List Company Observation Types

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

Annotations already declare readOnlyHint=true and destructiveHint=false, so the agent knows it's safe. The description adds value by detailing pagination behavior ('Use page and per_page to control pagination; the response includes pagination metadata'), which is beyond what annotations provide.

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 concise, using four sentences to cover purpose, usage, pagination, and required parameter. Every sentence adds value, and the key information is front-loaded.

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's simplicity (list endpoint with pagination, 3 parameters, no output schema), the description is complete: it explains what it returns, when to use it, how to paginate, and even includes the API endpoint and module for reference.

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 100% schema coverage, the schema already describes parameters. The description adds context by explaining the purpose of page/per_page for pagination and noting that the response includes metadata. It also reinforces the required company_id.

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 verb ('Returns a list') and the resource ('all Company Observation Types associated to a Company'), distinguishing it from project-level observation type tools. The slight inconsistency in calling the result 'Observations' is minor and does not obscure the purpose.

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 explicit usage scenarios: 'enumerate Observations when you need a paginated overview, to find IDs, or to filter by query parameters.' It does not mention when not to use or contrast with sibling tools like list_observation_items, but the context is clear.

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