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Job Spotter: Check an employer against the fair hiring badge

jobspotter_fair_hiring_check
Read-onlyIdempotent

Job Spotter. Check an employer against the fair hiring badge. For "is this employer fair to applicants?". Four checks from what the employer does: shows pay in its adverts on Job Spotter, replies to tracked applications, hires through scored consent-first introductions, and (UK employers with 250 or more staff) reports its gender pay gap on time. Each check comes with its figures; the badge is earned when every check with data passes and at least two have data. Includes a badge image link.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
companyYesThe employer, for example "Greggs".

Schema Changelog

Changes observed during successful MCP inspections.

  1. Added

TDQS

A4.1/5.0
Behavior4/5

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

Annotations already cover the safety profile (readOnly, idempotent, non-destructive, openWorld), so the bar is lower. The description adds genuine behavioral value: it lists what the four checks evaluate, states the badge is earned only when every check with data passes and at least two have data, and notes a badge image link is included.

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-loads purpose, then the user question, then the checks. Efficient overall, though the leading 'Job Spotter.' duplicates the name/title and the stacked clauses about the four checks are dense.

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 read-only lookup with no output schema, the description adequately explains what a caller gets back: per-check figures, the badge pass/fail logic, and an image link. Minor gap is that no explicit alternative-tool guidance is given, but the core invocation context is complete.

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?

Only one parameter exists with 100% schema description coverage, so the schema already documents 'company' with an example. The description adds no extra syntax or formatting guidance for the parameter, making the baseline 3 appropriate.

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+resource ('Check an employer against the fair hiring badge') and frames it with the user question 'is this employer fair to applicants?'. It enumerates the four checks and how the badge is earned, so an agent can distinguish it from siblings like employer_reply_rate or company_lookup, which each cover a single facet.

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?

Gives a clear context for use via the quoted user question, which maps intent to this tool well. However, it never names alternatives or when-not-to-use conditions, e.g. that employer_reply_rate or check_salary isolate one of the checks, so routing among near-siblings is left partly to inference.

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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