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Create a post

create_post

Publish a text post to your personal LinkedIn profile right now. Share updates with your network in one action.

Instructions

Publish a text post to your personal LinkedIn profile, now. For a future time use schedule_post (which first asks the user native vs local scheduler).

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
textYesPost body.
Behavior3/5

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

The annotation readOnlyHint is false, which aligns with 'Publish' indicating a mutation. The description adds context that it acts immediately and targets the personal profile, but it doesn't disclose potential prerequisites like login state or side effects such as immediate visibility. However, the annotation already signals a write operation, so the description's added value is modest. No contradiction exists.

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 two focused sentences: the first states the action and scope, the second provides an alternative. Every word earns its place with no filler, making it highly efficient and front-loaded.

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

Completeness4/5

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

For a simple one-parameter mutation tool, the description covers the core purpose, immediate execution, and points to the scheduling alternative. It doesn't mention return values, but with no output schema and a straightforward action, this is not a significant gap. The context is sufficient for an agent to select and invoke the tool correctly.

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?

The input schema fully describes the only parameter 'text' with type, min/max lengths, and description. The description adds no parameter-specific details, but given 100% schema coverage, the baseline 3 applies. The description does not hinder parameter understanding.

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 uses a specific verb 'Publish' and identifies the exact resource: a text post to the user's personal LinkedIn profile. It clearly distinguishes from sibling tools by noting it does this 'now' versus scheduled posts, making the tool's purpose unambiguous.

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 instructs when to use this tool over the alternative: use schedule_post for future times, and even notes that schedule_post asks about native vs local scheduler. This gives clear guidance on when to choose create_post versus a specific sibling, which is exemplary.

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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