extract_antv_topic

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 key behavioral traits: 'Smart Library Detection' (scans installed libraries and recommends best fit), 'Topic & Intent Extraction' (extracts technical topics and determines intent), 'Task Complexity Handling' (detects and decomposes complex tasks), and 'Seamless Integration' (prepares structured data for the next tool). However, it doesn't mention potential limitations like 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 appropriately structured with clear sections (mandatory callout, when to use, key features) but is somewhat verbose. Sentences like 'Specifically designed to handle any user queries related to AntV visualization libraries' and 'responsible for intelligently identifying, parsing, and structuring user visualization requirements' could be more concise while maintaining 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?

Given the tool's complexity (preprocessing with intelligent analysis) and lack of both annotations and output schema, the description provides good behavioral context but leaves significant gaps. It explains the workflow position and key features well, but doesn't describe the output format, error conditions, or parameter details. For a tool with 3 parameters at 0% schema coverage, this creates ambiguity about what the tool actually returns.

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 0%, so the description must compensate for all three parameters. While it mentions 'query' in the usage context, it doesn't explain what the 'query' parameter should contain, what 'library' represents, or what 'maxTopics' controls. The description adds no meaningful semantic information about the parameters beyond what's implied by the tool's purpose.

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: 'intelligently identifying, parsing, and structuring user visualization requirements' for AntV-related queries. It specifies the exact scope (AntV visualization libraries) and distinguishes it from its sibling tool query_antv_document by explaining this is the 'first step' that 'precedes' it.

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: 'MUST be called for ANY new AntV-related queries, including simple questions' and 'Always precedes query_antv_document tool.' It lists specific scenarios (AntV-related queries, visualization tasks, problem solving, learning & implementation) and clearly positions this tool as the mandatory first step in the workflow.

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