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

The annotations include openWorldHint: true, which suggests the tool may accept additional properties. The description does not contradict this; it explains the scope of the tool (specific responsibility-brand metrics). While it adds some behavioral context (what's included/excluded), it doesn't disclose any particular operational behaviors like rate limits or mutation effects. Since the annotation is minimal, the description partially compensates by defining the scope.

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 concise and front-loaded: it starts with the primary purpose, then lists included/excluded metrics, and ends with clear examples. Every line adds value with zero redundancy.

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?

Despite having an output schema (not shown), the description fully covers the tool's scope, including its specific metrics, exclusions, and usage examples. Given the complexity of distinguishing this from many sibling enterprise_change_* tools, the description is complete in guiding correct usage.

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 schema already provides descriptions for both parameters (company_name and country_name) with examples, achieving 100% coverage. The description reinforces the query pattern but doesn't add significant new meaning beyond what the schema describes. Baseline 3 is appropriate because the schema handles parameter documentation.

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: querying period changes in responsibility brand aspects for a specific company, including litigation counts, win rates, and IP/personal information/consumer protection litigation. It explicitly distinguishes what it does NOT cover (失信限高, 经营异常), and lists exactly which metrics are included. It also provides example queries.

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 explicitly states when to use this tool (for litigation-related responsibility metrics) and when NOT to use it (for non-responsibility violations like credit/debt restrictions). It also lists what's excluded (非本分类指标; 按园区/产业链批量筛企业名单) and gives typical query examples, providing clear context and exclusions.

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