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boss_ai_suggest_keywords

Analyzes job postings from a candidate pool and suggests keyword combinations to optimize search queries.

Instructions

基于候选池职位分析推荐搜索关键词组合 [可用性: 可用性: roles=candidate; candidate_platforms=zhilian, zhipin; recruiter_platforms=-]

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
limitNo候选池职位数上限
Behavior2/5

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

No annotations are provided, so the description must carry the full burden. It only mentions availability and recommends keywords, but does not disclose behavioral traits such as read-only nature, rate limits, or side effects. The tool's impact on data is unclear.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is concise, with a single purpose sentence followed by availability info. It is front-loaded, but the repetition in the availability string ('可用性: 可用性:') slightly mars the structure.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness3/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the simple schema (1 optional param) and no output schema, the description adequately explains the input and high-level output. However, it lacks details on the output format or how the analysis works, leaving some ambiguity.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 100%, providing a clear description for the only parameter 'limit'. The tool description adds no additional semantic meaning beyond the schema, meeting the baseline but not exceeding it.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the action: 'recommend search keyword combinations' based on 'candidate pool job analysis'. The name 'suggest_keywords' aligns with this, and it differentiates from sibling 'boss_ai_suggest' by focusing on keywords.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines3/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description includes availability constraints (roles, platforms) which imply context of use, but it does not explicitly state when to use this tool versus alternatives like 'boss_ai_suggest' or other analysis tools. No direct when-not guidance.

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

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