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Mohamed-Godaa

LinkedIn MCP for OpenWorker

linkedin_get_post

Read-only

Fetch a LinkedIn post using its URN to access the post content and metadata. Use this tool to retrieve specific post details for reading or authoring workflows.

Instructions

Retrieve a LinkedIn post by URN.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
post_urnYes
access_tokenNoOptional token. Defaults to the stored OAuth token, then LINKEDIN_ACCESS_TOKEN.
view_contextNoREADER
Install Server

TDQS

A3.6/5.0
Behavior3/5

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

The readOnlyHint annotation already signals this is a safe read operation, and the description's 'Retrieve' wording is consistent with that. The description does not add much behavioral context beyond the schema, such as response shape, authentication expectations, or error behavior, but it also introduces no contradiction.

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?

The description is a single, front-loaded sentence with no filler. It communicates the core purpose efficiently and is well-sized for a straightforward retrieval tool.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness3/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a simple read operation, the core call pattern is clear, and annotations cover safety. However, the description leaves the view_context parameter unexplained and does not describe what the returned post object contains, which is a notable gap given there is no output schema.

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

Parameters2/5

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

Schema description coverage is only 33%. The description mentions URN-based lookup but does not explain the meaning of view_context (READER vs AUTHOR) or how it affects the response, and it adds little beyond the property name 'post_urn' already present in the schema.

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 and resource: 'Retrieve a LinkedIn post by URN.' This clearly distinguishes the tool from siblings like create_text_post and find_posts_by_author, which involve different operations and inputs.

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 using this tool when you have a LinkedIn post URN and need the post's details. However, it provides no explicit guidance about when not to use it or when to prefer find_posts_by_author instead.

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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