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flin-agency

flin-linkedin-posts-mcp

by flin-agency

get_post_social_metadata

Retrieve comment and reaction summaries for a single LinkedIn post to analyze engagement.

Instructions

Fetch comment and reaction summary data for a single LinkedIn post

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
post_urnNo
post_urlNo
Behavior2/5

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

With no annotations, the description carries full burden for behavioral traits. It only states 'Fetch' which implies a read operation, but provides no details about authentication, rate limits, error conditions, or side effects.

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?

The description is a single, efficient sentence with no redundancy. However, its brevity sacrifices necessary detail, making it less helpful than a slightly longer but more informative description.

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

Completeness2/5

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

Given the lack of annotations, output schema, and parameter descriptions, the description is insufficient. An agent cannot determine required inputs or expected output beyond the vague notion of 'comment and reaction summary data'.

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

Parameters1/5

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

Schema coverage is 0% and the description does not explain the two parameters (post_urn, post_url). The agent has no information on what these parameters represent or how to use them.

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 explicitly states the action (Fetch), the resource (comment and reaction summary data), and the scope (single LinkedIn post). It clearly distinguishes from siblings like get_member_post_analytics and enrich_member_posts_with_engagement.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines2/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

No guidance on when to use this tool vs alternatives. The description does not mention any prerequisites, context, or scenarios where this tool is preferred over similar tools like get_member_post_analytics.

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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