boss_ai_suggest_keywords

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

No annotations exist, so the description carries the full burden. It does disclose meaningful preconditions – that the input is drawn from the candidate pool and that the tool is only available in the candidate role on the zhipin platform – but it never states that the operation is read-only, whether it consumes quota or triggers model calls, or what shape the recommendations take.

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?

A single front-loaded purpose clause followed by a compact bracketed constraint block – no wasted wording. The bracketed availability syntax is terse but decodable.

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 one-parameter AI-suggestion tool with no output schema, the definition covers purpose and platform/role gating but leaves the return value, invocation cost, and downstream use of the keywords unexplained. Adequate to call correctly, not sufficient to use confidently.

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?

There is only one parameter and schema coverage is 100%, with 'limit' fully described as the cap on candidate-pool jobs analyzed. The description adds no meaning beyond that, so the baseline of 3 applies.

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 and output ('推荐搜索关键词组合' – recommend search keyword combinations) plus its basis ('基于候选池职位分析' – analysis of jobs in the candidate pool). This distinguishes it from generic siblings like boss_ai_suggest or boss_ai_optimize, though it never names an alternative explicitly.

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 line gives a real gating condition (roles=candidate, candidate_platforms=zhipin, recruiter_platforms=-), telling the agent when the tool is even callable. However, there is no guidance on when to prefer this over boss_ai_suggest or how to act on the returned keywords.

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