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Opus Growth, Ad Platforms MCP Connector

TikTok Location Search

tiktok_region_search
Read-onlyIdempotent

Searches TikTok geo-targeting location IDs (location_id) — for the required location_ids field in create_tiktok_adgroup.

objective_type MUST match the campaign's objective (TRAFFIC|REACH|VIDEO_VIEWS|CONVERSIONS|LEAD_GENERATION|...): TikTok returns the location set per objective. keyword matching is accent-insensitive, so Turkish spellings work ("Şehzadeler" finds "Sehzadeler"). Turkey goes down to DISTRICT level, returned as level=CITY under the PROVINCE (e.g. Manisa → Sehzadeler, Yunusemre, Turgutlu, Saruhanli) — search the district name directly instead of settling for the province. Each row carries parent_name (the province) because city/district names repeat worldwide — always check it before using an id.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
keywordNo
advertiser_idNo
objective_typeNoTRAFFIC

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

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TDQS

A4.1/5.0
Behavior4/5

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

Annotations already cover the read-only/idempotent safety profile, so the description wisely spends its budget elsewhere: objective-scoped location sets, accent-insensitive matching, Turkey's district-level (level=CITY under PROVINCE) behavior, and the parent_name disambiguation caveat. It does not contradict any annotation. It stops short of noting rate limits or result caps.

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

Conciseness4/5

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

Information-dense and front-loaded: the purpose and the downstream consumer come first, then objective constraint, then matching/level nuances. Nearly every sentence earns its place, though the Turkey district digression is long for what is a general-purpose tool.

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?

An output schema exists so return-format detail is unnecessary. The description adds the one return nuance an agent needs (parent_name as province) and covers two of three params well, with the only real gap being the unexplained advertiser_id parameter.

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

Parameters3/5

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

Schema description coverage is 0%, so the description carries the param burden. It ably explains objective_type (with the allowed enum values) and adds real meaning to keyword (accent-insensitive, Turkish spellings), but advertiser_id is never mentioned, leaving one of three params undocumented.

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 ('Searches TikTok geo-targeting location IDs') and immediately anchors the output to its consumer ('the required location_ids field in create_tiktok_adgroup'). This clearly distinguishes it from siblings like geo_target_search, microsoft_location_search, and tiktok_targeting_search without opening any schema.

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?

Provides strong context on when to reach for it (populating location_ids in create_tiktok_adgroup) and what objective_type must satisfy. It falls short of 5 because it does not explicitly name or exclude the closest sibling geo-lookup alternatives, leaving the agent to infer platform routing.

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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