Comment on a post
commentPost a text comment on a LinkedIn post using the post ID and comment text to engage with your network.
Instructions
Leaves a text comment on a post.
Input Schema
| Name | Required | Description | Default |
|---|---|---|---|
| text | Yes | ||
| postId | Yes |
commentPost a text comment on a LinkedIn post using the post ID and comment text to engage with your network.
Leaves a text comment on a post.
| Name | Required | Description | Default |
|---|---|---|---|
| text | Yes | ||
| postId | Yes |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries full responsibility for behavioral disclosure. 'Leaves' implies a mutation, but the description does not mention required permissions, whether the comment is publicly visible, whether it can be edited or removed, or what the response will be.
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 a single, clear sentence with no filler or repetition. It is front-loaded and easy to parse, though it is also terse enough that some behavioral and parameter context is missing.
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?
For a simple two-parameter mutation tool, the description captures the core operation acceptably. However, with no annotations and no output schema, the absence of return-value or effect information leaves the agent without a full picture of what happens after the call.
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?
Schema description coverage is 0%, so the description must compensate for undocumented parameters. It only adds the concept of a 'text comment on a post', which loosely maps to 'text' and 'postId', but offers no detail about formats, constraints, or how the parameters relate.
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 action ('Leaves') and the resource ('a text comment on a post'). It is distinguishable from siblings like 'react' (non-text reaction) and 'create_post' (creating a new post), though it does not name any alternatives explicitly.
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 implies when to use this tool: whenever a text comment needs to be added to a post. However, it provides no explicit guidance about when not to use it or when to prefer a sibling such as 'react' or 'send_message'.
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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