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code-alchemist01

Development Tools MCP Server

fix_lint_issues

Automatically fix linting issues in code files to improve code quality and maintain consistency across your development projects.

Instructions

Automatically fix linting issues in code files

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
filesYesFile paths to fix

Implementation Reference

  • Core implementation of fix_lint_issues tool: runs ESLint with auto-fix on specified files, applies fixes, and returns updated lint results.
    async fixLintIssues(filePaths: string[]): Promise<LintResult[]> {
      try {
        const eslint = new ESLint({
          useEslintrc: true,
          fix: true,
        });
    
        const results = await eslint.lintFiles(filePaths);
        await ESLint.outputFixes(results);
    
        return this.lintFiles(filePaths);
      } catch (error) {
        if (error instanceof Error && error.message.includes('No ESLint configuration')) {
          return filePaths.map((file) => ({
            file,
            messages: [],
            errorCount: 0,
            warningCount: 0,
            fixableErrorCount: 0,
            fixableWarningCount: 0,
          }));
        }
        throw error;
      }
    }
  • Registers the 'fix_lint_issues' tool in the lintingTools array with name, description, and input schema.
    {
      name: 'fix_lint_issues',
      description: 'Automatically fix linting issues in code files',
      inputSchema: {
        type: 'object',
        properties: {
          files: {
            type: 'array',
            items: { type: 'string' },
            description: 'File paths to fix',
          },
        },
        required: ['files'],
      },
    },
  • Dispatcher handler in handleLintingTool that invokes the fixLintIssues utility for the 'fix_lint_issues' tool.
    case 'fix_lint_issues': {
      const files = params.files as string[];
      const results = await lintingUtils.fixLintIssues(files);
      return Formatters.formatLintResults(results);
    }
  • Input schema defining the expected parameters (files array) for the fix_lint_issues tool.
    inputSchema: {
      type: 'object',
      properties: {
        files: {
          type: 'array',
          items: { type: 'string' },
          description: 'File paths to fix',
        },
      },
      required: ['files'],
    },
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 states the tool 'Automatically fix[es]' issues, implying mutation, but doesn't disclose behavioral traits like whether it modifies files in-place, requires specific permissions, handles errors, or has side effects. This is inadequate for a mutation tool with zero annotation coverage.

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 unnecessary words. It's front-loaded and wastes no space, making it easy for an agent 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 the tool's complexity (a mutation operation to fix code issues), lack of annotations, and no output schema, the description is incomplete. It doesn't explain what 'fixing' entails, potential risks, return values, or error handling, leaving significant gaps for safe and effective use by an agent.

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 the 'files' parameter documented as 'File paths to fix'. The description doesn't add meaning beyond this, such as file format support or path requirements. With high schema coverage, the baseline score of 3 is appropriate, as the schema handles parameter documentation adequately.

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 action ('Automatically fix') and target ('linting issues in code files'), which is specific and understandable. However, it doesn't distinguish this tool from its sibling 'lint_code', which presumably identifies linting issues without fixing them, leaving some ambiguity about differentiation.

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. Given siblings like 'lint_code' (likely for detection) and 'format_code' (for formatting, not necessarily linting), there's no indication of prerequisites, timing, or comparative use cases, leaving the agent to guess.

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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