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

Annotations already declare readOnlyHint, idempotentHint, destructiveHint=false and openWorldHint=false, so safety is covered structurally. The description adds a genuinely behavioral fact beyond them: this call is the canonical provenance of slug values for all later operations. It omits pagination/volume behavior, 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?

Three compact clauses: what it returns, when to call it, and the slug-provenance rule. Nothing is wasted and the return-field list 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?

With no input params and no output schema, the description carries the return-shape information itself by naming the four fields, and the slug rule covers the cross-tool contract. Nothing an agent needs to call it correctly is missing.

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?

Zero parameters, so the baseline is 4. The description reinforces this explicitly with "参数：无", leaving no ambiguity that the tool takes no arguments.

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 (列出我名下的数字员工岗位) and enumerates the returned fields (slug / 名称 / 模板 / 画布链接), which cleanly separates it from siblings like get_job, list_templates, and get_staff_config.

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 an explicit trigger (用户问"我有哪些岗位"用它) plus a hard workflow rule: every downstream per-staff tool needs a slug and the slug must be taken from here rather than reconstructed from memory. That is when-to-use plus a concrete dependency chain.

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