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Job Spotter

by io.github.GoodTurnStudio
OverviewDiscussionsAdmin

The companies hiring most right now, with trends and pay

top_hiring_companies
Read-onlyIdempotent

The companies hiring most right now, with trends and pay. For "who's hiring the most data people in the UK?", "which companies are growing?", "who's hiring remotely?". Ranks employers in Job Spotter's index by open roles, each with roles added and taken down this week, its trend (growing, steady or contracting), the change on the week before, median advertised pay, AI roles, its careers page and any US layoff notices in the last 90 days. Then call search_jobs with the company name for its roles. A ready-to-read summary is in say.

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": "top_hiring_companies"
  }
}

Input Schema

NameRequiredDescriptionDefault
limitNoHow many companies, 1 to 30 (default 15).
trendNoOptional: growing, steady or contracting.
whereNoOptional town or city (for example London or Austin), or remote.
countryNoOptional country by name or two-letter code, for example United Kingdom, US or DE. Leave out for worldwide.
functionNoOptional job area: software, data (data and AI), design, product, sales, finance, marketing, customer, healthcare, education, people, legal, operations, hardware, service or management. A job word such as "nurse" works too.

Schema Changelog

Changes observed during successful MCP inspections.

  1. Added

TDQS

A4.4/5.0
Behavior4/5

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

Annotations already declare readOnly, non-destructive, idempotent and open-world, so the safety profile is covered. The description adds genuine value beyond that: the reporting window (roles added/taken down this week, trend vs. the week before), the scoping caveat that layoff notices are US-only and limited to 90 days, and the presence of a ready-to-read `say` summary.

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?

Front-loaded with the purpose, then examples, then the return payload, then the follow-up call. The return-field enumeration is long but earns its place since there is no output schema; only minor redundancy exists between the title sentence and the first body sentence.

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?

With no output schema, the description fully compensates by enumerating the returned company attributes and their time windows. An agent knows what it will get, what the data scope is (US-only layoffs), and what to do next.

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% with per-parameter descriptions and an enum, so the schema already carries the parameter meaning. The description's example questions loosely imply the function/country/where filters, but it adds no syntax, defaults, or interaction detail (e.g. how where and country combine) beyond what is already structured.

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?

States a specific verb and resource — 'ranks employers in Job Spotter's index by open roles' — and enumerates the fields returned (roles added/removed, trend, week-over-week change, median pay, AI roles, careers page, layoff notices). It is unmistakable from siblings like get_hiring_stats or search_jobs, and the closing instruction routes follow-up work to search_jobs.

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?

Opens with concrete user questions it answers ('who's hiring the most data people in the UK?', 'who's hiring remotely?') and explicitly prescribes the next step: call search_jobs with the company name for its roles. The only minor gap is that it doesn't exclude company_lookup for single-employer queries.

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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