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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
NameRequiredDescriptionDefault
decisionStatementYes
optionsYes
criteriaNo
analysisTypeYes
stageYes
stakeholdersNo
constraintsNo
timeHorizonNo
riskToleranceNo
possibleOutcomesNo
recommendationNo
rationaleNo
decisionIdYesUnique identifier for this decision analysis
iterationYesCurrent iteration of the decision process
nextStageNeededYesWhether another stage is needed in the process

Implementation Reference

  • 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
        );
  • 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"
Behavior3/5

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

With no annotations provided, the description carries the full burden of behavioral disclosure. It hints at capabilities ('supports multiple decision frameworks') but does not clarify whether the tool performs calculations, persists state across iterations, generates reports, or simply validates input structure. It omits critical behavioral details like whether it returns analysis results or requires multiple invocations to progress through stages.

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

Conciseness3/5

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

The description is three sentences long, which is appropriately brief, but wastes words on filler ('A detailed tool', 'This tool helps'). The content is front-loaded with adjectives rather than actionable guidance. It efficiently lists key concepts but lacks structural cues (bolding, lists) to navigate the 15-parameter complexity despite the conciseness.

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 15-parameter tool with nested objects, enums representing workflow stages, no output schema, and no annotations, the description is insufficient. It does not explain the iterative decision process implied by 'iteration' and 'nextStageNeeded', nor how the different analysisTypes (decision-tree vs expected-value) affect required inputs. Critical gaps remain regarding return values and side effects.

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 coverage is critically low at 20% (only 3 of 15 parameters have descriptions). While the description mentions 'options, criteria, and outcomes' providing some semantic context for those specific arrays, it fails to explain the crucial workflow parameters ('stage', 'analysisType' with their specific enum values), 'riskTolerance' levels, or the purpose of 'recommendation' and 'rationale' fields. Given the complexity, the description inadequately compensates for the schema gaps.

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 identifies the tool's purpose as 'structured decision analysis and rational choice' with specific capabilities ('evaluate options, criteria, and outcomes', 'probability estimates', 'value judgments'). However, given the crowded sibling space with many reasoning tools (structuredargumentation, collaborativereasoning, scientificmethod, etc.), it lacks explicit differentiation criteria for when this specific framework should be selected.

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 its many sibling reasoning tools. There is no mention of prerequisites (e.g., needing defined options first), workflow sequencing (relating to the 'stage' parameter), or alternatives to avoid. Users must infer applicability from the generic 'decision analysis' label.

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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