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chapmanjw

Rutherford MCP Server

by chapmanjw

consensus

Run a single prompt across multiple AI coding CLIs and return each response, enabling side-by-side comparison and synthesis.

Instructions

Ask the same prompt of several targets in parallel and return every voice.

targets is a list of {cli, model} objects (or cli / cli:model strings). Omit it, pass an empty list, or pass "all" to fan out to every installed + authenticated CLI at its default model (capped at max_targets); the result's skipped list explains any adapter left out. Optional stances (parallel to targets) steer each voice: for | against | neutral, and cannot be combined with the auto-expanded panel. synthesize=true adds a server-side combined answer (off by default, so the orchestrator can synthesize the voices itself). With mode="async" a job id is returned.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
promptYes
targetsNo
stancesNo
working_dirNo
filesNo
roleNo
safety_modeNoread_only
synthesizeNo
timeout_sNo
modeNosync
include_rawNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes
Behavior5/5

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

With no annotations, the description fully discloses behavioral traits: fan-out behavior with targets, skipped list, async job return, sync vs async mode, and synthesize option. It provides comprehensive context beyond basic read/write semantics.

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

Conciseness4/5

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

The description is structured with a lead sentence followed by parameter explanations in a paragraph, which is easy to scan. It is somewhat long but each sentence adds value given the complexity of the tool. Could be slightly more concise.

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

Completeness3/5

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

The description covers many parameters (prompt, targets, stances, synthesize, mode) but omits several: working_dir, files, role, safety_mode, timeout_s, include_raw. With 11 parameters and 0% schema coverage, this is a significant gap. Output schema exists but is not referenced.

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 coverage is 0%, so the description must compensate. It explains targets (including cli/model objects and strings), stances (for/against/neutral), synthesize (off by default), mode (async/sync), and provides examples (capped at max_targets). This adds significant meaning beyond the bare schema.

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 starts with a clear verb+resource statement: 'Ask the same prompt of several targets in parallel and return every voice.' This differentiates it from sibling tools like delegate (single target) or plan (sequential steps).

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 explains how to use targets, stances, mode, and synthesize, including specific instructions for auto-expansion and async mode. However, it does not explicitly state when not to use this tool or compare to alternatives like delegate for single-target tasks.

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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