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Open Search MCP

by flyanima

deep_research

Perform comprehensive deep research analysis on any topic with adjustable depth levels to gather detailed insights and information.

Instructions

Perform comprehensive deep research analysis on any topic

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
topicYesResearch topic or subject to analyze
depthNoResearch depth levelcomprehensive

Implementation Reference

  • Registration of the deep_research tool including schema, description, and handler function.
    registry.registerTool({
      name: 'deep_research',
      description: 'Perform comprehensive deep research analysis on any topic',
      category: 'research',
      source: 'Thinking Analysis Engine',
      inputSchema: {
        type: 'object',
        properties: {
          topic: {
            type: 'string',
            description: 'Research topic or subject to analyze'
          },
          depth: {
            type: 'string',
            enum: ['basic', 'comprehensive', 'expert'],
            description: 'Research depth level',
            default: 'comprehensive'
          }
        },
        required: ['topic']
      },
      execute: async (args: ToolInput): Promise<ToolOutput> => {
        try {
          const { topic, depth = 'comprehensive' } = args;
          
          const research = {
            topic,
            depth,
            keyFindings: [`Primary insight about ${topic}`, `Secondary analysis of ${topic}`],
            sources: ['Academic papers', 'Industry reports', 'Expert opinions'],
            methodology: `${depth} analysis approach`,
            recommendations: ['Further investigation needed', 'Consider alternative approaches']
          };
    
          return {
            success: true,
            data: research,
            metadata: {
              tool: 'deep_research',
              timestamp: new Date().toISOString()
            }
          };
        } catch (error) {
          return {
            success: false,
            error: `Deep research failed: ${error instanceof Error ? error.message : String(error)}`,
            data: null
          };
        }
      }
    });
  • The execute handler function that performs the deep_research tool logic, generating mock research results based on topic and depth.
    execute: async (args: ToolInput): Promise<ToolOutput> => {
      try {
        const { topic, depth = 'comprehensive' } = args;
        
        const research = {
          topic,
          depth,
          keyFindings: [`Primary insight about ${topic}`, `Secondary analysis of ${topic}`],
          sources: ['Academic papers', 'Industry reports', 'Expert opinions'],
          methodology: `${depth} analysis approach`,
          recommendations: ['Further investigation needed', 'Consider alternative approaches']
        };
    
        return {
          success: true,
          data: research,
          metadata: {
            tool: 'deep_research',
            timestamp: new Date().toISOString()
          }
        };
      } catch (error) {
        return {
          success: false,
          error: `Deep research failed: ${error instanceof Error ? error.message : String(error)}`,
          data: null
        };
      }
    }
  • Input schema for deep_research tool defining topic (required) and optional depth parameter.
    inputSchema: {
      type: 'object',
      properties: {
        topic: {
          type: 'string',
          description: 'Research topic or subject to analyze'
        },
        depth: {
          type: 'string',
          enum: ['basic', 'comprehensive', 'expert'],
          description: 'Research depth level',
          default: 'comprehensive'
        }
      },
      required: ['topic']
    },
  • src/index.ts:254-255 (registration)
    Invocation of registerThinkingAnalysisTools which registers the deep_research tool (among others) to the main tool registry.
    registerSmartSearchTools(this.toolRegistry);        // 2 tools: intelligent_research, market_intelligence_aggregator
    registerThinkingAnalysisTools(this.toolRegistry);   // 4 tools: deep_research, visualize_thinking, decompose_thinking, check_research_saturation
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 'comprehensive deep research analysis' but fails to explain what this entails—such as data sources, processing time, output format, or limitations. This leaves critical behavioral traits unspecified for a tool with potential complexity.

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 a single, efficient sentence with no wasted words, making it appropriately concise. However, it lacks front-loading of critical details like scope or constraints, which could improve structure for agent comprehension.

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 tool's potential complexity (implied by 'deep research'), no annotations, and no output schema, the description is incomplete. It doesn't cover behavioral aspects, output expectations, or how it differs from siblings, leaving significant gaps for agent understanding.

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 already documents both parameters ('topic' and 'depth' with enum values). The description adds no meaning beyond this, as it doesn't elaborate on parameter usage or effects. The baseline score of 3 reflects adequate but minimal value from the description in this context.

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's purpose as 'perform comprehensive deep research analysis on any topic,' which is clear but vague. It specifies the verb 'perform' and resource 'deep research analysis,' but lacks specificity about what constitutes 'deep research' compared to sibling tools like 'intelligent_research' or 'search_arxiv,' making it only moderately helpful for differentiation.

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. With many sibling tools for research and analysis (e.g., 'search_arxiv,' 'intelligent_research'), there is no indication of context, prerequisites, or exclusions, leaving the agent without usage direction.

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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