create_poll

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

With no annotations provided, the description carries the full burden. It discloses that this creates content via the LinkedIn API and mentions a product requirement, but doesn't cover important behavioral aspects like rate limits, authentication needs beyond the product requirement, error conditions, or whether the operation is idempotent. It does state what gets returned ('Returns the created poll post details').

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 efficiently structured with a clear purpose statement, prerequisite, parameter details in a readable format, and return information. Every sentence earns its place, and the information is front-loaded with the core functionality first.

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?

Given the tool has an output schema (true), the description doesn't need to detail return values. It covers the creation purpose, prerequisites, and parameter semantics well. However, as a mutation tool with no annotations, it could benefit from more behavioral context about permissions, side effects, or error handling.

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?

With 0% schema description coverage, the description fully compensates by providing detailed semantics for all 4 parameters: question (purpose, character limit, dual use as post text), options (format, count range, character limits), duration_days (allowed values, default), and visibility (allowed values). This adds substantial value beyond the bare schema.

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 specific action ('Create a LinkedIn poll') and resource ('using the Official API'), distinguishing it from sibling tools like create_post, create_image_post, or create_document_post. It specifies this is for polls specifically, not general posts.

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 provides clear context about when to use this tool ('Create a LinkedIn poll') and includes an important prerequisite ('Requires "Share on LinkedIn" product enabled in your LinkedIn Developer app'). However, it doesn't explicitly state when NOT to use it or name specific alternatives among the sibling tools.

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