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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
            );
Behavior2/5

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

With no annotations provided, the description bears full responsibility for behavioral disclosure. While it mentions 'facilitates creation,' it does not clarify whether this tool maintains state across calls, what it returns (no output schema exists), side effects, or how the dialectical chain progresses. The phrase 'detailed tool' is vague and non-descriptive of actual behavior.

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 consists of three sentences with minimal structural waste. However, it opens with filler ('A detailed tool for') and uses three sentences to convey what could be stated more directly ('Performs dialectical argument analysis via thesis/antithesis/synthesis structures'). The progression from general to specific is logical but not maximally efficient.

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 13 parameters, complex dialectical relationships (supports/contradicts/respondsTo), and no output schema or annotations, the description is insufficient. It omits critical workflow guidance (how to chain arguments using IDs), does not explain the Hegelian dialectic model implied by the enum values, and leaves users uncertain about the tool's statefulness or return values.

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 coverage is 69%, with 'claim,' 'premises,' and 'conclusion' lacking descriptions. The description mentions 'formal argumentation structures,' which loosely implies the claim-premise-conclusion model, but does not explicitly explain these core fields or the dialectical relationships (respondsTo, supports, contradicts). It earns baseline credit for hinting at the dialectical structure matching the argumentType enum.

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 identifies the resource (arguments) and actions (creation, critique, synthesis) using terms like 'dialectical reasoning' and 'formal argumentation structures.' However, given siblings like 'collaborativereasoning,' 'sequentialthinking,' and 'scientificmethod,' it fails to specify what makes this tool distinct or when to prefer its dialectical approach over linear or other reasoning methods.

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, nor does it mention prerequisites, expected workflows (e.g., chaining thesis→antithesis→synthesis), or exclusion criteria. Users must infer applicability from the parameter schema alone.

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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