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WonderCV

ClawHire MCP

by WonderCV

search_candidates

Search for job candidates in ClawHire's talent pool, including both active marketplace profiles and passive database entries, with filtering options for location, experience, salary, and AI proficiency levels.

Instructions

搜索候选人池,包含两类候选人:

市场候选人(已入驻)

  • Category 1: MCP原生用户(🤖 AI-Agent 熟练标识)

  • Category 2: GUI选择加入的用户

  • 可查看完整档案(根据可见性设置)

  • 可直接申请职位

数据库候选人(被动池)

  • Category 3: WonderCV现有用户,未主动入驻

  • 仅显示匿名化信息(城市、大致经验、技能)

  • 无法直接联系

  • 可发送 outreach 邀请(每日限额)

AI-Agent 熟练度徽章

  • verified_mcp_user: 已验证MCP用户(自动标识)

  • ai_power_user: 高级AI用户(自评4+分且有工作流描述)

  • ai_aware: 了解AI工具(自评2-3分)

建议:使用 job_token 参数可根据职位要求智能排序候选人。

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
session_idYes会话 ID,从 register_company 获取
queryNo自然语言搜索,如:"上海AI产品经理,3年以上"
cityNo按城市过滤
profession_idNo职位分类ID
experience_minNo最低工作年限(年)
experience_maxNo最高工作年限(年)
salary_minNo最低期望薪资(月/人民币)
salary_maxNo最高期望薪资(月/人民币)
open_to_remoteNo是否接受远程工作
ai_fluency_minNo最低AI熟练度要求:verified_mcp_user=MCP用户, ai_power_user=高级用户
poolNo搜索范围:marketplace=已入驻候选人, database=WonderCV数据库, all=全部
job_tokenNo关联的职位token,将根据职位要求优化匹配排序
pageNo页码
page_sizeNo每页数量,最大20
Behavior4/5

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

With no annotations provided, the description carries the full burden and does so effectively. It discloses key behavioral traits: daily outreach limits for database candidates, visibility settings for market candidates, and sorting behavior with job_token. It also explains contact restrictions and AI proficiency badges, adding valuable context beyond basic functionality.

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 well-structured with clear sections (market candidates, database candidates, AI proficiency badges, suggestion) and uses bullet points for readability. It is appropriately sized for the tool's complexity, though some redundancy exists (e.g., repeating candidate categories could be streamlined). Every sentence adds value without unnecessary fluff.

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

Completeness4/5

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

Given the tool's complexity (14 parameters, no annotations, no output schema), the description is quite complete. It explains candidate types, behavioral constraints, and usage tips. However, it doesn't detail the output format or pagination behavior, which is a minor gap since there's no output schema to rely on, but the overall context is well-covered.

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 description coverage is 100%, so the schema already documents all 14 parameters thoroughly. The description adds minimal parameter-specific semantics, only mentioning job_token for intelligent sorting. It doesn't provide additional syntax, format, or usage details beyond what the schema offers, meeting the baseline for high schema coverage.

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 tool searches candidate pools with specific categories (market candidates and database candidates), distinguishing it from sibling tools like list_applications or view_candidate. It provides a detailed breakdown of candidate types and their characteristics, making the purpose explicit and differentiated.

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

Usage Guidelines4/5

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

The description includes a suggestion to use job_token for intelligent sorting based on job requirements, which provides clear guidance on optimal usage. However, it lacks explicit when-not-to-use guidance or alternatives among sibling tools like list_applications or view_candidate, though the context of candidate pools is well-defined.

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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