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iGaming Tools — independent slot, provider & regulator reference data

List jobs

list_jobs
Read-only

List iGaming job vacancies.

igaming_segment / remote_mode / employment_type / seniority: exact filters.
country: location ISO-2 country code.
company / city: slug filters.
q: free-text title search (icontains).
posted_after / posted_before: ISO-8601 datetime range on posted_at.
include_closed: include recently-closed vacancies (default: active only).
source: 'careers' or 'linkedin'.
cursor: opaque pagination cursor from a previous response.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
qNo
cityNo
cursorNo
sourceNo
companyNo
countryNo
page_sizeNo
seniorityNo
remote_modeNo
posted_afterNo
posted_beforeNo
include_closedNo
employment_typeNo
igaming_segmentNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

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?

Annotations already declare readOnlyHint=true, but the description adds valuable behavioral details: default active-only behavior via include_closed, case-insensitive title search (icontains), ISO-8601 date range format, and opaque cursor pagination. This goes beyond the annotation and helps the agent understand tool behavior without contradicting it.

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?

The description is a tight, front-loaded bullet list that conveys all essential information with no fluff. First sentence states the purpose; subsequent lines enumerate filters in a scannable format. Every sentence earns its place.

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?

With an output schema present, the description need not explain return values. It covers parameter interpretations, default behavior, allowed source values, and cursor usage. The only gap is the undocumented page_size parameter, which slightly reduces completeness for a complex, 14-parameter tool.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters5/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 0%, so the description fully compensates by explaining 13 of 14 parameters with precise semantics (e.g., country as ISO-2, company/city as slug filters, q as icontains, posted_after/before as datetime range, source restricted to 'careers' or 'linkedin'). Only page_size is omitted, but the overwhelming coverage earns a top score.

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?

The description clearly states the tool's function: 'List iGaming job vacancies.' This is a specific verb+resource pairing that distinguishes it from sibling tools, which concern news, providers, slots, regulators, and sources. The scope is unambiguous.

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?

While no explicit alternatives are named, the tool is the only jobs-focused tool among siblings, making its usage context clear. The description provides a comprehensive list of filters, indicating it is the go-to tool for querying job vacancies. It lacks explicit 'when not to use' guidance, but domain clarity compensates.

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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