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Linked-API
by Linked-API

react_to_post

React to any LinkedIn post with a chosen reaction type (like, love, support, celebrate, insightful, funny), optionally on behalf of a company page.

Instructions

Allows you to react to a post using any available reaction type (st.reactToPost action).

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
postUrlYesLinkedIn URL of the post to react. (e.g., 'https://www.linkedin.com/posts/username_activity-id')
typeYesEnum describing the reaction type.
companyUrlNoLinkedIn company page URL. If specified, the reaction will be added on behalf of the company. (e.g., 'https://www.linkedin.com/company/acme-corp')
Behavior2/5

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

With no annotations provided, the description carries full burden. It does not disclose that this is a mutating action (it implies modification but no explicit statement of side effects), nor does it mention authentication needs, rate limits, or what happens to the post.

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 that is front-loaded with the purpose. It wastes no words, though it could be slightly more informative without losing conciseness.

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 no annotations, no output schema, and the mutating nature of the tool, the description is too sparse. It fails to explain return values, error handling, or behavioral context needed for reliable selection.

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?

Input schema coverage is 100% with clear descriptions for all parameters. The description adds no extra semantic value beyond the schema, so it meets the baseline of 3.

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 action (react) and the resource (post), and distinguishes from sibling tools like comment_on_post or create_post by focusing on reactions. It also mentions that multiple reaction types are available.

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?

The description provides no guidance on when to use this tool versus alternatives, no prerequisites, and no context about when not to use it. It simply states the action without contextual usage advice.

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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