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chapmanjw

Rutherford MCP Server

by chapmanjw

analyze

Generate a historical agreement report that scans kept consensus panels to calculate how often two distinct model lineages reach the same verdict when they co-vote.

Instructions

Analyze the kept run corpus (read-only). report="historical_agreement" is the default and only report.

historical_agreement scans the consensus panels you kept (persist=true / default_persistence=job) and reports how often two DISTINCT model lineages reached the same verdict when they co-voted -- an OBSERVATIONAL signal for your roster choice (e.g. a lineage that never adds a dissent), NOT a vote discount: agreement is not correctness, so down-weighting agreeing lineages would punish them for being right together. An empty corpus returns an empty report whose notes explain how to build one.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
reportNohistorical_agreement

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 behavior: it is read-only, scans kept panels, reports co-voting agreement between distinct lineages, and warns about not down-weighting agreeing lineages. It also describes the empty corpus case.

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 front-loaded with the key purpose and read-only nature. The subsequent paragraph adds essential detail without excessive fluff, though it could be slightly more concise.

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?

Given an output schema exists (context signal), the description need not explain return values. It covers input, behavior, interpretation, and edge case (empty corpus). Complete for a single-parameter tool.

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?

The single parameter 'report' is fully explained: it defaults to 'historical_agreement' and is the only valid value. The description details what the report does, compensating for 0% schema coverage.

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 analyzes the kept run corpus in read-only mode, and specifies the only report type 'historical_agreement' with detailed behavior. It distinguishes itself by being read-only and focused on historical agreement, though it does not explicitly contrast with siblings.

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 when to use it (for analyzing consensus panels) and provides a guideline against misinterpreting agreement as correctness ('NOT a vote discount'). It does not explicitly list alternatives but implies the tool is for this specific analysis.

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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