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

Annotations only provide openWorldHint, so the description carries the behavior burden. It adds meaningful details: merged return text (total/production/sales/dependent), two-year time window, and the explicit exclusion of count-only results. No contradiction with the openWorldHint annotation is present.

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 compact and sectioned into scope, metric types, exclusions, and examples. There is some repetition of '近两年有对外投资的企业列表', but the structure makes it scannable and each section contributes relevant operational context.

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 list tool with an output schema and 100% parameter coverage, the description is sufficient: it gives required dimensions, examples, exclusions, and typical queries. It could be improved by explicitly relating itself to sibling count/invested-list tools, but this is not a major gap.

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 describes all three parameters, and the description adds value with region granularity (国家/省份/城市/区县), concrete chain examples, and typical questions for region/chain/year. The relationship between the year parameter and '近两年' is implicit rather than fully explicit, but inferable from examples.

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 states a specific query: companies with outward investment in the last two years for a given region and industry chain. It also enumerates the returned sub-lists (total/production/sales/dependent) and provides typical questions, distinguishing it from general chain_company_list and chain_invest_company_num.

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 '不包含' section clarifies exclusions (other enterprise classifications and count-only results), and the typical question examples illustrate when the list tool is appropriate. It does not explicitly name alternatives such as chain_invest_company_num, but the list-vs-count distinction is clear from context.

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