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

No annotations are provided, so the description carries full burden for behavioral disclosure. It mentions the TBP 8-step process but does not explain side effects, permissions required, or what the tool creates/modifies. For a complex, multi-step tool, this is insufficient.

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 extremely concise with two sentences: one listing all relevant use cases and the second outlining the methodology. Every word earns its place, and it's front-loaded with the purpose.

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 10 optional parameters, no output schema, and no annotations, the description provides a high-level workflow (TBP 8-step) but does not map parameters to steps or explain expected return values. It is adequate but leaves gaps in understanding the full tool behavior.

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 100% with detailed parameter descriptions. The tool description does not add extra meaning beyond the schema; it only sets context. Baseline 3 is appropriate as the schema already does the heavy lifting.

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 clearly states the tool is for bug finding and fixing, listing specific use cases like 找问题、修 bug、排查异常、定位回归、分析失败原因. It also mentions the default TBP 8-step process, distinguishing it from sibling tools like fix_bug by emphasizing analysis before fixing.

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?

The description provides explicit when-to-use scenarios (当用户需要找问题…时使用), covering a wide range of troubleshooting needs. It does not explicitly state when not to use, nor mention alternatives, but the context is clear enough for an AI agent to select this tool over others like fix_bug.

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