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linkedin-ads-mcp

list_conversions

Retrieve conversion tracking rules for a LinkedIn Ad Account. See conversion names, types, attribution windows, and enabled status to manage tracking efficiently.

Instructions

Lists all conversion tracking rules configured for an account. Shows conversion names, types, attribution windows, and enabled status.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
accountIdYesThe LinkedIn Ad Account ID
enabledOnlyNoOnly show enabled conversions. Default: false

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

A3.8/5.0
Behavior3/5

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

With no annotations provided, the description must carry the burden of behavioral disclosure. 'Lists' clearly implies a read-only operation and the description names the returned fields, but it does not mention pagination, rate limits, authentication requirements, or whether the response includes unconfigured rules. This is adequate but not rich.

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?

Two concise sentences deliver the core purpose and output contents with no filler. The primary action is front-loaded, and the second sentence adds useful detail without redundancy.

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?

For a simple two-parameter list tool with no output schema, the description covers what is listed and what fields are shown. It lacks explicit usage guidance and behavioral caveats, but the overall context is sufficient for an agent to call the tool correctly in most straightforward scenarios.

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 100%, so the input schema already fully documents accountId and enabledOnly. The description adds no parameter-specific meaning beyond the schema, which matches the baseline of 3 for high schema coverage.

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 action ('Lists all conversion tracking rules') and a clear resource ('configured for an account'), with the fields returned explicitly listed. This makes it easy to distinguish from siblings like get_conversion_performance, which is about performance metrics rather than rule configuration.

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 the tool is for retrieving conversion tracking rule configurations, but it does not explicitly state when to use it versus alternatives such as get_conversion_performance or list_lead_forms. There is no when-not guidance or mention of related tools, so usage context is only implicit.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.