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Get one ad from LinkedIn's Ad Library

get_linkedin_ad

Fetch one ad in full by its id or URL: what linkedin/ads gives, and where it was seen, country by country, with its targeting. Give exactly one of id or url. Costs 7 credits, cached or not; a failed call is refunded.

Input Schema

NameRequiredDescriptionDefault
idNoThe Ad Library's id for the ad: `id` in linkedin/ads.
urlNoThe ad's page in the Ad Library: `https://www.linkedin.com/ad-library/detail/<id>`.
freshNoSkip the cache and fetch now. Charged normally. Not available on trial credits — buy any pack to unlock it.

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A4.2/5.0
Behavior4/5

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

With no annotations, the description carries the burden and does real work: it discloses the cost (7 credits), that caching does not change the price, and that failed calls are refunded. It also characterizes the breadth of the response (per-country sightings, targeting). It still omits auth/permission requirements, which is the notable remaining gap.

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?

Three tight clauses front-loaded with purpose, then the input constraint, then the cost/refund caveat. No filler and nothing buried, though the passive 'Costs 7 credits' sentence carries slightly off-topic pricing detail that is nonetheless useful.

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 single-record fetch with no output schema, the description covers purpose, input cardinality, cost and refund policy, and the shape of the return. The main omission is any note on prerequisites or on where ids come from, which leaves one inference to the agent.

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

Parameters4/5

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

Schema coverage is 100%, so the baseline is 3, but the description adds a genuine constraint the schema does not encode: the schema marks no parameters required, yet the description says exactly one of `id` or `url` must be supplied. That clarification is meaningful beyond the structured field.

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?

Specific verb ('Fetch') plus resource ('one ad') plus identifier modes, and it enumerates what comes back ('what linkedin/ads gives, and where it was seen, country by country, with its targeting'). It is clearly distinguishable from the sibling search_linkedin_ads, which finds ads rather than retrieving one.

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 constrains input ('Give exactly one of `${id}` or `${url}`') but never states when to reach for this tool versus search_linkedin_ads, nor how to obtain an id in the first place. Usage is only implied by the 'fetch one by id' framing.

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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