query_employee

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

With no annotations provided, the description carries the full behavioral burden and mostly delivers: it discloses matching semantics ('姓名模糊查询或账号精确查询' — fuzzy vs exact), the return shape (JSON containing id/userId, username, job_num), and the default page_size of 50. It omits edge behaviors such as what happens when both or neither filter is supplied, which keeps it from a 5.

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 tight and well-structured: a one-line purpose statement, a two-line behavior note, then clearly separated Args and Returns sections. Each sentence carries distinct information (purpose, matching behavior, downstream use, parameter semantics, return format) with no filler or repetition.

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 simple 3-parameter read-only query with an output schema present, the description covers purpose, all parameter semantics, return content, and downstream usage. The only gaps are edge-case behavior (no filters supplied, both filters supplied) and pagination semantics beyond the default, which are minor for this tool.

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%, so the description must compensate — and it documents all three parameters with meaning beyond the bare schema: name_like supports fuzzy matching, account is explicitly '登录名/手机/邮箱' (login name/phone/email), and page_size has a stated default of 50. Every parameter receives semantic context the schema lacks.

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 opens with a specific verb+resource — '查询泛微 E10 人员信息' (query Weaver E10 personnel) — then specifies the two query modes (fuzzy by name, exact by account) and the key return value (userId). The resource is personnel, which is unambiguous against the eight workflow/sibling tools, and the note that 'userId 用于流程列表和流程详情查询' situates it as the lookup step before workflow queries, further distinguishing it from the workflow siblings.

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 gives clear context for when to call this tool: userId is needed for workflow list/detail queries ('userId 用于流程列表和流程详情查询'), implying this is the prerequisite lookup for the workflow sibling tools. It does not, however, explicitly state when not to use it or name an alternative, so it falls 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.