list_connections

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

No annotations are provided, so the description carries full responsibility for behavioral disclosure. It explicitly states that passwords are never returned for security reasons, describes the returned fields, and implies a read-only operation. This is thorough and honest.

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 well-structured with bullet points and sections, front-loading the purpose and usage. It is slightly verbose but every sentence adds value. Slight improvement could be made by shortening the example queries list.

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?

For a simple tool with no parameters and an output schema (though not provided in schema field, the description compensates), the description covers purpose, usage, return fields, and a security note. It is complete enough for an AI agent to use correctly.

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 tool has zero parameters, so schema coverage is 100% and the description adds no parameter-specific detail. However, the description adds meaning by detailing the return fields and behavior (passwords excluded). Following the guidelines, baseline is 4.

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's purpose as retrieving connection configurations for external systems. It lists specific user queries that map to this tool, and the verb 'Get' with resource 'connection configurations' is precise. Sibling tools focus on DAGs, tasks, pools, etc., so this tool is well-distinguished.

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 guidance by listing example user queries like 'What connections are configured?' and 'List all connections'. It does not explicitly state when not to use the tool, but the context is clear enough for an AI agent to select it appropriately.

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