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OpenHire — Real Job Postings, Ghost Jobs Scored

OpenHire — Real Job Postings, Ghost Jobs Scored

by gzchenhao
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
Local

Careers portals OpenHire cannot read

list_portals
Read-onlyIdempotent

The blind spots as a link directory: employers in AI infra, autonomous driving and embodied AI whose postings this index cannot read, each with its own careers portal.

Instructions

The blind spots as a link directory: employers in AI infra, autonomous driving and embodied AI whose postings this index cannot read, each with its own careers portal.

Most are Chinese employers on Feishu Recruitment (飞书招聘), whose job-list API needs a request signature this index treats as access control; a few publish only on BOSS直聘 or keep a careers page without a readable list. Their postings are public to a person in a browser; OpenHire cannot index, date or watch them.

Use it when the user asks about these sectors broadly (具身智能有哪些公司在招, autonomous driving roles in Shanghai), after the search_jobs results: say which employers post elsewhere and give the links, so a blind spot is one click away instead of invisible. If you have a browser tool, offer to open a portal. Never present these links as OpenHire postings and never invent posting dates for them.

Args: sector: autonomous_driving, embodied_ai or ai_infra (自动驾驶, 具身, 大模型 work too); leave it out for all three.

Returns: PortalDirectory with portals[] (name, careers_url, what a browser shows without logging in, why the employer is not indexed, last_checked) and a note on what OpenHire does not do with them.

Tool call template

This tool declares no required parameters. Add optional parameters from the input schema as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {},
    "name": "list_portals"
  }
}

Input Schema

NameRequiredDescriptionDefault
sectorNo

Schema Changelog

Changes observed during successful MCP inspections.

  1. Addedv0.8.27

TDQS

A4.9/5.0
Behavior5/5

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

Beyond the read-only, idempotent, non-destructive annotations, the description discloses why these employers are not indexed, that postings are public in a browser but cannot be indexed/dated/watched by OpenHire, and that posting dates must never be invented. This is rich behavioral context for interpreting and presenting results.

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 front-loaded with the purpose, then provides usage context, arguments, and return shape in a clear order. It is longer than minimal, but nearly every sentence adds actionable context about blind spots, sectors, and presentation constraints.

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

Completeness5/5

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

Despite having no output schema, the description describes the PortalDirectory return shape in useful detail: portals with name, careers_url, browser-visible content, reason for not being indexed, last_checked, and a note. It also covers the behavioral and usage caveats an agent needs before calling and presenting results.

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

Parameters5/5

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

Schema description coverage is 0%, but the description fully explains the sole sector parameter: accepted values autonomous_driving, embodied_ai, and ai_infra, including Chinese equivalents, and that leaving it out returns all three. This compensates completely for the missing schema documentation.

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 states a specific resource and scope: a link directory of employers in AI infra, autonomous driving, and embodied AI whose postings OpenHire cannot read, each with a careers portal. It clearly differentiates itself from search_jobs by framing these as blind spots that are not indexed.

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

Usage Guidelines5/5

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

It explicitly says to use this when the user asks about these sectors broadly, gives concrete query examples, says to use it after search_jobs results, and describes how to offer opening a portal if a browser tool exists. It also includes output-use constraints such as not presenting the links as OpenHire postings.

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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