Skip to main content
Glama

Pay Transparency Rules for Job Posts

check_job_post

Checks a job post against pay transparency laws before it is published. Give every location the job is based in or could be done from, whether it can be done remotely, the employer headcount and the posting date. Returns each law that applies (or may apply, with the reason), a merged checklist of what the post must include (for example a good-faith minimum and maximum pay range and a description of benefits), salary history question bans, penalties and the official source and citation per law. Covers US states and cities, Canadian provinces and the EU Pay Transparency Directive (EU) 2023/970 country by country, including countries that have not transposed it yet. Free.

Input Schema

NameRequiredDescriptionDefault
dateNoPosting date, YYYY-MM-DD. Defaults to today. Future dates include laws already enacted with a later start.
remoteNoTrue if the job can be done remotely. Many US laws then apply to remote jobs that could be done in their state.
locationsYesWhere the job is based or could be done. Each item is a string like "Denver, CO", "New York City", "Ontario, Canada", "Germany", or an object {country, state, city}.
remote_scopeNoIf remote, where from: "US", "EU", "Canada" or "anywhere". Default: the countries of the locations given.
employer_employeesNoTotal employees. Several laws only cover employers above a size. Optional.

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A4.5/5.0
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 well: it discloses the evaluation point in the workflow, the deposited coverage (US states/cities, Canadian provinces, EU 2023/970 including non-transposed countries), that 'may apply' results come with a reason, and that the service is free. It omits auth requirements, rate limits or determinism guarantees.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

Four tight sentences ordered as purpose, required inputs, return contents, and coverage/cost. Every sentence earns its place and nothing is repeated.

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?

There is no output schema, so the description must describe the return values, and it does so in detail (applicable laws, reasons for 'may apply', merged checklist with example requirements, salary-history bans, penalties, per-law citation). Combined with full parameter documentation, an agent has everything needed to call and interpret it.

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 coverage is 100% so the baseline is 3, but the description adds rationale beyond the schema by explaining why the caller must enumerate every base or workable location, remote status, headcount and posting date — linking each input to whether a law applies.

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 ('Checks a job post against pay transparency laws') and scopes the timing ('before it is published'), which clearly distinguishes it from the sibling list_* tools that only enumerate laws or changes.

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 clear invocation context ('before it is published') and tells the caller exactly what inputs to supply, but never names an alternative tool or states when to use list_pay_transparency_laws instead.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Try in Browser

Glama MCP Gateway

Add one secure layer between your agents and this server.

Resources