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code-alchemist01

Development Tools MCP Server

analyze_bundle_size

Analyze dependency bundle sizes to identify optimization opportunities and reduce application bloat in development projects.

Instructions

Analyze bundle size of dependencies

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
projectPathNoPath to project root

Implementation Reference

  • Handler for the 'analyze_bundle_size' tool: calls DependencyAnalyzer.analyzeBundleSize and formats the bundle size result for output.
    case 'analyze_bundle_size': {
      const size = await analyzer.analyzeBundleSize(projectPath);
      return {
        bundleSize: size,
        formatted: size ? Formatters.formatBytes(size) : 'N/A',
      };
    }
  • Input schema for 'analyze_bundle_size' tool defining the expected projectPath parameter.
    inputSchema: {
      type: 'object',
      properties: {
        projectPath: {
          type: 'string',
          description: 'Path to project root',
        },
      },
    },
  • Registration of the 'analyze_bundle_size' tool in the dependencyAnalysisTools array.
    {
      name: 'analyze_bundle_size',
      description: 'Analyze bundle size of dependencies',
      inputSchema: {
        type: 'object',
        properties: {
          projectPath: {
            type: 'string',
            description: 'Path to project root',
          },
        },
      },
    },
  • Helper method in DependencyAnalyzer class implementing the bundle size analysis logic (currently stubbed).
    async analyzeBundleSize(_projectPath: string): Promise<number | undefined> {
      // This is a simplified version. In production, we'd use bundle-phobia or webpack-bundle-analyzer
      // For now, return undefined
      return undefined;
    }
Behavior2/5

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

No annotations are provided, so the description carries full burden. It mentions analysis but doesn't disclose behavioral traits like whether it's read-only, if it modifies files, what output format to expect, or any performance considerations. This leaves critical operational details unspecified.

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 with no wasted words. It's front-loaded and appropriately sized for the tool's apparent simplicity, making it easy to parse 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 no annotations, no output schema, and a single parameter, the description is incomplete. It fails to explain what the analysis entails, what results are returned, or how it differs from related tools, leaving significant gaps for an AI agent to understand and use the tool 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?

The description adds no parameter semantics beyond the input schema, which has 100% coverage for the single parameter 'projectPath'. Since schema coverage is high, the baseline score is 3, as the schema adequately documents the parameter without additional description value.

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 'Analyze bundle size of dependencies' states the verb ('analyze') and resource ('bundle size of dependencies'), but it's vague about scope and depth. It doesn't distinguish from siblings like 'analyze_dependencies' or 'find_unused_dependencies', leaving ambiguity about what specifically is analyzed.

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?

No guidance is provided on when to use this tool versus alternatives. With many sibling tools (e.g., 'analyze_dependencies', 'check_vulnerabilities'), the description lacks context on prerequisites, typical use cases, or exclusions, offering no help in tool selection.

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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