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Send a self-contained question to one council member and retrieve its answer. Include files or images as materials, and set a system instruction to shape the response.

Instructions

Ask ONE member of the council a question and return its answer.

model is the member's short id; the schema lists the ones this council has, and list_council describes them.

The member is stateless and cannot see this conversation, so prompt must carry everything it needs — including any other model's answer you want it to critique. Optionally set system to steer its role or output format.

materials hands the council the thing the question is about — a spec, a log, a diff, a screenshot — instead of you pasting it into prompt. Give {path, label} for a file, or {text, label} for something with no file behind it. Prefer a path: the members are then handed the file's exact bytes rather than your reproduction of them, you do not spend a copy of the whole document writing this call, and every member and every round get an identical copy, which is both what makes their answers comparable and what an endpoint's cache can match. Images go this way too, and are the case that matters most: describe a screenshot in prose and every member inherits the same description, so anything you misread is misread by the whole council at once.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
modelYes
promptYes
systemNo
materialsNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes
Install Server

TDQS

A4.8/5.0
Behavior5/5

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

With no annotations, the description carries the full behavioral burden. It discloses statelessness, lack of conversation context, how materials are delivered to every member/round, image handling, and caching implications — all beyond the minimal description.

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

Conciseness5/5

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

Every sentence earns its place: the core action is front-loaded, then parameters are explained in natural order. The materials rationale is detailed but directly serves correct usage, not padding.

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

Completeness5/5

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

An output schema exists, so return-value details need not be repeated. The description covers the tool's action, model selection, prompt construction, and material handling — sufficient for an agent to invoke it correctly without additional documentation.

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

Parameters5/5

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

Schema description coverage is 0%, and the description fully compensates. It explains model as a short ID, prompt as needing to carry full context, system as optional steering, and materials' path/text/label semantics including when to prefer paths. This adds essential meaning the schema omits.

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

Purpose5/5

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

Opens with a specific verb and resource: 'Ask ONE member of the council a question and return its answer.' The 'ONE member' phrasing immediately distinguishes it from the sibling ask_all, and the purpose is unambiguous.

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 contextual guidance: the member is stateless so prompt must be self-contained, and materials should be passed by path when possible. It does not explicitly name alternatives like ask_all or revise, but the 'ONE member' framing makes the boundary clear.

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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