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HoziMurayama

MCP Rubber Duck

Official
by HoziMurayama

Duck Council

duck_council
Read-only

Gather responses from a panel of AI models to compare perspectives, support debugging, and explore different solutions to your question.

Instructions

Get responses from all configured ducks (like a panel discussion)

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
modelNoSpecific model to use for all ducks (optional)
imagesNoOptional images to include with the prompt (for vision-capable models)
promptYesThe question for the duck council
Behavior4/5

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

Annotations already declare readOnlyHint=true and openWorldHint=true, so the description doesn't need to restate safety. It adds useful behavioral context: the panel discussion metaphor implies multiple responses from each duck, possibly in a coordinated manner. It does not contradict annotations. This goes beyond the structured fields.

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?

The description is a single, efficiently worded sentence. It uses an analogy to convey meaning without unnecessary detail. Every word earns its place, making it highly concise and well-structured.

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?

Given the tool's simplicity (3 well-described params, read-only, no output schema), the description covers the core purpose and usage context adequately. It doesn't detail the exact response format, but that is mitigated by the clear schema and the read-only annotation. The panel discussion analogy provides enough context for an agent to decide when to use it.

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

Parameters3/5

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

Schema description coverage is 100%, with each parameter (prompt, model, images) already documented in detail. The description adds no extra parameter semantics beyond what the schema provides, so baseline score of 3 is appropriate.

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?

The description clearly states the tool's purpose: 'Get responses from all configured ducks.' The analogy 'like a panel discussion' further clarifies the intent, and the phrase 'all configured ducks' distinguishes it from sibling tools like ask_duck, which likely targets a single duck. This provides specific verb+resource+scope.

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?

The description gives clear context for when to use the tool—when you want a panel-style collection of responses from all ducks. It implicitly contrasts with ask_duck (single duck) and other debate/vote tools, but does not explicitly list when not to use or name alternatives. This matches 'clear context, no exclusions'.

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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