Skip to main content
Glama
adops-tool

LinkedIn Ads MCP Toolkit

by adops-tool

get_lead_gen_performance

Read-onlyIdempotent

Retrieves lead generation form performance metrics—submissions, qualified leads, cost per lead—to help B2B marketers track and optimize campaigns.

Instructions

Retrieves lead generation form performance including form submissions, qualified leads, and cost per lead. Essential for B2B marketers running lead gen campaigns.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
endDateNoEnd date in YYYY-MM-DD format. Default: today
accountIdYesThe LinkedIn Ad Account ID
startDateYesStart date in YYYY-MM-DD format
campaignIdsNoFilter by specific campaigns
timeGranularityNoTime granularity. Default: ALL

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv1.1.0

TDQS

B3.2/5.0
Behavior3/5

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

Annotations already declare readOnlyHint, idempotentHint, non-destructive, and openWorld, so the safety profile is covered. The description adds the returned metric set (submissions, qualified leads, cost per lead), which is useful. It says nothing about date-range behavior, granularity effects, row limits, or aggregation semantics.

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?

Two sentences with the core capability front-loaded in the first. The second sentence is soft marketing copy that gives an agent little actionable value, but the whole definition is short enough that nothing is buried.

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?

A read-only analytics tool with complete schema coverage and no output schema; the description compensates by naming the metrics returned. Safety is covered by annotations. Missing only guidance on the analytics siblings, which is a usage rather than completeness gap.

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 all five parameters (accountId, startDate, endDate, campaignIds, timeGranularity) are documented at the schema level, including the enum and date format. The description adds no parameter-level meaning beyond that, so the baseline 3 applies.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

States a specific verb (retrieves) and resource (lead generation form performance) plus the three metric families returned: submissions, qualified leads, cost per lead. This distinguishes it from get_campaign_performance and get_conversion_performance by resource scope, though it never names those siblings explicitly.

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

Usage Guidelines2/5

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

The only usage signal is the audience tagline 'Essential for B2B marketers running lead gen campaigns' – a persona statement, not a condition. It gives no guidance on when to pick this over get_conversion_performance, list_lead_forms, or get_analytics, and states no prerequisites or exclusions.

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