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ask_agent

Ask another of the user's agents for something it's set up for (its tools, files, sign-ins or what it knows). It runs as a new task in that agent, on the Mac that runs it. from: your own "agent:task:key" from your instructions. With from, its answer comes back to this task as a new message by itself; without it (a client outside Caddie), it's a message to it marked as asked from outside Caddie via this client, and you get the answer with agent_reply (task_status follows the task, by the task_id it returns). wait_seconds (up to 50) waits here for a quick answer. Up to 4 asks an hour from one task. Don't ask it to do what you can do yourself.

Input Schema

NameRequiredDescriptionDefault
fromNoyour own "agent:task:key", so the answer comes back by itself
agentYesits name or id (list_agents)
messageYes
wait_secondsNo

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A4.1/5.0
Behavior5/5

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

With no annotations, the description carries the full burden and does so well: it discloses that the ask runs as a new task on the target's Mac, how the answer returns (as a new message with from; via agent_reply without from), that task_status follows by task_id, the wait_seconds wait behavior, and a 4-asks-per-hour rate limit.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness3/5

Is the description appropriately sized, front-loaded, and free of redundancy?

Purpose is front-loaded, but the middle is a dense run-on ('without it (a client outside Caddie), it's a message to it marked as asked from outside Caddie via this client') that is hard to parse. Every clause carries information, so it's not padded, but structure and readability suffer.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness4/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a 4-param tool with no output schema and no annotations, the description explains direction of the call, return path, and limits well enough to invoke correctly. It could be slightly clearer on what the returned answer message looks like, but the essential mechanics are covered.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters4/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 50%, and the description compensates by explaining the semantics of from (your own agent:task:key, triggers automatic reply) and wait_seconds (up to 50, waits here for a quick answer). agent is covered by the schema's list_agents hint; message is self-evident.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

States a specific verb+resource: asking another agent for something it's set up for, with scope ('its tools, files, sign-ins or what it knows'). This distinguishes it from agent_reply (which retrieves answers) and list_agents, though it doesn't name those siblings explicitly.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines4/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

Gives clear context: use it to get something only another agent can provide, and 'Don't ask it to do what you can do yourself.' It also explains the from vs no-from scenarios and the rate limit. However, it doesn't explicitly contrast with agent_reply as a retrieval alternative beyond mentioning it in passing.

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

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