Ask a panel of agents

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

Adds substantial context beyond the annotations: advisors run in parallel, headless and read-only, and critically that one advisor failing does not fail the others. It also discloses that each answer carries its own session_id for follow-ups through ask_agent, which is non-obvious continuation behavior the annotations cannot express.

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?

Three tight sentences: purpose first, then use cases, then behavioral contract. The cross-reference to ask_agent is doing real work rather than padding, and nothing is redundant.

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 does carry the return semantics (answers side by side, each with a session_id) and the partial-failure contract. It could say more about how failed advisors are represented in the response, but the essentials for correct invocation are present.

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?

Schema description coverage is 100%, so the schema already documents cwd, agents, effort and question. The description adds no parameter-level detail such as the minimum of two agents or the fixed CLI enum, so baseline 3 applies.

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?

States a specific verb and resource ('ask several AI coding agents the same question at once and get their answers side by side') and implicitly contrasts with the single-agent sibling ask_agent. An agent can distinguish this from ask_agent and list_agents without reading either schema.

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?

Gives clear use cases ('independent opinions on a decision', 'see whether advisors agree'), which is real guidance rather than restating the name. It stops short of explicit when-not-to-use guidance pointing at ask_agent for single opinions, leaving that inference to the caller.

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