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JavaScript
Remote

indeed_locations_suggest

Get Indeed location autocomplete suggestions from partial location text to build a valid l value for job searches. Returns the same location options as the search bar for accurate query setup.

Instructions

Indeed location suggestions. Returns Indeed's own location-search autocomplete suggestions for a partial location string -- the same suggestions the app's search bar offers -- for building a valid l value for search. Credential-free GraphQL only; there is no page-based fallback for this endpoint.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
qYesPartial location text
limitNoMax suggestions to return, defaults to 10, maxes at 25

Schema Changelog

Changes observed during successful MCP inspections.

  1. Added

TDQS

A4.5/5.0
Behavior4/5

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

With no annotations provided, the description carries the full burden. It discloses that the endpoint is credential-free and GraphQL-only, and that there is no page-based fallback. This is valuable behavioral context. It does not mention rate limits or response format, but for a simple autocomplete endpoint, the provided details are sufficient.

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 two sentences and highly efficient. The first sentence provides a succinct title-like summary, and the second delivers the operational detail. Every word earns its place, and the most important action is front-loaded.

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?

Despite lacking annotations and an output schema, the description is remarkably complete for a simple suggestion tool. It covers what the tool returns, why to use it, and a critical caveat (no fallback). Both parameters are documented in the schema, and the description provides the integration context. The agent can confidently invoke this tool and use the results.

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 100% (both q and limit are described). The description adds meaning beyond the schema by explaining that `q` is a partial location string used to generate suggestions that feed into the `l` parameter for search. This contextualizes the parameter's role, going beyond the bare schema description.

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 specific action ('Returns Indeed's own location-search autocomplete suggestions') and the resource (partial location string), with a clear purpose ('for building a valid `l` value for search'). It distinguishes itself from siblings by focusing on location suggestions for Indeed, and mentions the unique GraphQL-only nature.

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?

The description gives clear context: use this tool when you need location suggestions to construct a valid `l` value for Indeed search. It also notes there is no page-based fallback, implying when to rely on it exclusively. However, it does not explicitly name alternative tools or state when not to use it, so it lacks the explicit exclusions for a 5.

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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