Content
57%Reviews the quality of instructions and guidance provided to agents. Good implementation is clear, handles edge cases, and produces reliable results.
The skill body is concise and well-intentioned with a clear instructional sequence, but it lacks executable examples and references bundle files that are absent from the repo. Fixing the broken references and adding a validation/feedback checkpoint would most improve it.
Suggestions
Create the referenced bundle files (algorithm-data-structures.md, distributed.md, system-design-scenarios.md) or remove the broken 'Additional Resources' pointers, and format them as proper markdown links.
Add a brief validation checkpoint in the workflow, e.g. after追问 confirm '复杂度与边界是否已覆盖，否则继续追问反例' before moving to the engineering scenario.
Include one concrete worked example (a sample algorithm question plus the expected 追问 and 工程化迁移) to lift actionability above instructional guidance.
| Dimension | Reasoning | Score |
|---|---|---|
Conciseness | The body is lean and assumes Claude's competence (e.g. '要求候选人口述解法步骤、关键数据结构、复杂度与边界处理'), with no padding or explanation of basics Claude already knows. | 3 / 3 |
Actionability | Guidance is fairly concrete (1-2题、追问不变式或反例、迁移到计数/去重/TopK) but is instructional rather than executable, with no code or worked examples. | 2 / 3 |
Workflow Clarity | Numbered instructions give a clear sequence (算法题 -> 追问 -> 工程化追问), but there are no validation checkpoints or feedback loops for an interview flow, capping clarity at 2. | 2 / 3 |
Progressive Disclosure | The 'Additional Resources' section points to files (algorithm-data-structures.md, distributed.md, system-design-scenarios.md) that do not exist in references/, and the links are not clearly signaled markdown references, so navigation is broken. | 1 / 3 |
Total | 8 / 12 Passed |