Bash Tool ↗

The bash tool enables Claude to execute shell commands in a persistent bash session, allowing system operations, script execution, and command-line automation. Shell access is a foundational agent capability. On Terminal-Bench 2.0, a benchmark that evaluates real-world terminal tasks using shell-only validation, Claude shows strong performance gains with access to a persistent bash session.

Overview#

The bash tool provides Claude with:

• Persistent bash session that maintains state
• Ability to run any shell command
• Access to environment variables and working directory
• Command chaining and scripting capabilities

Model compatibility#

Older tool versions are not guaranteed to be backwards-compatible with newer models. Always use the tool version that corresponds to your model version.

Use cases#

• Development workflows: Run build commands, tests, and development tools
• System automation: Execute scripts, manage files, automate tasks
• Data processing: Process files, run analysis scripts, manage datasets
• Environment setup: Install packages, configure environments

Quick start#

import anthropic

client = anthropic.Anthropic()

response = client.messages.create(
    model="claude-opus-4-6",
    max_tokens=1024,
    tools=[{"type": "bash_20250124", "name": "bash"}],
    messages=[
        {"role": "user", "content": "List all Python files in the current directory."}
    ],
)

curl https://api.anthropic.com/v1/messages \
  -H "content-type: application/json" \
  -H "x-api-key: $ANTHROPIC_API_KEY" \
  -H "anthropic-version: 2023-06-01" \
  -d '{
    "model": "claude-opus-4-6",
    "max_tokens": 1024,
    "tools": [
      {
        "type": "bash_20250124",
        "name": "bash"
      }
    ],
    "messages": [
      {
        "role": "user",
        "content": "List all Python files in the current directory."
      }
    ]
  }'

How it works#

The bash tool maintains a persistent session:

1. Claude determines what command to run
2. You execute the command in a bash shell
3. Return the output (stdout and stderr) to Claude
4. Session state persists between commands (environment variables, working directory)

Parameters#

*Required unless using restart

{
  "command": "ls -la *.py"
}

{
  "restart": true
}

Example: Multi-step automation#

Claude can chain commands to complete complex tasks:

# User request
"Install the requests library and create a simple Python script that fetches a joke from an API, then run it."

# Claude's tool uses:
# 1. Install package
{"command": "pip install requests"}

# 2. Create script
{
    "command": "cat > fetch_joke.py << 'EOF'\nimport requests\nresponse = requests.get('https://official-joke-api.appspot.com/random_joke')\njoke = response.json()\nprint(f\"Setup: {joke['setup']}\")\nprint(f\"Punchline: {joke['punchline']}\")\nEOF"
}

# 3. Run script
{"command": "python fetch_joke.py"}

The session maintains state between commands, so files created in step 2 are available in step 3.

Implement the bash tool#

The bash tool is implemented as a schema-less tool. When using this tool, you don’t need to provide an input schema as with other tools; the schema is built into Claude’s model and can’t be modified.

Create a persistent bash session that Claude can interact with:

    import subprocess
    import threading
    import queue


    class BashSession:
        def __init__(self):
            self.process = subprocess.Popen(
                ["/bin/bash"],
                stdin=subprocess.PIPE,
                stdout=subprocess.PIPE,
                stderr=subprocess.PIPE,
                text=True,
                bufsize=0,
            )
            self.output_queue = queue.Queue()
            self.error_queue = queue.Queue()
            self._start_readers()
    ```
  <span class="step-end"></span>
  <span class="step-marker" data-step-title="Handle command execution"></span>
Create a function to execute commands and capture output:
```python
    def execute_command(self, command):
        # Send command to bash
        self.process.stdin.write(command + "\n")
        self.process.stdin.flush()

        # Capture output with timeout
        output = self._read_output(timeout=10)
        return output
    ```
  <span class="step-end"></span>
  <span class="step-marker" data-step-title="Process Claude's tool calls"></span>
Extract and execute commands from Claude's responses:
```python
    for content in response.content:
        if content.type == "tool_use" and content.name == "bash":
            if content.input.get("restart"):
                bash_session.restart()
                result = "Bash session restarted"
            else:
                command = content.input.get("command")
                result = bash_session.execute_command(command)

            # Return result to Claude
            tool_result = {
                "type": "tool_result",
                "tool_use_id": content.id,
                "content": result,
            }
    ```
  <span class="step-end"></span>
  <span class="step-marker" data-step-title="Implement safety measures"></span>
Add validation and restrictions:
```python
    def validate_command(command):
        # Block dangerous commands
        dangerous_patterns = ["rm -rf /", "format", ":(){:|:&};:"]
        for pattern in dangerous_patterns:
            if pattern in command:
                return False, f"Command contains dangerous pattern: {pattern}"

        # Add more validation as needed
        return True, None
    ```
  <span class="step-end"></span>
<span class="steps-end"></span>

### Handle errors

When implementing the bash tool, handle various error scenarios:

<details class="collapsible-section"><summary>Command execution timeout</summary>

If a command takes too long to execute:

