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

With no annotations provided, the description carries the behavioral burden and does disclose the key branch: omitting lookup_type returns only a summary of dictionary types and counts rather than full option lists. It also warns about a scale limit (tag volume) that would otherwise cause an agent to over-fetch. It stops short of stating explicitly that this is a read-only lookup or how large the result sets can get per type, leaving a small gap.

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?

Three sentences, front-loaded with purpose, then the default-return behavior, then the exclusion plus alternative — a logical order with no filler. The domain enumeration is somewhat long, but it substitutes for a missing enum, so it mostly earns its space.

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?

An output schema exists, so return values need not be described, and the description correctly focuses on selection logic, the null-parameter branch, and the sibling routing. For a single-optional-parameter lookup tool this is nearly complete; the only missing piece is the exact accepted lookup_type strings, which matters given the 0% schema coverage.

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 0% and lookup_type is an unconstrained nullable string with no enum, so the description must supply the value space — it does, by enumerating the concrete dictionary domains an agent can request. It also defines the default behavior when the parameter is null, which the schema only shows as default=null. It does not give exact accepted string values or spellings, so an agent must still infer casing/format.

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?

States a specific verb and resource ('查询小型字典选项') and immediately names the concrete domains covered (industry, sub-industry, funding round, province, development stage, institution type, company qualification, death reason, newsletter_type). It also explicitly distinguishes itself from search_tags, so an agent can separate it from the sibling without opening either schema.

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?

Gives the intended use case (mapping natural-language conditions to IDs), an explicit exclusion ('不要用本工具获取标签全集'), and the named alternative to use instead ('赛道或标签词映射请调用 search_tags'). It also explains the no-argument case, so both branches of invocation are covered.

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