Clear Thought MCP Server

decisionframework

Analyze complex decisions using structured frameworks to evaluate options, criteria, and outcomes systematically.

Instructions

A detailed tool for structured decision analysis and rational choice. This tool helps models systematically evaluate options, criteria, and outcomes. It supports multiple decision frameworks, probability estimates, and value judgments.

Input Schema

TableJSON Schema

Name	Required	Description
`decisionStatement`	Yes
`options`	Yes
`criteria`	No
`analysisType`	Yes
`stage`	Yes
`stakeholders`	No
`constraints`	No
`timeHorizon`	No
`riskTolerance`	No
`possibleOutcomes`	No
`recommendation`	No
`rationale`	No
`decisionId`	Yes	Unique identifier for this decision analysis
`iteration`	Yes	Current iteration of the decision process
`nextStageNeeded`	Yes	Whether another stage is needed in the process

Implementation Reference

src/tools/decisionFrameworkServer.ts:70-78 (handler)

The 'processDecisionFramework' method is the handler that processes the input for the 'decisionframework' tool.

public processDecisionFramework(input: unknown): DecisionFrameworkData {
  const validatedData = this.validateInputData(input);
  
  // Log formatted output to console
  const formattedOutput = this.formatOutput(validatedData);
  console.error(formattedOutput);
  
  return validatedData;
}

src/index.ts:1110-1113 (registration)
The tool 'decisionframework' is registered and dispatched in the main server logic within the switch-case block.
```
case "decisionframework": {
    const result = decisionFrameworkServer.processDecisionFramework(
        request.params.arguments
    );
```

src/models/interfaces.ts:149-160 (schema)

The 'DecisionFrameworkData' interface defines the input schema for the 'decisionframework' tool.

export interface DecisionFrameworkData {
    decisionStatement: string;
    options: OptionData[];
    criteria?: CriterionData[];
    analysisType:
        | "pros-cons"
        | "weighted-criteria"
        | "decision-tree"
        | "expected-value"
        | "scenario-analysis";
    stage:
        | "problem-definition"

Schema Changelog

Changes observed during successful MCP inspections.

First observedv1.1.2Mar 25, 2026

TDQS

C2.7/5.0

Behavior2/5

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

With no annotations provided, the description carries full burden for behavioral disclosure but offers minimal insight. It mentions 'systematically evaluate' and 'supports multiple decision frameworks' but doesn't describe what the tool actually does operationally—whether it performs calculations, generates reports, stores data, or requires specific permissions. For a complex tool with 15 parameters, this is inadequate.

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 efficiently structured in three sentences that each add value: establishing purpose, core functions, and capabilities. There's no redundant information, though it could be more front-loaded with concrete action verbs. The length is appropriate for the tool's complexity.

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

Completeness2/5

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

For a complex tool with 15 parameters, no annotations, and no output schema, the description is insufficient. It doesn't explain what the tool produces, how it handles the extensive input data, or what behavioral outcomes to expect. The gap between the description's generality and the schema's specificity creates ambiguity about the tool's actual operation.

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

Parameters2/5

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

Schema description coverage is only 20%, so the description must compensate but fails to do so. It vaguely references 'options, criteria, and outcomes' and 'probability estimates, and value judgments' which map to some parameters, but doesn't explain the purpose or relationships of the 15 parameters. Key parameters like 'analysisType', 'stage', and 'possibleOutcomes' remain semantically unclear from the description alone.

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

Purpose4/5

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

The description clearly states the tool's purpose as 'structured decision analysis and rational choice' with specific functions like evaluating options, criteria, and outcomes. It distinguishes from siblings by focusing on decision frameworks rather than reasoning methods, though it doesn't explicitly contrast with tools like 'structuredargumentation' or 'collaborativereasoning'.

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

Usage Guidelines2/5

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

The description provides no guidance on when to use this tool versus alternatives. It mentions supporting 'multiple decision frameworks' but doesn't specify scenarios where this tool is preferred over sibling tools like 'structuredargumentation' or 'mentalmodel', nor does it indicate prerequisites or exclusions for its use.

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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