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isteamhq

@isteam/linkedin-mcp

by isteamhq

get_comments

Retrieve comments from a LinkedIn post using its URN. Customize the number of comments to fetch, up to 50.

Instructions

Get comments on a LinkedIn post

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
post_urnYesURN of the post to get comments for
countNoNumber of comments to fetch
Behavior1/5

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

No annotations are provided, so the description must disclose behavioral traits. It only says 'Get comments on a LinkedIn post' with no mention of authentication, rate limits, or any side effects. This fails to inform the agent of important operational context.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness3/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is extremely short (5 words), which is concise but at the expense of completeness. It lacks structure such as examples or sections, and while every word earns its place, the overall informativeness is minimal.

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 tool has no output schema, no annotations, and only two parameters, the description should provide more context about the return format or behavior. It is incomplete for a tool that retrieves data, leaving the agent uninformed about what the response contains.

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 covers 100% of parameters with descriptions, so the baseline is 3. The tool description adds no additional semantics beyond what the schema already provides, so it neither improves nor detracts.

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?

The description clearly states the verb 'Get' and the resource 'comments on a LinkedIn post', making the tool's purpose unambiguous. However, it does not differentiate from sibling tools like 'get_post' or 'get_post_stats', which are also simple retrieval operations.

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 such as 'get_post' or 'get_post_stats'. There is no mention of prerequisites, context, or when not to use it.

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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