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southleft

LinkedIn Intelligence MCP Server

by southleft

create_reaction

Add reactions to LinkedIn posts and comments using the Official API. Supports multiple reaction types including Like, Celebrate, Love, Insightful, Support, and Funny to engage with content.

Instructions

Add a reaction to a LinkedIn post or comment using the Official API.

Requires "Community Management API" product enabled in your LinkedIn Developer app.

Args: target_urn: The URN of the post or comment to react to (e.g., "urn:li:share:123456", "urn:li:activity:123456", "urn:li:comment:(urn:li:activity:123,456)") reaction_type: Type of reaction to add. Options: - LIKE (👍 Like) - default - PRAISE or CELEBRATE (👏 Celebrate) - EMPATHY or LOVE (❤️ Love) - INTEREST or INSIGHTFUL (💡 Insightful) - APPRECIATION or SUPPORT (🙏 Support) - ENTERTAINMENT or FUNNY (😄 Funny)

Returns the created reaction details.

Note: The MAYBE reaction type is deprecated and no longer supported.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
target_urnYes
reaction_typeNoLIKE

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Behavior4/5

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

With no annotations provided, the description carries full burden and does well by disclosing: the API requirement, what gets created (reaction details returned), and behavioral notes about deprecated reaction types. It doesn't mention rate limits, authentication specifics, or error conditions, but provides substantial 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.

Conciseness4/5

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

Well-structured with purpose statement, prerequisite, parameter documentation, return information, and important note. Every sentence earns its place, though the reaction options list is somewhat lengthy but necessary. Could be slightly more front-loaded with the core purpose.

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

Completeness5/5

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

Given the tool's moderate complexity (2 parameters, mutation operation), no annotations, but with output schema present, the description is remarkably complete. It covers purpose, prerequisites, parameter details, return information, and important behavioral notes about deprecated functionality - providing everything needed for effective use.

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

Parameters5/5

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

With 0% schema description coverage, the description fully compensates by providing detailed parameter semantics: explains what target_urn represents with concrete examples, documents all reaction_type options with their display equivalents, and specifies the default value. This adds significant value beyond the bare schema.

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 the specific action ('Add a reaction') and target resource ('to a LinkedIn post or comment') using the verb+resource pattern. It distinguishes this tool from sibling tools like 'create_comment' or 'delete_reaction' by focusing specifically on reaction creation.

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

Usage Guidelines4/5

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

The description provides clear context about when to use this tool (for adding reactions to LinkedIn content) and includes an important prerequisite ('Requires "Community Management API" product enabled'). However, it doesn't explicitly contrast when to use this versus alternatives like 'delete_reaction' or other engagement tools.

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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