Skip to main content
Glama
HoziMurayama

MCP Rubber Duck

Official
by HoziMurayama

Duck Vote

duck_vote
Read-only

Resolve decisions by gathering reasoned votes from multiple AI models, then review the tally, confidence scores, and consensus level.

Instructions

Have multiple ducks vote on options with reasoning. Returns vote tally, confidence scores, and consensus level.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
votersNoList of provider names to vote (optional, uses all if not specified)
optionsYesThe options to vote on (2-10 options)
questionYesThe question to vote on (e.g., "Best approach for error handling?")
require_reasoningNoRequire ducks to explain their vote (default: true)

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
isTieYes
tallyYes
votesYes
winnerYes
optionsYes
questionYes
validVotesYes
totalVotersYes
consensusLevelYes
confidenceByOptionYes
Behavior3/5

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

Annotations already declare readOnlyHint=true and openWorldHint=true, so the agent knows it is a safe read operation. The description adds value by stating the output includes vote tally, confidence scores, and consensus level, but it does not disclose details like how votes are aggregated, whether the operation is stochastic, or what happens when no voters are specified (though that is in the schema). It is adequate but not rich.

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 sentence that front-loads the action and then lists the key returns. Every word earns its place with no waste or redundancy. It is 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 presence of an output schema (though not shown in the input schema chunk), the description need not explain return details beyond what it states. The description covers the essential purpose and primary outcomes for a voting tool. It is slightly brief but sufficient for the tool's complexity, so a 4 rather than a 5.

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%, so parameters are already well-documented. The description adds minimal new meaning, only referencing 'options' and 'reasoning' which are already in the schema. The baseline of 3 is appropriate since the schema does the heavy lifting.

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: 'Have multiple ducks vote on options with reasoning.' It specifies the action (vote), the subject (multiple ducks), and the object (options). It also distinguishes from siblings like ask_duck (single duck) and list_ducks (listing), and uniquely mentions returning vote tally, confidence scores, and consensus level.

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

Usage Guidelines3/5

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

The description implies usage for multi-duck voting, which differentiates it from single-duck tools, but it does not explicitly state when to use this tool versus alternatives or mention any exclusions. For example, it doesn't say 'For a single duck's opinion, use ask_duck instead.' The context is inferred rather than explicitly guided.

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

Install Server

Other Tools

Latest Blog Posts

MCP directory API

We provide all the information about MCP servers via our MCP API.

curl -X GET 'https://glama.ai/api/mcp/v1/servers/HoziMurayama/Multi-LLM-Debugging-Bridge'

If you have feedback or need assistance with the MCP directory API, please join our Discord server