get_users

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

With no annotations provided, the description carries the full disclosure burden. It adds value by stating the tool returns userId/userName/userAccount and supports fuzzy filtering — behavior not visible from the schema alone. However, it discloses no operational details such as pagination, whether an empty keyword returns all users, or authentication requirements. Given the read-only nature is implied rather than explicit, a 3 is appropriate.

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?

Two compact sentences with zero filler. The first is front-loaded with the core purpose and returned fields; the second adds the downstream use case. Every clause earns its place, and the most important information appears first.

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 no explanation. The tool is a simple list query with one optional parameter, and the description covers purpose, filtering semantics, and the primary usage scenario. The only minor gap is not stating what an empty keyword returns, but the default '' implies it lists all users — a small omission against an otherwise complete definition.

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. It does: '可按姓名或账号模糊过滤' explains that the keyword parameter matches fuzzily against both name and account fields — meaning the schema's bare 'keyword' string could not provide. This adds real semantic value beyond the input schema.

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 verb+resource: '查询能效平台用户列表' (query the energy platform user list), and names the returned fields (userId/userName/userAccount) plus the fuzzy filtering behavior. This is concrete and unambiguous, and the chained reference to query_defects further situates its role among 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 second sentence gives explicit usage context: use this tool to map an owner name/account to a userId, then pass that to query_defects for filtering. This tells the agent when the tool is the right choice. It doesn't name exclusions or when to prefer siblings like get_user_projects, but the stated use case is clear enough for a 4.

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