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

With no annotations, the description carries the full burden and does reasonably well: it discloses that results are a list of candidates (not a single resolved entity), states the default of 2 hits, and explains the clamping rule that values above 50 or below 0 are silently replaced with 10. It also notes that caller gateway credentials are used and that charges and authorization are gateway-determined, which is useful cost/auth context. It omits error behavior and what happens when no candidate matches.

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?

Five short sentences, each carrying distinct information: query semantics, required field, default and clamping, intended-vs-unintended use, and auth/charging. Nothing is repeated from the schema verbatim and the core purpose is front-loaded.

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 2-parameter lookup with no output schema, the description covers input semantics, result shape at a high level ('list of candidate enterprise details', 'aggregated details'), and operational constraints. The only material gap is that it does not indicate what fields a candidate record contains or how ambiguity between multiple candidates should be resolved, which matters for a fuzzy-name search.

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%, so baseline is 3, but the description adds meaning beyond the schema: it explains that name also accepts a former name or stock short name, and it specifies the out-of-range clamping behavior (greater than 50 or less than 0 becomes 10), which the schema does not state. That is genuine semantic value on top of the structured fields.

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: search by enterprise name, former name, or stock short name, returning a list of candidate enterprise details. It also scopes the query type (candidate lookup, not a strict unique-enterprise-ID query), which separates it from ID-based siblings. It does not name a specific sibling tool such as yuandian_get_open_rh_enterprisesearch or enterprisebaseinfo, so the differentiation is by query type rather than by named alternative.

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?

Explicitly directs the agent to use this API to find candidate enterprises from a name 'rather than for a strict unique-enterprise-ID query', giving both a when-use and a when-not condition. The alternative is described only abstractly (an ID-based query) rather than by naming the sibling tool that performs it, which keeps this short of a 5.

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