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trace_file

Analyze TypeScript files to detect schema mismatches between data producers and consumers through static analysis, enabling automated validation and code generation.

Instructions

Trace MCP tool usage in a single TypeScript file.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
filePathYesPath to a TypeScript file

Implementation Reference

  • Zod input schema validation for the trace_file tool.
    const TraceFileInput = z.object({
      filePath: z.string().describe('Path to a single TypeScript file to trace tool usage in'),
    });
  • src/index.ts:167-177 (registration)
    Tool registration in the listTools handler, defining name, description, and input schema.
    {
      name: 'trace_file',
      description: 'Trace MCP tool usage in a single TypeScript file.',
      inputSchema: {
        type: 'object',
        properties: {
          filePath: { type: 'string', description: 'Path to a TypeScript file' },
        },
        required: ['filePath'],
      },
    },
  • MCP CallToolRequest handler for 'trace_file': parses input, calls traceFromFile, and formats response.
    case 'trace_file': {
      const input = TraceFileInput.parse(args);
      log(`Tracing file: ${input.filePath}`);
      
      const usage = await traceFromFile(input.filePath);
      
      return {
        content: [
          {
            type: 'text',
            text: JSON.stringify({
              success: true,
              count: usage.length,
              usage,
            }, null, 2),
          },
        ],
      };
    }
  • Core implementation of traceFromFile: delegates to language-specific parser for the given file.
    export async function traceFromFile(filePath: string, language?: string): Promise<ConsumerSchema[]> {
      // For backward compatibility, default to TypeScript
      const lang = language || 'typescript';
    
      if (!hasParser(lang)) {
        throw new Error(
          `No parser available for language: ${lang}. Make sure to call bootstrapLanguageParsers() at startup.`
        );
      }
    
      const parser = getParser(lang);
    
      // Extract from the directory containing the file
      const rootDir = filePath.substring(0, filePath.lastIndexOf('/') || filePath.lastIndexOf('\\'));
      const fileName = filePath.substring((filePath.lastIndexOf('/') || filePath.lastIndexOf('\\')) + 1);
    
      const allSchemas = await parser.traceUsage({
        rootDir: rootDir || '.',
        include: [fileName],
      });
    
      return allSchemas.filter(s => s.callSite.file === filePath);
    }
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 states the action ('Trace MCP tool usage') but doesn't explain what 'trace' entails (e.g., output format, whether it modifies the file, error handling, or performance implications). This leaves significant gaps in understanding the tool's behavior beyond its basic purpose.

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 directly states the tool's purpose without any wasted words. It is appropriately sized and front-loaded, making it easy for an agent to parse and understand quickly.

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 tracing tool usage (which could involve analysis or logging), the lack of annotations and output schema means the description is incomplete. It doesn't cover what the tool returns, how it handles errors, or any behavioral traits, leaving the agent with insufficient information for effective use.

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?

The input schema has 100% description coverage, with 'filePath' clearly documented as 'Path to a TypeScript file'. The description doesn't add any extra meaning or context about the parameter beyond what the schema provides, so it meets the baseline for high schema coverage without compensating further.

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 verb ('Trace') and resource ('MCP tool usage in a single TypeScript file'), making the purpose specific and understandable. However, it doesn't explicitly differentiate from sibling tools like 'trace_usage' or 'extract_file', which might have overlapping functionality, so it doesn't reach the highest 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, such as 'trace_usage' or other siblings. It lacks context about prerequisites, exclusions, or specific scenarios where this tool is preferred, 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.

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