```json
{
  "role": "user",
  "content": [
    {
      "type": "tool_result",
      "tool_use_id": "toolu_01A09q90qw90lq917835lq9",
      "content": "Error: Command timed out after 30 seconds",
      "is_error": true
    }
  ]
}

{
  "role": "user",
  "content": [
    {
      "type": "tool_result",
      "tool_use_id": "toolu_01A09q90qw90lq917835lq9",
      "content": "bash: nonexistentcommand: command not found",
      "is_error": true
    }
  ]
}

{
  "role": "user",
  "content": [
    {
      "type": "tool_result",
      "tool_use_id": "toolu_01A09q90qw90lq917835lq9",
      "content": "bash: /root/sensitive-file: Permission denied",
      "is_error": true
    }
  ]
}

Follow implementation best practices#

def execute_with_timeout(command, timeout=30):
    try:
        result = subprocess.run(
            command, shell=True, capture_output=True, text=True, timeout=timeout
        )
        return result.stdout + result.stderr
    except subprocess.TimeoutExpired:
        return f"Command timed out after {timeout} seconds"

# Commands run in the same session maintain state
commands = [
    "cd /tmp",
    "echo 'Hello' > test.txt",
    "cat test.txt",  # This works because we're still in /tmp
]

def truncate_output(output, max_lines=100):
    lines = output.split("\n")
    if len(lines) > max_lines:
        truncated = "\n".join(lines[:max_lines])
        return f"{truncated}\n\n... Output truncated ({len(lines)} total lines) ..."
    return output

import logging


def log_command(command, output, user_id):
    logging.info(f"User {user_id} executed: {command}")
    logging.info(f"Output: {output[:200]}...")  # Log first 200 chars

def sanitize_output(output):
    # Remove potential secrets or credentials
    import re

    # Example: Remove AWS credentials
    output = re.sub(r"aws_access_key_id\s*=\s*\S+", "aws_access_key_id=***", output)
    output = re.sub(
        r"aws_secret_access_key\s*=\s*\S+", "aws_secret_access_key=***", output
    )
    return output

Security#

The bash tool provides direct system access. Implement these essential safety measures:

• Running in isolated environments (Docker/VM)
• Implementing command filtering and allowlists
• Setting resource limits (CPU, memory, disk)
• Logging all executed commands

Key recommendations#

• Use ulimit to set resource constraints
• Filter dangerous commands (sudo, rm -rf, etc.)
• Run with minimal user permissions
• Monitor and log all command execution

Pricing#

The bash tool adds 245 input tokens to your API calls.

Additional tokens are consumed by:

• Command outputs (stdout/stderr)
• Error messages
• Large file contents

See tool use pricing for complete pricing details.

Common patterns#

Development workflows#

• Running tests: pytest && coverage report
• Building projects: npm install && npm run build
• Git operations: git status && git add . && git commit -m "message"

Git-based checkpointing#

Git serves as a structured recovery mechanism in long-running agent workflows, not just a way to save changes:

• Capture a baseline: Before any agent work begins, commit the current state. This is the known-good starting point.
• Commit per feature: Each completed feature gets its own commit. These serve as rollback points if something goes wrong later.
• Reconstruct state at session start: Read git log alongside a progress file to understand what has already been done and what comes next.
• Revert on failure: If work goes sideways, git checkout reverts to the last good commit instead of trying to debug a broken state.

File operations#

• Processing data: wc -l *.csv && ls -lh *.csv
• Searching files: find . -name "*.py" | xargs grep "pattern"
• Creating backups: tar -czf backup.tar.gz ./data

System tasks#

• Checking resources: df -h && free -m
• Process management: ps aux | grep python
• Environment setup: export PATH=$PATH:/new/path && echo $PATH

Limitations#

• No interactive commands: Cannot handle vim, less, or password prompts
• No GUI applications: Command-line only
• Session scope: Persists within conversation, lost between API calls
• Output limits: Large outputs may be truncated
• No streaming: Results returned after completion

Combining with other tools#

The bash tool is most powerful when combined with the text editor and other tools.

If you’re also using the code execution tool, Claude has access to two separate execution environments: your local bash session and Anthropic’s sandboxed container. State is not shared between them. See Using code execution with other execution tools for guidance on prompting Claude to distinguish between environments.

Next steps#

Learn about tool use with Claude

View and edit text files with Claude