Codex Parallel Subagents
DEPRECATED: This skill is deprecated. Use evolving-workflow instead, which provides a declarative workflow API with built-in parallel execution support via .concurrency(n).
Run multiple AI agent threads concurrently with bounded parallelism and collect results safely.
When to use this skill
- Running multiple agent tasks in parallel
- Fan-out work across files, packages, or repositories
- Batch processing with rate limiting
- Streaming progress from concurrent tasks
- Collecting structured outputs from multiple agents
Quick navigation
Production-ready assets
Copy these to jumpstart your implementation:
| Asset |
Description |
Run |
| parallel_batch |
Reentrant batch processing with stdin/file input, offset/limit, JSON output |
moon run -C assets/parallel_batch assets/parallel_batch |
| package_analyzer |
Discover and summarize all MoonBit packages |
moon run -C assets/package_analyzer assets/package_analyzer |
How to use these assets
- Copy the asset directory to your project
- Customize
run_task() (or the main processing function) for your use case
- Adjust structs (
TaskInput, etc.) if you need additional fields
- Set environment variables as needed (
CODEX_WORKDIR, PARALLELISM)
See each asset's README for detailed usage and options.
Key rules
- One thread per task - never share threads across concurrent tasks
- Use semaphores - guard parallel runs with
@async.Semaphore::new(n) to avoid rate limits
- Set working directory - use
ThreadOptions::new(working_directory=...) for task isolation
- Allow failures - use
allow_failure=true and capture errors per task
- Avoid conflicts - for tasks that modify shared resources (e.g., building software, editing same files), use git worktrees or separate directories to isolate each agent