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MushroomFleet

DeepLucid3D UCPF Server

analyze_problem

Analyze and process problem statements using the UCPF framework to enable structured cognitive analysis, knowledge mapping, and perspective generation for advanced problem-solving.

Instructions

Process a problem statement through the full UCPF framework

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
detailedNoWhether to include detailed analysis
enable_stateNoWhether to enable state management for this analysis
problemYesThe problem statement to analyze
session_idNoOptional session ID for maintaining state between calls

Implementation Reference

  • The core handler function that processes the input problem using the UCPF framework, generates creative perspectives, and formats the analysis output.
    export async function analyzeProblem(
      problem: string,
      ucpfCore: UcpfCore,
      creativePatterns: CreativePatterns,
      stateManager: StateManager,
      sessionId?: string,
      detailed: boolean = false
    ): Promise<string> {
      // Process the problem through UCPF
      const analysis = await ucpfCore.processInput(problem, sessionId);
      
      // Generate creative perspectives
      const creativeInsights = creativePatterns.generatePerspectives(problem, 3);
      
      // Format the results
      return formatAnalysis(analysis, creativeInsights);
    }
  • The input schema defining the parameters for the analyze_problem tool, including problem (required), session_id, enable_state, and detailed.
    inputSchema: {
      type: "object",
      properties: {
        problem: {
          type: "string",
          description: "The problem statement to analyze"
        },
        session_id: {
          type: "string",
          description: "Optional session ID for maintaining state between calls"
        },
        enable_state: {
          type: "boolean",
          description: "Whether to enable state management for this analysis",
          default: false
        },
        detailed: {
          type: "boolean",
          description: "Whether to include detailed analysis",
          default: false
        }
      },
      required: ["problem"]
    }
  • src/index.ts:429-476 (registration)
    The dispatch handler in the MCP tool call request that validates parameters, calls the analyzeProblem function, handles state, and returns the formatted response.
    case "analyze_problem": {
      // Validate required parameters
      if (!args?.problem || typeof args.problem !== "string") {
        throw new McpError(
          ErrorCode.InvalidParams,
          "Required parameter 'problem' must be a string"
        );
      }
      
      // Optional parameters
      const sessionId = args.session_id as string | undefined;
      const enableState = Boolean(args.enable_state);
      const detailed = Boolean(args.detailed);
      
      // Update state management if needed
      if (enableState !== stateManager.getState("global")?.enabled) {
        stateManager.setEnabled(enableState);
        ucpfCore.setStateEnabled(enableState);
      }
      
      // Process the problem
      const analysis = await analyzeProblem(
        args.problem,
        ucpfCore,
        creativePatterns,
        stateManager,
        sessionId,
        detailed
      );
      
      // Store the analysis if state is enabled
      if (enableState && sessionId) {
        stateManager.setState(sessionId, {
          analysis,
          timestamp: Date.now(),
          problem: args.problem
        });
      }
      
      return {
        content: [
          {
            type: "text",
            text: analysis
          }
        ]
      };
    }
  • Helper function that formats the UCPF analysis and creative insights into a structured Markdown presentation.
    export function formatAnalysis(
      analysis: UcpfAnalysis,
      creativeInsights: CreativePerspective[] = []
    ): string {
      const formatSection = (title: string, content: string): string => {
        return `## ${title}\n\n${content}\n\n`;
      };
    
      let result = "";
    
      // Format Cognitive State
      result += formatSection("Cognitive State Assessment", 
        `Current cognitive state: **${analysis.cognitiveState.type}**\n\n` +
        `${analysis.cognitiveState.description}\n\n` +
        "**Characteristics:**\n" +
        analysis.cognitiveState.characteristics
          .map(char => `- ${char}`)
          .join("\n")
      );
    
      // Format Knowledge Mapping
      result += formatSection("Knowledge Dimension Mapping",
        "The problem space has been mapped across the following knowledge dimensions:\n\n" +
        analysis.knowledgeMapping
          .map(category => (
            `### ${category.label}\n` +
            `**Description:** ${category.description}\n` +
            (category.examples.length > 0 ? 
              "**Examples:**\n" + category.examples.map(ex => `- ${ex}`).join("\n") : 
              "*No specific examples identified.*")
          ))
          .join("\n\n")
      );
    
      // Format Recursive Questions
      result += formatSection("Recursive Self-Questioning",
        "The following questions challenge initial assumptions and perspectives:\n\n" +
        analysis.recursiveQuestions
          .map(q => (
            `### ${q.question}\n` +
            `**Purpose:** ${q.purpose}\n` +
            `**Target Area:** ${q.targetArea}`
          ))
          .join("\n\n")
      );
    
      // Format Creative Perspectives
      if (creativeInsights.length > 0) {
        result += formatSection("Creative Perspectives",
          "These alternative viewpoints open new possibilities:\n\n" +
          creativeInsights
            .map(p => (
              `### ${p.viewpoint}\n` +
              `**Rationale:** ${p.rationale}\n` +
              (p.implications.length > 0 ? 
                "**Implications:**\n" + p.implications.map(i => `- ${i}`).join("\n") : 
                "") +
              (p.potentialOutcomes.length > 0 ? 
                "\n\n**Potential Outcomes:**\n" + p.potentialOutcomes.map(o => `- ${o}`).join("\n") : 
                "")
            ))
            .join("\n\n")
        );
      }
    
      // Format Synthesis
      result += formatSection("Synthesis & Integration",
        "**Key Insights:**\n" +
        (analysis.synthesis.insights.length > 0 ?
          analysis.synthesis.insights.map(i => `- ${i}`).join("\n") :
          "- *Analysis indicates further exploration needed to generate specific insights.*") +
        "\n\n**Confidence Level:** " + (analysis.synthesis.confidenceLevel * 100).toFixed(0) + "%" +
        "\n\n**Uncertainties:**\n" +
        (analysis.synthesis.uncertainties.length > 0 ?
          analysis.synthesis.uncertainties.map(u => `- ${u}`).join("\n") :
          "- *No specific uncertainties identified.*")
      );
    
      return result;
    }
Behavior2/5

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

No annotations are provided, so the description carries the full burden of behavioral disclosure. It mentions 'process' and 'full UCPF framework', implying analysis or transformation, but doesn't describe what the tool actually does behaviorally—such as whether it performs computations, returns structured data, has side effects, or requires specific permissions. This leaves significant gaps in understanding the tool's operation and impact.

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, efficient sentence that front-loads the core purpose without unnecessary words. It directly states the action and resource, making it easy to parse and understand quickly, with no wasted information.

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?

Given the complexity implied by 'full UCPF framework' and the lack of annotations and output schema, the description is incomplete. It doesn't explain what the tool returns, how it handles state or detailed analysis, or its behavioral traits, leaving the agent with insufficient context to use the tool effectively beyond basic parameter input.

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 the schema fully documents all four parameters. The description adds no additional meaning beyond what the schema provides, such as explaining how parameters interact with the UCPF framework or typical use cases. With high schema coverage, the baseline score of 3 is appropriate as the description doesn't compensate but also doesn't detract.

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

Purpose3/5

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

The description states the tool 'processes a problem statement through the full UCPF framework', which provides a clear verb ('process') and resource ('problem statement') with a specific methodology ('UCPF framework'). However, it doesn't differentiate from sibling tools like 'creative_exploration' or 'manage_state', leaving the specific scope of 'full UCPF framework' somewhat vague compared to alternatives.

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 the sibling tools 'creative_exploration' or 'manage_state'. It lacks explicit context, prerequisites, or exclusions, leaving the agent to infer usage based on the tool name and description alone without clear alternatives or constraints.

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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