get_next_suggestion

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

With no annotations, the description carries the burden. It clearly indicates an advisory role through '推断' and '建议', and fully discloses its decision logic. However, it does not explicitly state that it performs no side effects or how it handles invalid session IDs.

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 well-structured: a clear purpose sentence, a usage context, a bulleted decision list, and an Args section. Every sentence is informative, and the rules are compact and easily scannable.

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?

The description covers the entire decision logic, the parameter, and usage scenarios. Since an output schema exists, return value details are unnecessary. The tool is fully self-described for an agent to invoke it correctly.

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?

The input schema provides no description for session_id, but the description explicitly documents it as '目标会话 ID' (target session ID). This fully compensates for the 0% schema description coverage and adds meaningful context.

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 states '根据当前项目状态推断下一步应该做什么' (infer next actions based on current project state), which is a specific verb and resource. It further differentiates from siblings by listing a decision tree that recommends distinct tools like open_project, run_synthesis, and generate_bitstream, making its purpose unmistakable.

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?

It explicitly states it is '适合新手、刚打开老项目、或者不知道从哪下手的场景' (suitable for beginners, old projects, or unsure where to start), providing clear context. The decision rules also name alternative tools for each scenario, but it does not explicitly state when not to use this tool.

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