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zackscriven

ghl-mcp-server-v2

by zackscriven

ghl_ad_google_segment_offline_job_create

Create an offline user list job to upload customer data to a Google Customer Match list for ad targeting. Requires location ID and supports optional CSV file and smart list IDs.

Instructions

Create offline user list job Create a job to upload users to a Google customer match list Endpoint: POST /ad-publishing/google/segments/offline-user-list-job (Version header: 2021-07-28; source: v3/ad-publishing-v3.json) OAuth scopes: adPublishing.write

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
bodyYesRequest body (schema carried verbatim from the official OpenAPI spec).
Behavior3/5

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

Annotations already indicate a write operation (readOnlyHint=false) and non-destructive behavior (destructiveHint=false). The description adds endpoint and OAuth scopes, but these are technical details rather than behavioral traits like job processing or return values. No new behavioral insights beyond annotations.

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 very concise, with a clear header line, one line explaining the purpose, and then endpoint and scopes. Every sentence adds value without repetition or fluff.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness2/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Despite having no output schema, the description does not hint at what the tool returns (e.g., job ID, status). The creation process's nature (synchronous or async) is unmentioned. This lack of output context leaves a significant gap for an effective create operation.

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 coverage is 100% with descriptions and examples for all parameters. The description does not add any explanation beyond what the schema provides, so it meets the baseline but does not enhance understanding.

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 creates an offline user list job for uploading users to a Google customer match list. It uses a specific verb (Create) and resource (offline user list job), and the sibling tools like ghl_ad_google_segment_upsert are for different purposes, so this tool is well-distinguished.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines3/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description implies usage for uploading users to a customer match list but does not explicitly state when to use this tool versus alternatives or provide conditions for not using it. No exclusions or alternatives are mentioned, offering only implied guidance.

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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