Claude Code CLI — Programmatic Usage

Use Claude Code as a programmable agent from shell scripts, CI/CD pipelines, Python, or TypeScript. The CLI’s -p (print) flag runs non-interactively; the Agent SDK gives full programmatic control.

Quick Start

One-shot task (CLI)

claude -p "Find and fix the bug in auth.py" --allowedTools "Read,Edit,Bash"

Python SDK

import asyncio
from claude_agent_sdk import query, ClaudeAgentOptions

async def main():
    async for message in query(
        prompt="Find and fix the bug in auth.py",
        options=ClaudeAgentOptions(allowed_tools=["Read", "Edit", "Bash"])
    ):
        if hasattr(message, "result"):
            print(message.result)

asyncio.run(main())

TypeScript SDK

import { query, ClaudeAgentOptions } from "@anthropic-ai/claude-agent-sdk";

for await (const message of query({
  prompt: "Find and fix the bug in auth.py",
  options: { allowedTools: ["Read", "Edit", "Bash"] },
})) {
  if (message.result) console.log(message.result);
}

Core Concepts

Print Mode (-p)

The -p flag runs Claude non-interactively. All CLI flags work with -p:

claude -p "What does the auth module do?"

Key flags for programmatic use:

Structured Output

Get JSON responses with metadata:

claude -p "Summarize this project" --output-format json

Response includes result (text), session_id, and usage metadata.

For schema-validated output, add --json-schema:

claude -p "Extract function names from auth.py" \
  --output-format json \
  --json-schema '{"type":"object","properties":{"functions":{"type":"array","items":{"type":"string"}}},"required":["functions"]}'

Structured result is in the structured_output field. Parse with jq:

claude -p "Summarize this project" --output-format json | jq -r '.result'

Streaming Output

Stream tokens as they arrive:

claude -p "Explain recursion" \
  --output-format stream-json --verbose --include-partial-messages

Filter for text deltas with jq:

claude -p "Write a poem" \
  --output-format stream-json --verbose --include-partial-messages | \
  jq -rj 'select(.type == "stream_event" and .event.delta.type? == "text_delta") | .event.delta.text'

Auto-Approve Tools

Skip permission prompts for specific tools:

claude -p "Run tests and fix failures" --allowedTools "Bash,Read,Edit"

Use permission rule syntax with prefix matching (* after a space):

claude -p "Create a commit" \
  --allowedTools "Bash(git diff *),Bash(git log *),Bash(git status *),Bash(git commit *)"

Skip ALL permission prompts (use with caution):

claude -p "Fix all lint errors" --dangerously-skip-permissions

Session Management

Continue the most recent conversation:

claude -p "Review this codebase for issues"
claude -p "Now focus on database queries" --continue
claude -p "Generate a summary" --continue

Capture and resume by session ID:

session_id=$(claude -p "Start review" --output-format json | jq -r '.session_id')
claude -p "Continue that review" --resume "$session_id"

System Prompt Customization

Append to default prompt (recommended — preserves built-in capabilities):

claude -p "Review this PR" \
  --append-system-prompt "You are a security engineer. Focus on vulnerabilities."

Replace entire prompt:

claude -p "Analyze this code" \
  --system-prompt "You are a Python expert who only writes type-annotated code"

Load prompts from files (print mode only):

claude -p "Review this PR" --append-system-prompt-file ./prompts/security-rules.txt
claude -p "Analyze code" --system-prompt-file ./prompts/custom-prompt.txt

Piping Input

Pipe content to Claude via stdin:

cat error.log | claude -p "Explain these errors"
gh pr diff 123 | claude -p "Review this diff for security issues"
git diff --staged | claude -p "Write a commit message for these changes"

Subagents

Define custom subagents inline via --agents JSON:

claude --agents '{
  "code-reviewer": {
    "description": "Expert code reviewer. Use proactively after code changes.",
    "prompt": "You are a senior code reviewer. Focus on quality, security, and best practices.",
    "tools": ["Read", "Grep", "Glob", "Bash"],
    "model": "sonnet"
  },
  "debugger": {
    "description": "Debugging specialist for errors and test failures.",
    "prompt": "You are an expert debugger. Analyze errors, identify root causes, and provide fixes."
  }
}'

Subagent fields: description (required), prompt (required), tools, disallowedTools, model (sonnet/opus/haiku/inherit), skills, mcpServers, maxTurns, permissionMode.

File-based subagents go in .claude/agents/ (project) or ~/.claude/agents/ (personal):

---
name: code-reviewer
description: Reviews code for quality and best practices
tools: Read, Glob, Grep
model: sonnet
---
You are a code reviewer. Analyze code and provide specific,
actionable feedback on quality, security, and best practices.

Agent Teams (Experimental)

Coordinate multiple Claude Code instances working in parallel:

# Enable first
export CLAUDE_CODE_EXPERIMENTAL_AGENT_TEAMS=1

# Then ask Claude to create a team
claude "Create an agent team: one on security, one on performance, one on test coverage to review PR #142"

Teams have a lead (coordinator) and teammates (workers). Each teammate has its own context window. Communication is via shared task lists and direct messaging.

Additional Resources

• For the complete CLI flags reference, see cli-reference.md
• For Python and TypeScript Agent SDK details, see agent-sdk.md
• For common automation patterns and CI/CD recipes, see patterns.md

Source Documentation

• Claude Code CLI Reference
• Programmatic Usage (Headless)
• Agent SDK Overview
• Subagents
• Agent Teams