List Observation Types

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

Annotations already indicate a safe, read-only, idempotent operation. The description adds value by explaining pagination behavior (page, per_page, pagination metadata) and the parameter constraint that only one of the two required parameters is needed. No contradiction with annotations.

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 informative but slightly long, containing multiple sentences, a note, and endpoint reference. It is well-structured with the important constraint upfront, but could be trimmed slightly without losing clarity.

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?

With no output schema, the description covers the core functionality, pagination, and the key parameter nuance. It does not detail return fields beyond 'JSON array of Observations', but annotations and schema cover safety and parameters. It is sufficiently complete for agent invocation.

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?

Although the schema covers all parameters with descriptions, the description provides critical semantic nuance: despite both project_id and company_id being marked required, only one needs to be passed. This goes beyond schema and resolves ambiguity, making parameter usage significantly clearer.

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 tool returns observation types, distinguishes between project and company scope, and explicitly mentions enumeration for paginated overview, ID lookup, and filtering. This provides a specific verb+resource with clear scope 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?

The description includes a crucial note about the required parameters being mutually exclusive (only one of project_id or company_id needed), and advises using the tool for paginated overviews and filtering. While it gives clear usage context, it does not explicitly list alternatives or when not to use it, which is acceptable given the specificity.

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