report_progress

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

With no annotations provided, the description carries the full burden of behavioral disclosure. It effectively describes the tool's purpose and workflow (reporting progress and requesting guidance), though it doesn't specify technical details like response format, rate limits, or authentication requirements. However, it clearly communicates the tool's interactive nature and expected usage pattern.

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 and appropriately sized. It opens with a clear purpose statement, provides usage guidelines, and includes a formatted section with usage scenarios and parameters. Every sentence serves a purpose with no redundancy or wasted words.

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 the tool's moderate complexity (4 parameters, interactive workflow) and the presence of an output schema (which handles return values), the description is largely complete. It covers purpose, usage context, and parameters adequately. The main gap is lack of behavioral details like error handling or response structure, but the output schema mitigates this.

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 description coverage is 100%, so the schema already documents all parameters thoroughly. The description lists parameters in a section but doesn't add meaningful semantic context beyond what's in the schema (e.g., explaining how 'result' influences guidance or what constitutes good 'feedback'). This meets the baseline for high schema coverage.

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's purpose with specific verbs ('报告执行进度' - report execution progress, '请求下一步指导' - request next-step guidance) and distinguishes it from siblings like consult_aurai (consultation), get_status (status retrieval), and sync_context (context synchronization). It explicitly defines the tool's role in reporting results after executing superior AI suggestions.

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 usage guidelines: '在执行了上级AI的建议后，调用此工具报告结果，获取下一步指导' (After executing superior AI suggestions, call this tool to report results and get next-step guidance). It clearly defines when to use this tool (post-execution reporting) versus alternatives like consult_aurai (for consultation before execution) or get_status (for status checking without guidance).

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