generate_impact_report

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

The description reveals cache-based fallback behavior when scan_results/ast_results are omitted, which goes beyond the readOnlyHint annotation. It does not mention potential errors if the cache is missing, but the annotation covers the safety profile.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is two sentences: the first states the core action, the second covers fallback and recommended workflow. Every clause contributes new information.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given no output schema, the description sufficiently explains the tool's role and inputs, including cache fallback and the recommended upstream scan calls. It does not detail report structure, but for a read-only aggregation tool with a well-described workflow, it is adequate.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 75%, with change_description, scan_results, and ast_results documented. The description adds the cache fallback context and an illustrative change_description example, but most parameter semantics are already in the schema.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description opens with a clear verb-resource pairing: '将扫描结果聚合成结构化 Markdown 影响分析报告' (aggregate scan results into a structured Markdown impact report). It distinguishes itself from sibling scanning tools by being the report-generation step, and the recommended workflow reinforces this role.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

Explicit workflow guidance is provided: '推荐工作流：先调用 scan_patterns 和/或 analyze_python_ast，再调用此工具生成报告'. It also describes the cache fallback when scan_results/ast_results are omitted, making the usage context precise.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.