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chirag127
by chirag127

structuredargumentation

Analyze complex questions through formal argumentation structures. Create, critique, and synthesize competing arguments for systematic dialectical reasoning.

Instructions

A detailed tool for systematic dialectical reasoning and argument analysis. This tool helps analyze complex questions through formal argumentation structures. It facilitates the creation, critique, and synthesis of competing arguments.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
claimYes
premisesYes
conclusionYes
argumentIdNoOptional unique identifier for this argument
argumentTypeYes
confidenceYesConfidence level in this argument (0.0-1.0)
respondsToNoID of the argument this directly responds to
supportsNoIDs of arguments this supports
contradictsNoIDs of arguments this contradicts
strengthsNoNotable strong points of the argument
weaknessesNoNotable weak points of the argument
nextArgumentNeededYesWhether another argument is needed in the dialectic
suggestedNextTypesNoSuggested types for the next argument

Implementation Reference

  • The processStructuredArgumentation method is the core handler for the 'structuredargumentation' tool. It processes the input and returns the formatted response.
    public processStructuredArgumentation(input: unknown): { content: Array<{ type: string; text: string }>; isError?: boolean } {
      try {
        const validatedData = this.validateInputData(input);
        const processedData: ArgumentData = {
          ...validatedData,
          supports: validatedData.supports || [],
          contradicts: validatedData.contradicts || [],
          strengths: validatedData.strengths || [],
          weaknesses: validatedData.weaknesses || [],
          suggestedNextTypes: validatedData.suggestedNextTypes || []
        };
        
        const formattedOutput = this.formatOutput(processedData);
        console.error(formattedOutput);
    
        return {
          content: [{
            type: "text",
            text: JSON.stringify({
              argumentType: processedData.argumentType,
              claim: processedData.claim,
              confidence: processedData.confidence,
              nextArgumentNeeded: processedData.nextArgumentNeeded,
              argumentId: processedData.argumentId || `arg-${Date.now()}`,
              status: 'success'
            }, null, 2)
          }]
        };
      } catch (error) {
        return {
          content: [{
            type: "text",
            text: JSON.stringify({
              error: error instanceof Error ? error.message : String(error),
              status: 'failed'
            }, null, 2)
          }],
          isError: true
        };
      }
    }
  • src/index.ts:1150-1154 (registration)
    The 'structuredargumentation' tool is registered within the main switch statement of the MCP server's call tool handler in index.ts.
    case "structuredargumentation": {
        const result =
            structuredArgumentationServer.processStructuredArgumentation(
                request.params.arguments
            );

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv1.1.2

TDQS

C2.9/5.0
Behavior2/5

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 describes the tool's function but lacks critical details: it doesn't specify if this is a read-only or mutating operation, what the output looks like (e.g., structured analysis or plain text), or any constraints like rate limits or authentication needs. For a tool with 13 parameters and no output schema, this is a significant gap in transparency.

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, front-loaded with the core purpose. Each sentence adds value: the first defines the tool, the second specifies its application, and the third outlines key actions. There's no wasted text, though it could be slightly more detailed without losing 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?

Given the tool's complexity (13 parameters, no output schema, no annotations), the description is inadequate. It doesn't explain the output format, behavioral traits, or how parameters interact in practice. For a tool designed for 'systematic dialectical reasoning,' more context on expected inputs and results is needed to guide the agent effectively.

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 69%, meaning most parameters have some documentation in the schema itself. The description adds little beyond this, as it doesn't explain parameter meanings, relationships (e.g., how 'claim' and 'conclusion' differ), or usage examples. Given the high coverage, the baseline is 3, but the description fails to compensate for the 31% gap or provide deeper insights.

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 'systematic dialectical reasoning and argument analysis' with specific verbs like 'analyze,' 'create,' 'critique,' and 'synthesize.' It distinguishes the tool by focusing on formal argumentation structures, which differentiates it from sibling tools like 'collaborativereasoning' or 'scientificmethod.' However, it doesn't explicitly contrast with all siblings, keeping it from a perfect score.

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 analyzing 'complex questions' but gives no context for choosing this over sibling tools like 'decisionframework' or 'mentalmodel.' There are no exclusions, prerequisites, or named alternatives, leaving the agent with minimal usage direction.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.