Skip to main content
Glama

linkedin_post_details

Get detailed information about a specific LinkedIn post by URL. Returns full post text, author details, and engagement metrics (likes, comments, shares, reaction breakdowns).

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
urlYesLinkedIn post URL
get_sentimentNoAdd AI sentiment analysis (Plutchik emotions, dominant_emotion, intensity, and positive/negative/neutral polarity) to each result. Adds a small surcharge per page, or per request on single-request endpoints.

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed1 schema field changed
    • changedInput schema / properties / get_sentiment / description
      Previous value: -"Add AI sentiment analysis (Plutchik emotions, dominant_emotion, intensity, and positive/negative/neutral polarity) to each result. Adds a small per-page surcharge."New value: +"Add AI sentiment analysis (Plutchik emotions, dominant_emotion, intensity, and positive/negative/neutral polarity) to each result. Adds a small surcharge per page, or per request on single-request endpoints."
  2. First observed

TDQS

A3.8/5.0
Behavior3/5

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

No annotations are provided, so the description carries the behavioral burden. It does convey that this is a retrieval operation and previews the return payload, which is useful. However, it does not mention authentication requirements, rate limits, public-post accessibility, or failure behavior, leaving a moderate transparency gap for a no-annotation tool.

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, well-structured sentence with no filler. It front-loads the core purpose and immediately specifies what the caller can expect in the response. Every part earns its place.

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 straightforward two-parameter retrieval endpoint, the description combined with the schema is largely sufficient: it names the required input, scopes the target, and describes the expected output categories. It omits edge-case caveats such as URL validity or privacy restrictions, but these are not essential for basic tool selection and invocation.

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?

The schema already covers both parameters at 100%: 'url' has a direct description and 'get_sentiment' has a detailed explanation. The tool description adds little beyond restating the URL requirement and does not clarify sentiment behavior. With full schema coverage, the baseline of 3 is appropriate.

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 clearly states a specific action and resource: 'Get detailed information about a specific LinkedIn post by URL.' It also enumerates the return contents, which distinguishes it from event-like siblings such as linkedin_company_posts or search_linkedin. The scope is unambiguous and immediately actionable.

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 the use case: call this when you already have a LinkedIn post URL and need post-level detail. However, it does not name alternatives or explain when not to use it, such as when looking for company posts or person posts. The 'by URL' condition provides context, but explicit routing guidance is missing.

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

Try in Browser

Glama MCP Gateway

Add one secure layer between your agents and this server.

Resources