codex-subagent
Spawn autonomous subagents to offload context-heavy work and preserve parent token budget.
- Subagents burn their own tokens and return only final results, ideal for deep research (3+ searches), codebase exploration (8+ files), multi-step workflows, and long-running operations
- Choose between mini model (gpt-5.1-codex-mini) for pure search tasks or inherit parent model for multi-step analysis, refactoring, and generation work
- Supports up to 5 parallel subagents via background shell execution with file-based output capture using
-oparameter or JSONL event stream parsing - Requires detailed, context-rich prompts following a structured template: task context, specific objectives, constraints, output format, and success criteria
Codex Subagent Skill
Spawn autonomous subagents to offload context-heavy work. Subagents burn their own tokens, return only final results.
Golden Rule: If task + intermediate work would add 3,000+ tokens to parent context → use subagent.
Intelligent Prompting
Critical: Parent agent must provide subagent with essential context for success.
Good Prompting Principles
- Include relevant context - Give the subagent thorough context
- Be specific - Clear constraints, requirements, output format
- Provide direction - Where to look, what sources to prioritize
- Define success - What constitutes a complete answer
Examples
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