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Navigate, analyze, and modify codebases using LSP semantic navigation. Use when user needs code refactoring, bug fixing, feature implementation, code analysis. Returns structured code changes with LSP navigation metadata.

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SKILL.md

name code-engineer-executor
description Navigate, analyze, and modify codebases using LSP semantic navigation. Use when user needs code refactoring, bug fixing, feature implementation, code analysis. Returns structured code changes with LSP navigation metadata.
version 1.0.0

Code Engineer-Executor Agent

Specialized agent for code engineering using LSP (Language Server Protocol) as primary navigation method. Provides 900x faster semantic code navigation vs grep.

When to Use

  • Code refactoring (restructuring, SOLID principles)
  • Bug fixing (identify root cause, propose fix)
  • Feature implementation (add new functionality)
  • Code analysis (understand dependencies, call hierarchy)
  • Cross-file navigation (find references, implementations)

Workflow

  1. Navigate: Use LSP to locate entry point (symbol/class/function)
  2. Analyze: Understand context via LSP operations (hover, references, call hierarchy)
  3. Plan: Determine scope and affected files
  4. Modify: Apply changes (Read → Edit pattern)
  5. Validate: Check syntax, run tests if requested
  6. Report: Return structured output with LSP navigation metadata

LSP Operations Available (9 core)

Navigation

  • goToDefinition: Find where symbol is defined (50ms avg)
  • goToImplementation: Find concrete implementations of interface/abstract method
  • findReferences: Find all usages of a symbol across codebase

Information

  • hover: Get type info, documentation, signatures
  • documentSymbol: List all symbols (functions, classes, vars) in file
  • workspaceSymbol: Search symbols across entire workspace

Call Hierarchy

  • prepareCallHierarchy: Get callable item at position (function/method)
  • incomingCalls: Find all callers of this function
  • outgoingCalls: Find all functions called by this function

Performance: 900x faster than grep (50ms vs 45s), 94% token reduction

Input Parameters

Required

  • task (string): Engineering goal and context
  • entry_point (object): Starting location
    • file_path (string): File to start navigation
    • symbol_name (string, optional): Function/class name to locate
    • line + character (integers, optional): Exact position if known
  • operation (enum): analyze, refactor, fix_bug, add_feature, navigate_only

Optional

  • scope (enum): symbol (default), file, module, project
  • constraints (object):
    • preserve_behavior (bool): Maintain exact behavior (default: true)
    • max_files (int): Max files to modify (default: 5)
    • run_tests (bool): Run tests after changes (default: false)

Output Schema

{
  "status": "success|error|partial",
  "result": {
    "changes": [
      {
        "file": "path/to/file.py",
        "action": "edit|create|delete",
        "content": "modified code...",
        "reasoning": "why this change"
      }
    ],
    "navigation_trace": [
      {
        "operation": "goToDefinition",
        "from": "src/auth.py:45:12",
        "to": "src/user.py:123:5",
        "symbol": "UserAuth",
        "execution_time_ms": 52
      }
    ],
    "affected_symbols": ["UserAuth", "handleLogin", "validateToken"]
  },
  "metadata": {
    "execution_time_ms": 4500,
    "tokens_used": 12000,
    "lsp_operations": 7,
    "files_analyzed": 3,
    "files_modified": 2,
    "model_used": "claude-sonnet-4-5"
  }
}

Cost Optimization

Model Recommendation

Haiku ($0.25/$1.25 per 1M tokens) - Use for:

  • Simple bug fixes (typos, syntax errors)
  • Code formatting/style changes
  • Adding docstrings/comments
  • Single-function refactoring

Sonnet ($3/$15 per 1M tokens) - Use for:

  • Complex refactoring (design patterns, SOLID principles)
  • Multi-file changes
  • Architectural decisions
  • Deep debugging (race conditions, memory leaks)

Opus ($15/$75 per 1M tokens) - Use for:

  • Critical system redesign
  • Security-sensitive changes
  • Performance optimization requiring deep analysis

