Agent Data API

company_hiring_movers

Which companies are hiring fastest, or cutting? Ranks companies by job postings added and removed in the last 7, 14 or 30 days, from our recorded history of about 20,000 public company job boards (Greenhouse, Lever, Ashby, Workable, SmartRecruiters, Recruitee, Workday) crawled twice a day. Filter by job function (sales, engineering, data...) to find companies ramping a team. Returns up to 50 companies with open roles, added, removed, net change, growth rate and layoff or hiring-freeze signals. Costs $0.01 USDC on Base via x402.

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": "company_hiring_movers"
  }
}

Input Schema

Name	Required	Description
`days`	No	Window in days (default 7)
`limit`	No	Results, 1-50 (default 25)
`minOpen`	No	Smallest company to include: open postings at the window's start, 5-5000 (default 10)
`function`	No	Rank by one job function's net change, read from job titles (e.g. sales)
`direction`	No	growing ranks by most postings added net; shrinking by most removed net (default growing)

Schema Changelog

Changes observed during successful MCP inspections.

AddedNov 14, 2026

TDQS

A3.7/5.0

Behavior4/5

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

With no annotations, the description carries the full burden and does substantial work: it discloses data provenance (seven named ATS platforms, twice-daily crawls), result fields including growth rate and layoff/freeze signals, a hard cap of 50 results, and a payment requirement ($0.01 USDC on Base via x402). It omits rate limits, failure modes, and whether the x402 charge applies per call or per page, which keeps it from a 5.

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 lead sentence is a question that immediately frames the use case, and detail follows in a logical order: method, sources, filters, outputs, cost. The platform list and payment clause are dense but each earns its place by grounding trust and cost expectations; minor trimming of the enumerated ATS names is possible.

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?

For a five-parameter, all-optional tool with no annotations and no output schema, the description covers what the tool returns, how results are ordered, the payment model, and the sample size. It is nearly sufficient to call correctly, with the main residual gap being the semantics of minOpen and the exact cost trigger.

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%, so the schema already documents all five parameters including enums and defaults, making a 3 the baseline. The description adds real context by explaining the 'function' filter's intent (reading job titles to find teams being ramped) and the direction semantics, but says nothing about minOpen, limit, or the string-typed numeric patterns.

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

Purpose4/5

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

The description names a specific verb and resource ('Ranks companies by job postings added and removed') and quantifies scope with 7/14/30-day windows and a 20,000-board crawl universe. An agent can tell this is a hiring-momentum ranking tool, though it never contrasts itself with the sibling company_hiring_trend, leaving that distinction to inference.

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?

Usage is implied through framing questions ('Which companies are hiring fastest, or cutting?') and a concrete scenario ('Filter by job function ... to find companies ramping a team'). There is no explicit when-not guidance, no prerequisites stated, and no named alternative for time-series or single-company lookups.

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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