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find_concept_contradictions

Detect contradictions in concept definitions across different versions of a manuscript to ensure consistency and accuracy in writing projects.

Instructions

Detect contradictions in concept definitions across versions

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
project_pathNoPath to manuscript directory (defaults to current directory)
concept_nameYesConcept to check for contradictions

Implementation Reference

  • Main handler function that executes the core tool logic: queries the concept tracker for contradictions in concept definitions across versions and formats the response with version details and contradiction explanations.
    findConceptContradictions(options: { conceptName: string }) {
      const contradictions = this.conceptTracker.findContradictions(options.conceptName);
    
      return {
        conceptName: options.conceptName,
        contradictions: contradictions.map((c) => ({
          version1: {
            versionNumber: c.version1.versionNumber,
            definition: c.version1.definition,
            timestamp: new Date(c.version1.timestamp).toISOString(),
          },
          version2: {
            versionNumber: c.version2.versionNumber,
            definition: c.version2.definition,
            timestamp: new Date(c.version2.timestamp).toISOString(),
          },
          contradiction: c.contradiction,
        })),
        total: contradictions.length,
      };
    }
  • Specific tool handler method that extracts the 'concept_name' from input args and delegates execution to WritersAid.findConceptContradictions.
    private async findConceptContradictions(args: Record<string, unknown>) {
      const conceptName = args.concept_name as string;
    
      return this.writersAid.findConceptContradictions({ conceptName });
    }
  • Tool registration in the central handleTool switch statement, routing calls to the specific handler method.
    case "find_concept_contradictions":
      return this.findConceptContradictions(args);
  • Tool schema definition specifying the name, description, and input schema (requiring 'concept_name', optional 'project_path').
    {
      name: "find_concept_contradictions",
      description: "Detect contradictions in concept definitions across versions",
      inputSchema: {
        type: "object",
        properties: {
          project_path: { type: "string", description: "Path to manuscript directory (defaults to current directory)" },
          concept_name: { type: "string", description: "Concept to check for contradictions" },
        },
        required: ["concept_name"],
      },
    },
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. While 'detect contradictions' implies a read-only analysis operation, the description doesn't specify what constitutes a contradiction, how results are presented, whether this requires specific file access permissions, or any performance characteristics. For a tool with zero annotation coverage, this is insufficient.

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 gets straight to the point with zero wasted words. It's appropriately sized for this tool's complexity and front-loads the core functionality.

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 of contradiction detection across versions, no annotations, and no output schema, the description is incomplete. It doesn't explain what the tool returns, how contradictions are identified, or what format results take. For a specialized analysis tool in a rich sibling environment, this leaves too many questions unanswered.

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 fully documents both parameters. The description doesn't add any parameter-specific information beyond what's in the schema. According to scoring rules, when schema_description_coverage is high (>80%), the baseline is 3 even with no param info in the description.

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 with a specific verb ('detect') and resource ('contradictions in concept definitions across versions'). It distinguishes from siblings like 'track_concept_evolution' by focusing on contradiction detection rather than evolution tracking. However, it doesn't explicitly differentiate from all possible 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 alternatives. It doesn't mention prerequisites, appropriate contexts, or exclusions. With many sibling tools available for manuscript analysis, this lack of comparative guidance is a significant gap.

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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