boss_ai_chat_coach

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

No annotations exist, so the description must carry the behavioral burden. It does disclose what the tool produces (a diagnosis, action suggestions, and ready-to-send templates), which tells the agent this is a generative advisory call rather than a lookup. It says nothing about whether it mutates state, how long it takes, or whether the chat text is sent to a model, leaving the side-effect profile to inference.

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?

It is a single front-loaded clause stating the function, followed by a compact availability constraint. No sentence is wasted. The availability metadata is slightly cramped inside brackets but remains readable.

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 three-parameter generative tool with no annotations and no output schema, the description covers the purpose and the return shape at a high level. It omits the one thing an agent most needs in this crowded AI family: how this differs from boss_ai_reply and the other advisory siblings.

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 100%, so style, resume, and chat_text are already documented with examples in the schema. The description adds no further meaning about input format, expected length of chat_text, or how style influences output. With the schema doing the heavy lifting, the baseline of 3 is appropriate.

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 names a concrete verb-resource pair: it diagnoses communication state from chat logs and returns next-step actions plus ready-made message templates. That is specific and actionable. It stops short of differentiating itself from AI siblings such as boss_ai_reply or boss_chat_summary, so an agent cannot fully rule those out from the text alone.

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 bracketed availability block is genuinely useful: it states this only applies to the candidate role on zhipin and is explicitly unavailable for recruiters, which prevents a whole class of wrong calls. It gives no guidance, however, on when to prefer this over boss_ai_reply or boss_chat_summary, so the choice among AI chat tools remains implied rather than stated.

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