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fetch_post

Retrieve LinkedIn post data, including comments and reactions, by supplying the post URL.

Instructions

Open a LinkedIn post and retrieve its data, with optional comments and reactions. (st.openPost action).

Linked API actions are queued into a cloud-browser workflow and may take several minutes. The server returns immediately after starting the workflow with {status: 'pending'|'running', pendingReason, workflowId, operationName, message}. To retrieve the final result, call get_workflow_result with the returned workflowId and operationName — it will long-poll until completion or the request budget elapses, then return either the final result or another in-progress snapshot. Do not retry the original tool while a workflow is still running; that creates duplicate queued work.

A pending workflow carries pendingReason: 'queued' means it is waiting its turn behind other work on the same account and will start within minutes. 'outsideWorkingHours' means the account has configured working hours and the workflow is parked until they reopen — possibly the next working day. In that case get_workflow_result returns immediately instead of polling, message states when the window opens, and you should report that to the user rather than looping.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
postUrlYesLinkedIn URL of the post. (e.g., 'https://www.linkedin.com/posts/username_activity-id')
retrieveCommentsNoOptional. When true, also retrieve comments for the post. Configure via commentsRetrievalConfig.
retrieveReactionsNoOptional. When true, also retrieve reactions for the post. Configure via reactionsRetrievalConfig.
commentsRetrievalConfigNoOptional. Applies only when retrieveComments is true. Controls comments retrieval (limit, replies, sort).
reactionsRetrievalConfigNoOptional. Applies only when retrieveReactions is true. Controls reactions retrieval (limit).
Behavior5/5

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

With no annotations provided, the description fully discloses the tool's asynchronous behavior: it queues into a cloud-browser workflow, returns immediately with a pending/running status, and may take minutes. It also explains pendingReason semantics ('queued' vs 'outsideWorkingHours') and the risk of duplicate work. This is rich behavioral context beyond what any annotation would provide.

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

Conciseness5/5

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

The description is front-loaded with the core purpose in the first sentence, then logically organized into workflow behavior and pendingReason details. Every sentence provides essential information, including actionable instructions for the agent. Length is justified by the complexity of the async workflow.

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 complexity (async workflow, no output schema), the description is remarkably complete. It explains the immediate response, how to retrieve the final result via get_workflow_result, the meaning of pending reasons, and appropriate agent behavior. It covers all necessary operational context for correct usage.

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?

Schema description coverage is 100%, so the baseline is 3. The description mentions 'optional comments and reactions' but adds no meaning beyond the schema's detailed parameter descriptions. All parameter semantics are adequately handled by the input 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 a specific action: 'Open a LinkedIn post and retrieve its data, with optional comments and reactions.' It uses the verb 'retrieve' and identifies the resource (LinkedIn post). This distinguishes it from sibling tools like fetch_person or react_to_post, which target different resources or write actions.

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

Usage Guidelines5/5

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

The description explicitly provides when-to-use and when-not-to-use guidance. It instructs to call get_workflow_result for the final result, warns against retrying the original tool while a workflow is running (which creates duplicate queued work), and explains how to handle the 'outsideWorkingHours' pendingReason by reporting to the user rather than looping.

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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