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Seo Linkedin Ad Library

seo_linkedin_ad_library
Read-only

LinkedIn Ad Library search (ads LinkedIn discloses publicly, including EU/EEA): up to 24 ads per page with ad id, advertiser, format (single image, video, carousel, document), creative type, tagline, ad text, links and detail link. Search by keyword and/or advertiser, optionally one country and a time window. From linkedin.com/ad-library via a residential proxy. Price: $0.01 in USDC per successful call, paid with x402 (Base, Solana or Arc); failed calls are not charged.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
periodNoOptional: last-30-days, current-month, current-year, last-year
countryNoOptional two-letter country code where the ad ran, e.g. US, DE
keywordNoWords in the ad, e.g. software, cybersecurity
advertiserNoAdvertiser (company) name, e.g. Microsoft

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A4.4/5.0
Behavior5/5

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

Beyond the annotations, it discloses that results come via a residential proxy, are capped at 24 ads per page, that access is paid at $0.01 USDC per successful call via x402 on Base/Solana/Arc, and that failed calls are not charged. Cost and payment mechanics are exactly the kind of context an agent cannot infer from readOnlyHint/openWorldHint.

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 sentences, front-loaded with what the tool returns and how to filter, with pricing/auth kept in a separate trailing sentence. The field enumeration is dense but each item tells the agent what to expect in the response.

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?

Covers source, filters, result shape, coverage caveat (publicly disclosed, incl. EU/EEA), and full cost model; with an output schema present it need not explain return values. It leaves one real gap: it mentions 'per page' but no page/cursor parameter exists, so pagination behavior is unstated.

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, and the description adds a genuine constraint the schema does not: only ONE country may be supplied, and keyword and advertiser are combinable via 'and/or'. It does not clarify behavior when both keyword and advertiser are omitted.

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?

States a specific verb and resource ('LinkedIn Ad Library search') plus the exact data returned (ad id, advertiser, format, tagline, ad text, links) and the source (linkedin.com/ad-library). The resource is distinct from the nearest sibling, search_google_ads, so an agent can select it without opening either schema.

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?

It says how to combine filters ('by keyword and/or advertiser, optionally one country and a time window'), which implies at least one identifier is expected, but there is no explicit when-to-use/when-not, no prerequisites, and no comparison against alternatives such as search_google_ads.

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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