Content
50%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 clearly sequenced workflow description with concrete commands and a useful variable/JSON schema, but it is verbose with redundant sections, lacks validation checkpoints for its iterative batch nature, and ships as a monolithic file with no reference structure.
Suggestions
Add validation checkpoints to the iteration loop (e.g., confirm web-search returned results, confirm the LLM JSON parsed before branching on shouldContinue) to support error recovery in this batch workflow.
Provide concrete prompt templates or schemas for the two LLM steps (analysis and synthesis) instead of leaving them as '使用LLM分析' abstractions.
Trim redundant sections — fold '技术特点' into the workflow and move '使用场景'/'故障排除'/the output template into separate reference files to reduce token bloat and improve navigation.
| Dimension | Reasoning | Score |
|---|---|---|
Conciseness | The core workflow is useful, but sections like '技术特点' restate workflow features already described, '使用场景' duplicates the description, and the large placeholder output template adds padding that could be trimmed. | 3 / 5 |
Actionability | Provides concrete, executable elements (the `python scripts/web_search.py "<query>"` command, the nextSearchTopic/shouldContinue JSON schema, the variable table), but the LLM analysis steps are abstract with no prompt templates and the skill ships no executable script of its own. | 3 / 5 |
Workflow Clarity | The five-phase sequence and conditional shouldContinue branching are clearly laid out, but there are no validation checkpoints (e.g., verify search returned results, verify JSON parsed) in this batch/iterative workflow, which caps the score at 3 per the rubric. | 3 / 5 |
Progressive Disclosure | Section headers provide reasonable structure, but no bundle files exist and everything (use cases, troubleshooting, output template) is inlined in a single long document rather than split into one-level-deep references. | 3 / 5 |
Total | 12 / 20 Passed |