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BACH-AI-Tools

LinkedIn Data API MCP Server

get_post_reactions

Retrieve the profiles of users who reacted to a LinkedIn post, providing data for engagement analysis and audience insights.

Instructions

Get profiles that reacted to the post

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Behavior1/5

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

With no annotations provided, the description carries the full burden of behavioral disclosure. It fails to specify whether the tool is read-only, requires authentication, has rate limits, or what the output format is. The minimal description offers no transparency beyond the basic action.

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 concise sentence with no unnecessary words. However, it is too brief and omits critical details, which slightly detracts from its effectiveness.

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?

For a tool with no parameters, no output schema, and no annotations, the description must be self-contained. It does not explain how the post is specified, what the return value looks like, or any potential constraints. This incompleteness forces the agent to rely on assumptions.

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 input schema has zero parameters, so baseline is 4. However, the description does not clarify how the post is identified (e.g., implicitly from context), which is a gap. Since there are no parameters to describe, the score is reduced for missing contextual details.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose3/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description states the verb 'Get' and resource 'profiles that reacted to the post', which is clear in general but lacks specificity on how the post is identified. Since the input schema has no parameters, the description does not explain how the target post is determined, leaving ambiguity.

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 is provided on when to use this tool versus alternatives like get_article_reactions or get_profile_reactions. There is no mention of context, prerequisites, or exclusions.

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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