OpenClaw skill
codex-orchestration
An OpenClaw skill that enables agents to orchestrate multiple Codex agents for solving complex, multi-step problems. It provides tools for spawning Codex sub-agents, delegating subtasks, facilitating inter-agent communication, and aggregating results.
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How this skill works
- Receives a complex task from the OpenClaw agent
- Decomposes the task into subtasks using OpenAI Codex
- Generates Python code for each subtask via Codex
- Assembles subtasks and code into an orchestration plan
- Returns the plan to the agent for execution
When to use it
- When an agent needs to orchestrate complex multi-step tasks using Codex planning and execution
- When breaking down high-level goals into executable sub-tasks managed by Codex
- When coordinating dynamic workflows involving code generation, validation, and iteration with Codex
Best practices
- Set OPENAI_API_KEY environment variable
- Provide language, context, and examples in prompts for optimal results
- Use low temperature (default 0.2) for consistent code generation
- Limit MAX_TOKENS to control costs and output length
- Monitor OpenAI API usage and costs via dashboard
- Consider GPT-4 alternatives as Codex models are deprecated
Example use cases
- Code completion with Codex: Completes partial code snippets using the Codex model based on a provided prompt.
- Code editing and fixing with Codex: Edits existing code according to specific instructions, such as fixing bugs or refactoring.
- Generating Python web scrapers: Orchestrates Codex to produce complete Python scripts for web scraping tasks.
- Optimizing SQL queries: Uses Codex to analyze and optimize SQL queries for better performance.
- Generating unit tests: Leverages Codex to create unit tests for given codebases.
FAQs
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