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southleft

LinkedIn Intelligence MCP Server

by southleft

cancel_scheduled_post

Cancel a scheduled LinkedIn post by providing its job ID to remove it from the publishing queue.

Instructions

Cancel a scheduled post.

Args: job_id: ID of the scheduled post to cancel

Returns success status.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
job_idYes

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Behavior2/5

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

No annotations are provided, so the description carries the full burden of behavioral disclosure. It states the action ('Cancel') and return ('success status'), but lacks details on permissions required, whether cancellation is reversible, error conditions (e.g., invalid job_id), or side effects. For a mutation tool with zero annotation coverage, this 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.

Conciseness5/5

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

The description is extremely concise and well-structured: a clear purpose statement followed by parameter and return documentation in a bullet-like format. Every sentence earns its place with zero waste, making it easy to parse quickly.

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

Completeness3/5

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

Given the tool's moderate complexity (a mutation with one parameter) and the presence of an output schema (which handles return values), the description is minimally complete. However, with no annotations and incomplete behavioral context, it leaves gaps in understanding permissions, errors, and usage scenarios, making it adequate but not thorough.

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

Parameters4/5

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

The description explicitly documents the single parameter 'job_id' with its purpose ('ID of the scheduled post to cancel'), adding crucial meaning beyond the schema's 0% coverage. Since there's only one parameter and the description fully explains it, this compensates well for the schema gap, though it doesn't specify format or sourcing details.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool's purpose with a specific verb ('Cancel') and resource ('scheduled post'), making it immediately understandable. However, it doesn't differentiate from sibling tools like 'delete_post' or 'delete_draft' which might also remove content, so it doesn't fully distinguish its specific scope.

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. It doesn't mention prerequisites (e.g., needing a scheduled post ID), exclusions (e.g., cannot cancel already published posts), or compare to siblings like 'delete_post' for non-scheduled content. This leaves the agent with minimal context for decision-making.

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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