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

The description discloses the behavior beyond the sparse annotations (only openWorldHint): it returns merged text for total/production/sales/dependent counts, and mentions the fixed 'last two years' time scope. It also clarifies what is not included. It does not contradict the openWorldHint annotation. While it doesn't describe auth or rate limits (likely irrelevant for a query tool), the behavioral details provided are sufficient.

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 yet comprehensive: it opens with the core purpose, enumerates the metrics included, lists exclusions, and provides representative examples. Every sentence contributes to understanding, and the structure is scannable. No redundant content.

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 simplicity (3 parameters, expected count output) and the presence of an output schema, the description is complete: it explains the query semantics, the fixed two-year window, the specific count categories, what is excluded, and provides usage examples. The agent has all necessary guidance to decide and invoke the tool 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 already provides 100% coverage with clear descriptions for each parameter (year, region, chain_name). The description reinforces this by giving typical question examples that illustrate how to fill the parameters, but it does not add significant semantic detail beyond the schema. Baseline is 3 because the schema is already descriptive, and the examples add modest value.

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 the count of companies that participated in tenders in the last two years based on region and industrial chain. It explicitly names the resource (企业数量/count of companies) and the action (查询/query), and distinguishes it from sibling tools like chain_won_tender_company_num or chain_issued_tender_company_num by specifying 'participated' and also clarifying it returns aggregated counts (total/production/sales/dependent) rather than lists.

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 clear context on when to use this tool: when you need aggregated count statistics for companies participating in tenders, with explicit examples of typical questions. It also states exclusions (other company categories, company list details), which guides the agent to avoid using it for list queries. However, it does not explicitly name alternative tools (like the list counterpart chain_participated_tender_company_list), though the context strongly implies the distinction.

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