LinkedIn Intelligence MCP Server

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

No annotations are provided, so the description carries the full burden. It discloses that the tool uses the Official API and requires a specific product enabled, adding useful context. It also clarifies that it 'removes your reaction,' indicating ownership and scope. However, it lacks details on permissions, rate limits, error handling, or what 'success status' entails, leaving gaps in behavioral understanding for a mutation tool.

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

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

The description is well-structured and front-loaded with the core purpose, followed by prerequisites, parameter details, return info, and a clarifying note. Each sentence adds value without redundancy, such as the note reinforcing the action's scope. It efficiently covers key points in a compact format, making it easy to parse.

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

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

Given the tool's complexity (a mutation with no annotations but an output schema), the description is mostly complete. It covers purpose, prerequisites, parameter meaning, and return indication ('Returns success status'), with the output schema likely handling return details. However, it could improve by addressing error cases or side effects, slightly reducing completeness for a deletion operation.

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

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

The input schema has 0% description coverage, but the description compensates by explaining the 'target_urn' parameter: it specifies the URN of the post or comment, provides examples (e.g., 'urn:li:share:123456'), and clarifies its purpose ('to remove reaction from'). This adds meaningful semantics beyond the bare schema, though it could detail format constraints or validation rules more explicitly.

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

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

The description clearly states the specific action ('Remove a reaction') and target resource ('from a LinkedIn post or comment'), using the Official API. It distinguishes itself from sibling tools like 'create_reaction' by specifying the opposite operation, and from other deletion tools (e.g., 'delete_post', 'delete_comment') by focusing on reactions rather than content.

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

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

The description provides clear context for when to use this tool: when needing to remove a reaction from LinkedIn content. It explicitly mentions the prerequisite ('Requires "Community Management API" product enabled'), which is helpful guidance. However, it does not explicitly state when not to use it or name specific alternatives among siblings, such as distinguishing from 'delete_post' or 'delete_comment' for content removal.

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