extract_antv_topic

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

With no annotations provided, the description carries full burden and does well by describing key behavioral features: 'Smart Library Detection' (scans dependencies), 'Topic & Intent Extraction,' 'Task Complexity Handling' (decomposes tasks), and 'Seamless Integration' (prepares data for next tool). However, it doesn't mention potential limitations, error handling, or performance characteristics.

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 with clear sections (mandatory rule, usage scenarios, key features) and front-loaded with the most important information. However, some sentences could be more concise, and the 'Key features' section contains marketing language ('intelligently,' 'seamless') that doesn't add operational clarity.

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?

For a preprocessing tool with 3 parameters, 100% schema coverage, and no output schema, the description provides good context about its role in the workflow and behavioral characteristics. However, without annotations or output schema, it could benefit from more detail about what the tool actually produces (structured data format) and any limitations or error conditions.

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 baseline is 3. The description adds some context about 'library' parameter ('automatically detect project dependencies and intelligently recommend') and implies 'maxTopics' relates to 'complex tasks,' but doesn't provide additional semantic meaning beyond what's already well-documented in the schema descriptions.

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 as 'intelligently identifying, parsing, and structuring user visualization requirements' for AntV libraries, specifying it's a 'preprocessing tool' and 'first step in processing AntV technology stack issues.' It explicitly distinguishes from its sibling 'query_antv_document' by stating it 'always precedes' that tool.

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 rules with 'MANDATORY: Must be called for ANY new AntV-related queries' and a detailed 'When to use this tool' section listing four specific scenarios. It clearly states the tool must precede 'query_antv_document' and provides examples of what constitutes AntV-related queries.

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