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

Beyond the minimal openWorldHint annotation, the description discloses that the result is a merged text string combining four counts (overall, production, sales, dependent), specifies the trailing two-year window relative to the year parameter, and reveals pricing details. These are useful behavioral traits not present in the annotations and do not contradict the openWorldHint annotation.

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: a one-sentence core purpose, a bulleted list of included metrics, exclusions, and typical queries, followed by a separate pricing block. It is slightly long but every section serves a purpose; the embedded JSON pricing snippet adds minor noise but is cleanly separated.

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 availability of an output schema and the tool's moderate complexity (3 params, many siblings), the description covers the key aspects: what counts are returned, aggregation logic, exclusions, and example phrasings. It could theoretically specify edge-case behavior (e.g., empty results), but the documentation is robust for an open-world tool with a defined output schema.

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 coverage is 100%, covering all 3 parameters, so a baseline of 3 applies. The description adds semantic value by clarifying that the 'year' parameter anchors the 'recent two years' calculation and by illustrating acceptable formats for 'region' and 'chain_name' through realistic examples (e.g., '全国', '北京市海淀区', '集成电路'), which helps agents construct valid calls.

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 queries the number of companies that have initiated tenders in the last two years, filtered by specific geography (country/province/city/district) and supply chain name. It also distinguishes itself from siblings by specifying the output is a merged count text (total/production/sales/dependent) and explicitly excluding company lists and other categories, differentiating it from chain_issued_tender_company_list.

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 strong usage context through three realistic example queries, clarifies the two-year lookback window, and states exclusions ('not include: other company classifications; list of companies'). However, it does not explicitly name alternative tools like chain_issued_tender_company_list or other sibling count tools, so the differentiation is implied rather than stated.

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