
|---|---|---|
Conciseness | The body is dense and operational without explaining basic concepts, but reference file paths are listed twice (lines 79–88 and 181–192) and the 公共硬约束 boilerplate is verbose, so it could be noticeably tightened. | 3 / 5 |
Actionability | Concrete executable guidance is present — the copy-paste-ready prepare_workspace.py CLI invocation, concrete template/reference paths, fixed section ordering, and named build tools — but rendering commands are left unspecified and many values are deferred to config.yaml keys, leaving minor gaps. | 4 / 5 |
Workflow Clarity | A clearly sequenced 阶段0–5 workflow with explicit validation checkpoints (数字审查, section-role-check, 全文一致性终审, 逻辑树终审) and feedback loops ('若有阻塞性问题，修复后再复审'), supported by referenced checklists/templates. | 5 / 5 |
Progressive Disclosure | SKILL.md acts as an overview that delegates long rule blocks to one-level-deep references (verified to exist) with categorized '优先只读取' and '读取建议' navigation guidance, giving clear easy navigation. | 5 / 5 |
Total | 17 / 20 Passed |