like_post
Like or react to a LinkedIn post by specifying the post's URN. Enable AI agents to engage with LinkedIn content.
Instructions
Like/react to a LinkedIn post
Input Schema
| Name | Required | Description | Default |
|---|---|---|---|
| post_urn | Yes | URN of the post to like |
Like or react to a LinkedIn post by specifying the post's URN. Enable AI agents to engage with LinkedIn content.
Like/react to a LinkedIn post
| Name | Required | Description | Default |
|---|---|---|---|
| post_urn | Yes | URN of the post to like |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, and the description only mentions 'like/react' without disclosing whether it supports multiple reaction types, idempotency, or notification effects. The description carries the burden but is insufficient.
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?
Single sentence, no wasted words. Front-loaded with the core action.
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 simple single-parameter tool with no output schema, the description is largely complete. However, it lacks details on reaction types or whether the tool can be used for other reactions beyond a simple like.
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 covers 100% of parameters with a description. The tool description adds no extra meaning beyond the schema, so baseline of 3 applies.
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 verb 'like/react' and the resource 'LinkedIn post', distinguishing it from sibling tools like comment_on_post or create_post.
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?
No explicit guidance on when to use this tool versus alternatives like comment_on_post or other reaction tools. Usage is implied but not stated.
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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