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AdsAgent — TikTok Ads MCP

templates_get

Get one saved template owned by the authenticated user by exact template_name (preferred, Meta-portable) or template_id. Mirrors Meta templates_get. A missing exact selector returns complete=true, found=false, status=not_found as a normal read — it does not authorize a write. Returns Meta-wire (adset_params) and TikTok-native (adgroup_params) keys plus effective_creation_defaults (CBO/ABO budget_level, is_smart_plus, identity, copy/CTA, ad_format and music_info). Create preparation preserves the template's explicit music choice and verifies that exact track for the target advertiser before approval. An unavailable track requires a new explicit choice, not silent replacement.

REQUIRED: template_id OR template_name. EXAMPLE: templates_get({"template_name": "iOS14 AEO"}) EXAMPLE: templates_get({"template_id": ""})

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
template_idNo
template_nameNo

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A4.8/5.0
Behavior5/5

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

With no annotations provided, the description carries the full burden and does so thoroughly. It discloses the not_found edge case (`complete=true, found=false, status=not_found` as a normal read), the return key groups, and detailed downstream behavior around music preservation and explicit track verification.

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 dense but every sentence adds useful operational information, from selector behavior to return shapes to edge-case handling. Key requirements and examples are placed at the end for easy scanning, and there is no repetition of schema fields.

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 having no output schema or annotations, the definition gives the agent enough to call the tool correctly: required input, return key structure, missing-selector behavior, and follow-up implications. No critical operational detail needed for correct invocation is missing.

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 coverage is 0%, so the description is the only source of parameter meaning. It clearly explains both parameters, their roles as mutually exclusive selectors, the preference for `template_name`, and the required-one constraint, which the schema itself does not express.

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 states a specific verb and resource: retrieving one saved template by exact `template_name` or `template_id`. It also names the broader Meta API it mirrors, and the selector semantics make it distinguishable from sibling `templates_list` and other template tools.

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?

It explicitly states the required selector contract (`REQUIRED: template_id OR template_name`), marks `template_name` as preferred, and provides two concrete invocation examples. It does not explicitly contrast with siblings, but the context is clear enough for an agent to know when this single-fetch tool is appropriate.

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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