optimizer

Agent Optimization Skill (Optimizer)

📌 Mandatory Usage Guidelines

CRITICAL: READ BEFORE USE. Adherence to these rules is essential for the skill to function correctly.

1. Tool Calls are Direct:

   • ✅ DO call tool functions like CAST_ANALYSIS(...) and CAST_CODER(...) directly.
   • ❌ DO NOT write or show Python code examples that import or manually implement tool logic (e.g., from aworld.experimental.ast import ACast). The tools are pre-loaded and ready for direct invocation.

2. CAST_ANALYSIS Query Format:

   • ✅ DO use regular expression (regex) patterns for all search_ast queries.
     • Example: .*MyClassName.*|.*my_function_name.*
   • ❌ DO NOT use natural language for search_ast queries.
     • Incorrect: "Show me the implementation of the MyClassName class"

3. CAST_CODER Workflow:

   • ✅ DO use CAST_CODER.generate_snapshot to create a backup before any modifications.
   • ✅ DO generate patch content (either structured JSON for search_replace or diff format text) based on your analysis. The LLM's role is to create the patch content.
   • ✅ DO use CAST_CODER actions (like search_replace) to apply the generated patch content to the source code.
   • ❌ DO NOT show Python lists of patches to the user (e.g., patches = [...]).

4. Patch Content Rules:

   • ✅ DO ensure each patch operation targets only one file.
   • ✅ DO create focused patches that modify one logical block of code at a time for clarity and safety.
   • ✅ DO verify code with CAST_ANALYSIS.search_ast to get accurate line numbers and context before generating a diff.

📜 Skill Overview

The Optimizer Skill is an advanced agent capability designed to analyze and enhance other agents. It leverages Abstract Syntax Tree (AST) analysis to systematically improve an agent's behavior and performance.

It achieves this by focusing on an agent's core behavioral drivers: its system prompt (which controls its reasoning and workflow) and its tool configuration (mcp_config.py) (which defines its capabilities). By intelligently patching these high-impact areas, the Optimizer can rapidly correct flaws and expand an agent's functionality. This skill treats the target agent as a codebase, applying static analysis and automated patching to achieve its goals.