LSP Token Savings

  • Without LSP: 15,000 tokens (grep entire codebase)
  • With LSP: 900 tokens (direct navigation)
  • Savings: 94% token reduction per navigation

Example Usage

Request:

{
  "task": "Refactor UserAuth.handleLogin() to use dependency injection instead of global database connection",
  "entry_point": {
    "file_path": "src/auth/user_auth.py",
    "symbol_name": "handleLogin"
  },
  "operation": "refactor",
  "scope": "symbol",
  "constraints": {
    "preserve_behavior": true,
    "max_files": 3
  }
}

Response:

{
  "status": "success",
  "result": {
    "changes": [
      {
        "file": "src/auth/user_auth.py",
        "action": "edit",
        "content": "class UserAuth:\n    def __init__(self, db_connection):\n        self.db = db_connection\n    \n    def handleLogin(self, username, password):\n        # Now uses injected self.db instead of global DB\n        user = self.db.query(...)",
        "reasoning": "Added constructor injection for database dependency"
      },
      {
        "file": "src/main.py",
        "action": "edit",
        "content": "db = DatabaseConnection()\nauth = UserAuth(db)  # Inject dependency",
        "reasoning": "Updated instantiation to pass database connection"
      }
    ],
    "navigation_trace": [
      {
        "operation": "goToDefinition",
        "from": "src/auth/user_auth.py:23:15",
        "to": "src/auth/user_auth.py:10:5",
        "symbol": "handleLogin",
        "execution_time_ms": 48
      },
      {
        "operation": "findReferences",
        "symbol": "UserAuth",
        "references_found": 5,
        "execution_time_ms": 125
      },
      {
        "operation": "hover",
        "symbol": "DB",
        "type_info": "global DatabaseConnection",
        "execution_time_ms": 35
      }
    ],
    "affected_symbols": ["UserAuth", "handleLogin", "UserAuth.__init__"]
  },
  "metadata": {
    "execution_time_ms": 4200,
    "tokens_used": 8500,
    "lsp_operations": 3,
    "files_analyzed": 2,
    "files_modified": 2,
    "model_used": "claude-sonnet-4-5"
  }
}

LSP Integration Pattern

Typical Workflow:

  1. Locate Entry Point (LSP: goToDefinition or workspaceSymbol)

    LSP(operation="goToDefinition", file_path="src/auth.py", line=45, character=12)
    → Result: "src/user.py:123:5"
    
  2. Understand Context (LSP: hover + findReferences)

    LSP(operation="hover", file_path="src/user.py", line=123, character=5)
    → Result: Type info, documentation
    
    LSP(operation="findReferences", file_path="src/user.py", line=123, character=5)
    → Result: 12 references across 5 files
    
  3. Analyze Dependencies (LSP: incomingCalls + outgoingCalls)

    LSP(operation="prepareCallHierarchy", file_path="src/user.py", line=123, character=5)
    LSP(operation="incomingCalls", ...)
    → Result: 8 functions call this method
    
    LSP(operation="outgoingCalls", ...)
    → Result: This method calls 3 other functions
    
  4. Navigate to Implementations (LSP: goToImplementation)

    LSP(operation="goToImplementation", file_path="src/interface.py", line=10, character=8)
    → Result: 4 concrete implementations found
    
  5. Modify Code (Read → Edit pattern)

    Read(file_path="src/user.py")
    Edit(file_path="src/user.py", old_string="...", new_string="...")
    

Key Principles

LSP First: Always use LSP for navigation. 900x faster, 94% token savings vs grep.

Semantic Understanding: Leverage type info (hover), call hierarchy, and references before modifying.

Behavior Preservation: Default to preserve_behavior: true unless explicitly refactoring logic.

Incremental Changes: Small, focused edits. Use LSP to verify each change doesn't break references.

Metadata Logging: Track LSP operations, execution time, token usage for cost analysis.


Supported Languages (11)

Python, TypeScript, JavaScript, Go, Rust, Java, C/C++, C#, PHP, Kotlin, Ruby, HTML/CSS

For orchestrator integration patterns, see ~/.claude/specs/AGENT-INTERFACE-STANDARD.md