2460 Agent Sdk Python 6152fc1a

Installation

pip install claude-agent-sdk

Choosing Between query() and ClaudeSDKClient

The Python SDK provides two ways to interact with Claude Code:

Quick Comparison

When to Use query() (New Session Each Time)

Best for:

• One-off questions where you don't need conversation history
• Independent tasks that don't require context from previous exchanges
• Simple automation scripts
• When you want a fresh start each time

When to Use ClaudeSDKClient (Continuous Conversation)

Best for:

• Continuing conversations - When you need Claude to remember context
• Follow-up questions - Building on previous responses
• Interactive applications - Chat interfaces, REPLs
• Response-driven logic - When next action depends on Claude's response
• Session control - Managing conversation lifecycle explicitly

Functions

query()

Creates a new session for each interaction with Claude Code. Returns an async iterator that yields messages as they arrive. Each call to query() starts fresh with no memory of previous interactions.

async def query(
    *,
    prompt: str | AsyncIterable[dict[str, Any]],
    options: ClaudeAgentOptions | None = None
) -> AsyncIterator[Message]

Parameters

Returns

Returns an AsyncIterator[Message] that yields messages from the conversation.

Example - With options

import asyncio
from claude_agent_sdk import query, ClaudeAgentOptions

async def main():
    options = ClaudeAgentOptions(
        system_prompt="You are an expert Python developer",
        permission_mode='acceptEdits',
        cwd="/home/user/project"
    )

    async for message in query(
        prompt="Create a Python web server",
        options=options
    ):
        print(message)

asyncio.run(main())

tool()

Decorator for defining MCP tools with type safety.

def tool(
    name: str,
    description: str,
    input_schema: type | dict[str, Any]
) -> Callable[[Callable[[Any], Awaitable[dict[str, Any]]]], SdkMcpTool[Any]]

Parameters

Input Schema Options

1. Simple type mapping (recommended):

    {"text": str, "count": int, "enabled": bool}
   

2. JSON Schema format (for complex validation):

    {
        "type": "object",
        "properties": {
            "text": {"type": "string"},
            "count": {"type": "integer", "minimum": 0}
        },
        "required": ["text"]
    }
   

Returns

A decorator function that wraps the tool implementation and returns an SdkMcpTool instance.

Example

from claude_agent_sdk import tool
from typing import Any

@tool("greet", "Greet a user", {"name": str})
async def greet(args: dict[str, Any]) -> dict[str, Any]:
    return {
        "content": [{
            "type": "text",
            "text": f"Hello, {args['name']}!"
        }]
    }

create_sdk_mcp_server()

Create an in-process MCP server that runs within your Python application.

def create_sdk_mcp_server(
    name: str,
    version: str = "1.0.0",
    tools: list[SdkMcpTool[Any]] | None = None
) -> McpSdkServerConfig

Parameters

Returns

Returns an McpSdkServerConfig object that can be passed to ClaudeAgentOptions.mcp_servers.

Example

from claude_agent_sdk import tool, create_sdk_mcp_server

@tool("add", "Add two numbers", {"a": float, "b": float})
async def add(args):
    return {
        "content": [{
            "type": "text",
            "text": f"Sum: {args['a'] + args['b']}"
        }]
    }

@tool("multiply", "Multiply two numbers", {"a": float, "b": float})
async def multiply(args):
    return {
        "content": [{
            "type": "text",
            "text": f"Product: {args['a'] * args['b']}"
        }]
    }

calculator = create_sdk_mcp_server(
    name="calculator",
    version="2.0.0",
    tools=[add, multiply]  # Pass decorated functions
)

# Use with Claude
options = ClaudeAgentOptions(
    mcp_servers={"calc": calculator},
    allowed_tools=["mcp__calc__add", "mcp__calc__multiply"]
)

Classes

ClaudeSDKClient

Maintains a conversation session across multiple exchanges. This is the Python equivalent of how the TypeScript SDK's query() function works internally - it creates a client object that can continue conversations.

