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ZLeventer

linkedin-campaign-manager-mcp

li_list_campaign_groups

List campaign groups in a LinkedIn ad account, returning name, status, total budget, run schedule, and campaign count to understand account structure before pulling campaign-level data.

Instructions

List campaign groups in a LinkedIn ad account. Campaign groups are containers that group related campaigns under a shared name and optional total budget cap. Returns group name, status, total budget, run schedule, and the campaigns count. Use to understand account structure before pulling campaign-level data.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
ad_account_idNo
statusNo
page_sizeNo
Behavior3/5

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

No annotations are provided, so the description must cover behavioral traits. It mentions the returned fields but omits details like pagination behavior, error handling, authentication requirements, or rate limits. The description is adequate for a simple list operation but lacks comprehensive transparency.

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, front-loaded with purpose and output, then usage guidance. No redundant or extra words. Every sentence adds value and is easy to parse quickly.

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

Completeness3/5

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

Given no output schema and moderate complexity (3 params), the description lacks parameter details and pagination behavior. It covers purpose and output fields partially but not fully. It is usable but leaves the agent with unanswered questions for robust invocation.

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

Parameters1/5

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

With 0% schema description coverage, the description must explain parameters. It does not mention ad_account_id, status, or page_size at all. The only hint is 'in a LinkedIn ad account' implying ad_account_id, but no details on usage, default, or enum meanings. This is a critical gap.

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 lists campaign groups in a LinkedIn ad account, defines what campaign groups are, and specifies the returned fields (name, status, total budget, run schedule, campaigns count). It distinguishes from siblings by advising use before pulling campaign-level data, making its purpose unmistakable.

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 explicitly states when to use: 'Use to understand account structure before pulling campaign-level data,' providing a clear context. It lacks explicit alternatives or when-not-to-use guidance, but the context is strong enough to guide selection among siblings.

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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