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Toolcall

by click.toolcall
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job-search

Live job postings without scraping: company= returns an employer's current openings straight from their official ATS board (Greenhouse, Lever, Ashby, SmartRecruiters) with title, location, department, type and apply URL; query= searches remote-heavy job APIs (Remotive, Arbeitnow) by keyword. Optional location= filter. JSON response. [Paid: $0.02 USDC per call via x402 on Base; the calling client pays automatically.]

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": "job-search"
  }
}

Input Schema

NameRequiredDescriptionDefault
limitNo
queryNoKeyword search across job APIs, alternative to company
companyNoEmployer name; reads their public ATS job board
locationNoLocation filter substring, optional

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A4/5.0
Behavior3/5

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

With no annotations, the description carries the full burden. It correctly identifies sources (Greenhouse, Lever, Remotive, etc.) and output format (JSON). It does not detail failure modes, rate limits, data freshness, or behavior when no results are found.

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 a single dense paragraph that efficiently conveys purpose, modes, and pricing. It could be slightly more structured with bullet points, but it is concise and front-loaded.

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 no output schema, the description mentions JSON response but lacks details on response structure, pagination (limit), or error cases. It covers core functionality but is incomplete for advanced use without schema support.

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

Parameters4/5

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

Schema coverage is 75% (limit missing description). The description adds value by explaining the behavior of company, query, and location parameters with source context. The limit parameter's semantics are only in the schema (range), not in the description.

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 it fetches live job postings from official ATS boards and remote job APIs. It distinguishes between company-specific searches (company=) and keyword searches (query=), making the purpose unambiguous and distinct from siblings like web-search or news-search.

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?

Guidance is provided on when to use company= vs query=, and the optional location filter is mentioned. It also includes pricing information. However, explicit when-not-to-use scenarios or alternatives among siblings are not mentioned.

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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