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Job Spotter: What's hiring most in a place

jobspotter_whats_hiring
Read-onlyIdempotent

Job Spotter. 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

A3.8/5.0
Behavior3/5

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

Annotations already declare readOnlyHint=true, idempotentHint=true, openWorldHint=true and destructiveHint=false, so the safety profile is covered. The description adds useful context about what the result contains (top roles, top employers), but says nothing about result breadth, ranking basis, or coverage limits.

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 and mostly economical: the example queries earn their space by showing intent and parameter pairing. The opening "Job Spotter. What's hiring most in a place." duplicates the title and is the only dead weight.

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 must sketch the return shape, and it does (most-advertised roles plus top employers). With all three parameters documented in the schema, an agent has enough to invoke it correctly; only ranking methodology and result limits are unaddressed.

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 description coverage is already 100%, so baseline is 3. The description's examples go further by implicitly demonstrating how the parameters combine ("nurses in Manchester" maps 'what' to "nurse" and 'where' to "Manchester"), which adds meaning beyond the schema definitions.

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 states a specific aggregate function: the roles advertised most and the employers with the most open jobs for a given place. This clearly separates it in kind from listing-style siblings such as jobspotter_search_jobs, though no sibling is named explicitly. Examples reinforce the purpose rather than merely restating the title.

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 queries ("who's hiring in Leeds?", "jobs in demand in Austin", "companies hiring nurses in Manchester") make the intended use case unmistakable. There are no explicit exclusions or named alternatives, so it stops short of the 5 tier.

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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