List Default Correspondence Types

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

Annotations already declare readOnlyHint=true, destructiveHint=false, idempotentHint=true, so the agent knows it's a safe, idempotent read. The description adds value by explaining pagination behavior (page/per_page control), response format (paginated JSON array with metadata), and the exact endpoint. 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 a single paragraph of moderate length, efficiently conveying purpose, usage context, pagination, and endpoint info. It is front-loaded with the core purpose. However, the endpoint and API version information, while possibly helpful, could be considered extraneous for an AI agent's primary decision-making.

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 absence of an output schema, the description adequately describes the return type (paginated JSON array) and mentions pagination metadata. Combined with safety annotations, it provides sufficient context for a list tool. It could be more complete by detailing the array contents, but it is reasonable.

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?

The input schema has 100% description coverage, but the description adds context: it explains that page and per_page control pagination and that the response includes pagination metadata. It also repeats that company_id is required. This provides meaning beyond the schema descriptions.

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 default correspondence types for the company, specifically those used for creating generic tools. It specifies the resource (default correspondence types) and the context (Custom - Configurable Tools). While it distinguishes from siblings by linking to generic tools, it does not explicitly differentiate from the sibling 'list_correspondence_type_defaults', which may have a similar 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 usage context: 'Use this to enumerate Custom - Configurable Tools when you need a paginated overview, to find IDs, or to filter by query parameters.' It mentions pagination parameters and required parameter. However, it does not specify when not to use this tool or mention alternative tools (e.g., for filtering by user/workspace), leaving some ambiguity.

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