linkedin_post

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

With no annotations provided, the description carries the full burden of behavioral disclosure. It does state that the request is authenticated, which is useful, but it does not mention potential side effects, whether the POST is idempotent, required permissions, rate limits, or error behavior. This is a significant gap for a mutating operation.

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 extremely short, which is concise in length, but it under-specifies to the point of being unhelpful. While it has no wasted words, it also lacks essential structure and content needed to understand the tool's purpose and parameters.

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?

Despite having an output schema, the description is too minimal to support correct invocation. It omits parameter details, end-user expectations, and behavioral context. For a low-level helper with three parameters, the description provides far too little context, making the tool difficult to use safely and accurately.

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 explain the parameters, but it does not. It fails to clarify that 'path' is the endpoint path, 'body_json' is the request body, or 'api_version' is the API version. The schema only provides field names and defaults, leaving the agent without meaningful parameter semantics.

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 'Raw authenticated POST helper' clearly identifies the action (POST) and the scope (authenticated requests), which is distinct from the sibling tools focused on authentication and listing campaigns. However, it does not specify which LinkedIn resource or endpoint is targeted, so it is clear but lacks full sibling differentiation.

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 guidance is provided about when to use this tool versus alternatives. There is no mention of conditions, exclusions, or preferred use cases. The only implied usage is from the name and description, which is insufficient for an AI agent to decide between this and the sibling tools.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.