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AzDeltaQQ

MCP Advanced Reasoning Server

by AzDeltaQQ

reason_beam

Solve complex problems using Beam Search to explore multiple reasoning paths and identify optimal solutions for challenging tasks.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
queryYesThe problem or task to reason about using Beam Search

Implementation Reference

  • The handler function for the 'reason_beam' tool. It simulates Beam Search reasoning over 3 iterative steps, building thoughts progressively, and returns a JSON-structured response containing all thoughts, strategy details, and completion status.
    async ({ query }) => {
      try {
        // Initialize first thought
        const totalThoughts = 3;
        let currentThought = `Beam Search Reasoning (Step 1/${totalThoughts}): Initial analysis of the problem "${query}":\n\n` +
                             `Let me explore multiple approaches to this problem. ${query}\n\n` +
                             `[This would be the initial Beam Search-based reasoning]`;
        let thoughtNumber = 1;
        let complete = false;
        let allThoughts = [currentThought];
        
        // Automatically iterate through all thoughts
        while (!complete && thoughtNumber < totalThoughts) {
          // Simulate next thought generation
          thoughtNumber++;
          const nextThought = `Beam Search Reasoning (Step ${thoughtNumber}/${totalThoughts}): ` +
                             `Considering 3 alternative paths from "${currentThought.slice(0, 50)}...", ` +
                             `the most promising direction is...\n\n` +
                             `[This would be the next step of Beam Search reasoning for: ${query}]`;
          
          allThoughts.push(nextThought);
          currentThought = nextThought;
          
          // Check if we've reached the final thought
          if (thoughtNumber >= totalThoughts) {
            complete = true;
          }
        }
        
        // Final result with all thoughts
        return {
          content: [
            {
              type: "text",
              text: JSON.stringify({
                strategy: "beam_search",
                originalPrompt: query,
                allThoughts: allThoughts,
                thoughtNumber: thoughtNumber,
                totalThoughts: totalThoughts,
                complete: true
              }, null, 2)
            }
          ]
        };
      } catch (error) {
        throw new ReasoningError(`Beam Search reasoning command failed: ${error instanceof Error ? error.message : String(error)}`);
      }
    }
  • The input schema for the 'reason_beam' tool, defining a single 'query' string parameter using Zod validation.
    {
      query: z.string().describe("The problem or task to reason about using Beam Search")
    },
  • The registration of the 'reason_beam' tool using server.tool(), including the tool name, input schema, and handler function within the registerCommandWrappers function.
    server.tool(
      "reason_beam",
      {
        query: z.string().describe("The problem or task to reason about using Beam Search")
      },
      async ({ query }) => {
        try {
          // Initialize first thought
          const totalThoughts = 3;
          let currentThought = `Beam Search Reasoning (Step 1/${totalThoughts}): Initial analysis of the problem "${query}":\n\n` +
                               `Let me explore multiple approaches to this problem. ${query}\n\n` +
                               `[This would be the initial Beam Search-based reasoning]`;
          let thoughtNumber = 1;
          let complete = false;
          let allThoughts = [currentThought];
          
          // Automatically iterate through all thoughts
          while (!complete && thoughtNumber < totalThoughts) {
            // Simulate next thought generation
            thoughtNumber++;
            const nextThought = `Beam Search Reasoning (Step ${thoughtNumber}/${totalThoughts}): ` +
                               `Considering 3 alternative paths from "${currentThought.slice(0, 50)}...", ` +
                               `the most promising direction is...\n\n` +
                               `[This would be the next step of Beam Search reasoning for: ${query}]`;
            
            allThoughts.push(nextThought);
            currentThought = nextThought;
            
            // Check if we've reached the final thought
            if (thoughtNumber >= totalThoughts) {
              complete = true;
            }
          }
          
          // Final result with all thoughts
          return {
            content: [
              {
                type: "text",
                text: JSON.stringify({
                  strategy: "beam_search",
                  originalPrompt: query,
                  allThoughts: allThoughts,
                  thoughtNumber: thoughtNumber,
                  totalThoughts: totalThoughts,
                  complete: true
                }, null, 2)
              }
            ]
          };
        } catch (error) {
          throw new ReasoningError(`Beam Search reasoning command failed: ${error instanceof Error ? error.message : String(error)}`);
        }
      }
    );
Behavior1/5

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

Tool has no description.

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

Conciseness1/5

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

Tool has no description.

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

Completeness1/5

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

Tool has no description.

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

Parameters1/5

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

Tool has no description.

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

Purpose1/5

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

Tool has no description.

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

Usage Guidelines1/5

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

Tool has no description.

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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