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kLOsk

Google Ads - AdLoop

by kLOsk

Search Reddit targeting

search_reddit_targeting
Read-only

Find Reddit targeting options for ad groups by subreddit, interest, location, language, or keyword, and get related community suggestions with IDs for Google Ads targeting lists.

Instructions

Look up targeting options for draft_reddit_ad_group.

kind: "communities" (subreddits; query required), "interests" (query filters by name), "geolocations" (country ISO code and/or city query), "languages" (upper-case ISO 639-1 codes), "keywords" (comma-separated seed terms → suggestions with Reddit-wide monthly views), or "community_suggestions" (Reddit's related-community picks for seed communities in query, e.g. "PPC,googleads", and/or a website_url). Returns ids/names to pass into the targeting lists.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
kindYes
limitNo
queryNo
countryNo
website_urlNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. Addedv0.14.0

TDQS

A4.5/5.0
Behavior4/5

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

Annotations already mark this as read-only, and the description adds useful behavioral detail: it returns ids/names for targeting lists, requires particular input formats per kind, and notes that keyword suggestions include Reddit-wide monthly views. It does not discuss pagination or rate limits, but the output schema and readOnly annotation reduce the burden.

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 front-loaded with the core action, then compactly lists each kind with required formats and examples. Every clause adds operational value; the line structure and arrows make the options scannable without wasted words.

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 low schema coverage, the description covers the required kind, applicable queries, country, website_url, and the output shape of ids/names. An output schema exists, so return details need not be restated; nothing critical is missing for invoking the tool correctly.

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?

With 0% schema description coverage, the description carries parameter meaning almost entirely. It explains kind values and how query, country, and website_url are used. Only limit is left implicit, though its default and name make it low-risk.

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 opens with a specific verb and resource: 'Look up targeting options for draft_reddit_ad_group.' It then enumerates every kind of targeting, making the tool's scope unmistakable and distinguishing it from the broader Reddit management siblings.

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 intended use is clear: before drafting a Reddit ad group, look up targeting values. The kind-by-kind instructions give concrete conditions, such as query required for communities and country ISO code for geolocations. It does not explicitly name alternatives or when-not-to-use cases, but the context is strong.

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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