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

Annotations are minimal (only openWorldHint=true), so the description carries the transparency burden. It explains the output format (merged text with counts) and exclusions, and implicitly indicates a read-only query. However, it does not mention any limitations, data source, or potential side effects, though none are expected. This adds some value but could be more explicit about the read-only nature and data coverage.

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 with a core function statement, metric list, exclusions, examples, and pricing. It is somewhat long, but each section earns its place by clarifying scope and usage. The use of bullet-style formatting and examples aids readability without unnecessary fluff.

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 simple tool (3 params, 2 required), high schema coverage, and existing output schema, the description is fairly complete. It covers the main use case, return content, and exclusions. It does not detail edge cases or error handling, but these are less critical for a count query with clear inputs and output.

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 100%, so the description does not need to compensate for missing parameter docs. It adds examples of valid region and chain_name values (e.g., national, city, district, industry chain names), reinforcing the schema but not introducing new semantics. This meets the baseline of 3 for high-coverage schemas.

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 count of high-tech enterprises by region and chain name, returning a merged text with totals and subtypes (production/sales/dependency). It explicitly excludes list details, distinguishing it from the sibling list tool (chain_high_tech_company_list) and other count tools by focusing on high-tech companies. Examples make the purpose unambiguous.

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 typical query examples that illustrate when to use this tool (e.g., asking for counts by region/chain). It states exclusions (no other classifications, no list details), implying if you need lists or other metrics, you should use alternative tools. However, it does not explicitly name or differentiate from other chain_*_num tools, so the guidance is clear but not exhaustive.

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