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linkedin_product

Retrieve LinkedIn product details by ID, including name, category, organization, media, featured customers, and similar products, so you can enrich product research.

Instructions

Get LinkedIn Product info by ID. Returns a LinkedIn product page by its product id. The response has the name, about text, category, owning organization, external link, logo, cover image, media items, featured customers with industry and follower count, and lists of other and similar products.

Input Schema

NameRequiredDescriptionDefault
idYesLinkedIn Product ID

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv1.0.0

TDQS

A3.5/5.0
Behavior3/5

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

No annotations are provided, so the description carries the full burden. It helpfully enumerates the return payload (name, about, category, owning organization, featured customers, similar products), which compensates for the missing output schema, but it says nothing about auth requirements, rate limits, or error behavior for an invalid ID.

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?

Opening sentence is front-loaded with purpose, and the follow-up sentence carries the payload contents. The field enumeration is long but functional since no output schema exists. No wasted framing.

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 read-only fetch with one required ID and no output schema, the description is complete enough: it tells the agent exactly what the returned product page contains so callers know if the data meets their need. Only the absence of any auth/error context keeps it from full marks.

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% for the single 'id' parameter, so the schema already documents it. The description only restates that the lookup is by 'product id', adding no format, source, or resolution detail beyond the schema. 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 (Get) and resource (LinkedIn Product info) scoped 'by ID', which cleanly separates it from the sibling search tool linkedin_products_search and from linkedin_product_categories. It stops short of naming the alternatives explicitly, but an agent can distinguish it from siblings on the 'by ID' qualifier alone.

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 'by ID' phrasing implies that a product ID is required and that search-style discovery is a different tool, but there is no explicit when-to-use guidance or named alternative. Usage is inferable rather than stated.

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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