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What's hiring most in a place

whats_hiring
Read-onlyIdempotent

What's hiring most in a place. For "who's hiring in Leeds?", "what jobs are in demand in Austin?", "which companies are hiring nurses in Manchester?". Gives the roles advertised most and the employers with the most open jobs.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
whatNoOptional field to narrow it, for example "nurse" or "engineering".
whereYesA city, region, postcode or country, for example Birmingham, Austin, TX or remote.
countryNoUS or UK when the place exists in both, or a country by name.

Schema Changelog

Changes observed during successful MCP inspections.

  1. Added

TDQS

A3.6/5.0
Behavior3/5

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

Annotations already declare readOnlyHint, idempotentHint, openWorldHint and destructiveHint=false, so the safety profile is covered structurally. The description usefully discloses what the tool returns (aggregate role and employer counts), but says nothing about freshness of the data, rate limits, or how 'place' resolution failures are handled.

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?

Three short sentences, front-loaded with the purpose and followed by examples and the return shape. The opening sentence duplicates the title, which is mild redundancy, but nothing else is wasted.

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?

There is no output schema, so the description correctly carries the burden of describing returns ('roles advertised most and the employers with the most open jobs'). Combined with annotations covering the read-only, open-world nature, an agent has enough to invoke it correctly; data freshness and result sizing remain unstated.

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 all three parameters are already documented in the schema. The description's examples of 'nurses in Manchester' loosely illustrate how 'what' and 'where' combine, but add no syntax or disambiguation beyond what the schema already states. Baseline 3 applies.

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?

States a specific resource and outcome: the roles advertised most and the employers with the most open jobs in a place. The example queries ('who's hiring in Leeds?') make the intent unmistakable. It does not name any sibling tool (e.g. search_jobs, hiring_posts) as the contrasting alternative, so it stops short of a 5.

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?

Three concrete example phrasings give clear context for when this tool fits: aggregate demand questions about a place, optionally narrowed by occupation. No explicit when-not-to-use rule or named alternative is given, which keeps it below 5.

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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