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

With no annotations, the description carries the full behavioral burden. It helpfully discloses the partial-result shape { agents, partial: true, note } when there are too many agents, but it does not explicitly state read-only semantics, permission needs, or pagination behavior beyond the partial note.

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 definition is compact and front-loads the purpose before describing the partial-return behavior. The second sentence is somewhat fragmentary ('A list; when...'), but every piece of information earns its place.

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 zero-parameter, no-output-schema listing tool, the description gives enough context to call it and interpret the main response. It could be more complete by clarifying read-only behavior and the exact shape of the partial response, but the core is covered.

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 parameter semantics are not a meaningful burden. The description does not need to explain any input parameters, and the baseline for a zero-parameter tool 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 identifies the resource as the user's other Caddie agents and lists the key fields returned: purpose, current work, and Mac availability. It also states the intended use for choosing an agent for ask_agent, though it does not explicitly contrast with other agent-related siblings like agent_tasks or organize_agents.

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?

It provides clear usage context: this tool helps pick an agent for ask_agent. It lacks explicit when-not conditions or comparisons to adjacent tools, but the intended selection scenario is stated directly.

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