4dayweek.io Jobs

Market statistics

get_market_stats

Read-onlyIdempotent

Aggregate statistics on the reduced-hours job market: how many employers are tracked, how many run each schedule type, the distribution of weekly hours, and which day the non-working day falls on.

Use this for "how common is a 4-day week" questions. The response separates genuinely reduced-hours employers from compressed 4x10 employers, and reports the full-pay and pro-rata splits separately, so quote whichever the question actually asked for. Figures carry an as_of date; cite it.

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": "get_market_stats"
  }
}

Input Schema

Name	Required	Description	Default
No arguments

Output Schema

Name	Required	Description	Default
`as_of`	No
`notes`	No
`full_data`	No
`live_jobs`	No
`methodology`	No
`companies_tracked`	No
`four_day_week_day_off`	No
`four_day_week_full_pay`	No
`four_day_week_pro_rata`	No
`companies_by_schedule_type`	No
`companies_by_hours_full_time`	No
`four_day_week_fixed_day_total`	No
`genuinely_reduced_hours_total`	No
`compressed_4x10_not_a_4_day_week`	No

Schema Changelog

Changes observed during successful MCP inspections.

First observedOct 13, 2026

TDQS

A4.5/5.0

Behavior4/5

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

Annotations already cover read-only, idempotent, non-destructive semantics, so the bar is lower. The description adds real behavioral context beyond them: the aggregation separates genuine reduced-hours employers from compressed 4x10 employers, reports full-pay and pro-rata splits separately, and carries an as_of date that should be cited.

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?

Three sentences, front-loaded with what is aggregated, followed by when to use it and how to report the results. Every sentence carries distinct, actionable information with no filler.

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?

An output schema exists, so return structure needn't be explained. For a parameterless read-only statistics tool, the description covers scope, usage trigger, data-segmentation caveats, and the as_of freshness convention — nothing an agent needs is missing.

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?

The tool takes zero parameters, so there is nothing for the description to disambiguate; baseline 4 applies. No input semantics are needed.

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 precise content: employer counts, schedule-type distribution, weekly-hours distribution, and non-working-day distribution. It is unmistakably the aggregate/statistics tool among siblings like get_company, search_companies, and search_jobs, which are entity-level lookups.

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 concrete triggering question ("how common is a 4-day week") and instructs the agent to quote the full-pay vs pro-rata split the question actually asked for. It stops short of naming explicit alternatives or when-not-to-use conditions, but the usage context is clear.

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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