Spawning Agents via CLI

Overview

Subagents don't have access to the Task tool. When you need to delegate work as a subagent, spawn Claude instances via CLI backgrounding:

cat [prompt-file] | claude -p --output-format json

Core principle: Spawn fresh Claude instances with clean context for independent work, get structured JSON responses.

When to Use

Use when:

• You're a subagent and need to delegate work (can't use Task tool)
• Context budget is tight and delegation would be more efficient
• You need parallel analysis of independent items
• Task benefits from fresh context without conversation history

Don't use when:

• You're the main Claude instance (use Task tool instead)
• You can efficiently do the work yourself with available tools
• The task requires shared conversation context that's hard to serialize
• You were just spawned to do a specific task - do the work, don't spawn another level

Recursion guard: If you were spawned via this technique, do the work you were spawned for. Don't spawn yet another agent unless the task genuinely requires parallel delegation.

Core Pattern

Before (baseline failure):

Subagent receives large analysis task
→ Tries to do everything itself
→ Burns context budget on work that could be delegated
→ May hit limits or inefficiency

After (with spawning):

Subagent receives large analysis task
→ Writes focused prompt to file
→ Backgrounds: cat prompt.txt | claude -p --output-format json
→ Polls BashOutput until complete
→ Parses JSON response and continues work

Quick Reference

Implementation

Step 1: Write Focused Prompt

**Role:** You are analyzing TypeScript error patterns.

**Task:**
Search /path/to/code for all files with TypeScript errors and categorize by error type.

**Deliver:**
A JSON object with error categories and file counts.

Context passing:

• Use --add-dir /path/to/files if spawned agent needs file access
• Use --tools "Read,Grep,Glob" to limit available tools if needed
• Leave --system-prompt alone - let spawned agent use normal prompts

Step 2: Background the Spawn

cat task-prompt.txt | claude -p --output-format json

Use run_in_background: true in Bash tool. Capture the bash_id.

Step 3: Poll for Completion

System reminders notify you when output available:

<system-reminder>
Background Bash abc123 (...) Has new output available.
</system-reminder>

Poll with BashOutput tool:

BashOutput({ bash_id: "abc123" })
// Returns: { status: "completed", exit_code: 0, stdout: "{...}" }

Polling strategy:

• Wait 3-5 seconds between polls (use sleep command)
• System reminder appears when output ready
• Process ends when work complete, not at timeout

Step 4: Parse JSON Response

{
  "type": "result",
  "subtype": "success",
  "is_error": false,
  "result": "your actual answer here",
  "session_id": "...",
  "duration_ms": 7125,
  "total_cost_usd": 0.18
}

Extract the result field for the actual answer.

Error handling:

• Check is_error: true for failures
• Check exit_code from BashOutput (0 = success)
• Empty/malformed JSON = spawned agent failed

Common Rationalizations

Common Mistakes

❌ Forgetting You Don't Have Task Tool

You are a subagent
→ Tries Task tool
→ Tool not available

Fix: Use CLI spawning instead.

❌ Not Passing File Access

cat prompt.txt | claude -p --output-format json
→ Spawned agent: "I don't have access to /some/path"

Fix: Add --add-dir /some/path to command.

❌ Constant Polling Without Sleep

while not complete:
    check BashOutput every few milliseconds
    → Burns through tool calls

Fix: Use sleep 3 between polls. System reminders notify when ready.

❌ Not Handling JSON Parse Errors

Parse stdout directly
→ Malformed JSON crashes

Fix: Check exit_code: 0 and is_error: false before parsing.

Real-World Impact

Context efficiency: Spawning agents with fresh context can be 50-100x more efficient than loading large files into current context.

Parallel work: Spawn multiple agents for independent tasks, poll all, gather results.

Subagent capability: Subagents can now delegate just like main instances (via different mechanism).