Key Features

• Session Continuity: Maintains conversation context across multiple query() calls

• Same Conversation: Claude remembers previous messages in the session

• Interrupt Support: Can stop Claude mid-execution

• Explicit Lifecycle: You control when the session starts and ends

• Response-driven Flow: Can react to responses and send follow-ups

• Custom Tools & Hooks: Supports custom tools (created with @tool decorator) and hooks

  class ClaudeSDKClient: def init(self, options: ClaudeAgentOptions | None = None) async def connect(self, prompt: str | AsyncIterable[dict] | None = None) -> None async def query(self, prompt: str | AsyncIterable[dict], session_id: str = "default") -> None async def receive_messages(self) -> AsyncIterator[Message] async def receive_response(self) -> AsyncIterator[Message] async def interrupt(self) -> None async def disconnect(self) -> None

Methods

Context Manager Support

The client can be used as an async context manager for automatic connection management:

async with ClaudeSDKClient() as client:
    await client.query("Hello Claude")
    async for message in client.receive_response():
        print(message)

Important: When iterating over messages, avoid using break to exit early as this can cause asyncio cleanup issues. Instead, let the iteration complete naturally or use flags to track when you've found what you need.

Example - Continuing a conversation

import asyncio
from claude_agent_sdk import ClaudeSDKClient, AssistantMessage, TextBlock, ResultMessage

async def main():
    async with ClaudeSDKClient() as client:
        # First question
        await client.query("What's the capital of France?")

        # Process response
        async for message in client.receive_response():
            if isinstance(message, AssistantMessage):
                for block in message.content:
                    if isinstance(block, TextBlock):
                        print(f"Claude: {block.text}")

        # Follow-up question - Claude remembers the previous context
        await client.query("What's the population of that city?")

        async for message in client.receive_response():
            if isinstance(message, AssistantMessage):
                for block in message.content:
                    if isinstance(block, TextBlock):
                        print(f"Claude: {block.text}")

        # Another follow-up - still in the same conversation
        await client.query("What are some famous landmarks there?")

        async for message in client.receive_response():
            if isinstance(message, AssistantMessage):
                for block in message.content:
                    if isinstance(block, TextBlock):
                        print(f"Claude: {block.text}")

asyncio.run(main())

Example - Streaming input with ClaudeSDKClient

import asyncio
from claude_agent_sdk import ClaudeSDKClient

async def message_stream():
    """Generate messages dynamically."""
    yield {"type": "text", "text": "Analyze the following data:"}
    await asyncio.sleep(0.5)
    yield {"type": "text", "text": "Temperature: 25°C"}
    await asyncio.sleep(0.5)
    yield {"type": "text", "text": "Humidity: 60%"}
    await asyncio.sleep(0.5)
    yield {"type": "text", "text": "What patterns do you see?"}

async def main():
    async with ClaudeSDKClient() as client:
        # Stream input to Claude
        await client.query(message_stream())

        # Process response
        async for message in client.receive_response():
            print(message)

        # Follow-up in same session
        await client.query("Should we be concerned about these readings?")

        async for message in client.receive_response():
            print(message)

asyncio.run(main())

Example - Using interrupts

import asyncio
from claude_agent_sdk import ClaudeSDKClient, ClaudeAgentOptions

async def interruptible_task():
    options = ClaudeAgentOptions(
        allowed_tools=["Bash"],
        permission_mode="acceptEdits"
    )

    async with ClaudeSDKClient(options=options) as client:
        # Start a long-running task
        await client.query("Count from 1 to 100 slowly")

        # Let it run for a bit
        await asyncio.sleep(2)

        # Interrupt the task
        await client.interrupt()
        print("Task interrupted!")

        # Send a new command
        await client.query("Just say hello instead")

        async for message in client.receive_response():
            # Process the new response
            pass

asyncio.run(interruptible_task())

Example - Advanced permission control

from claude_agent_sdk import (
    ClaudeSDKClient,
    ClaudeAgentOptions
)

async def custom_permission_handler(
    tool_name: str,
    input_data: dict,
    context: dict
):
    """Custom logic for tool permissions."""

    # Block writes to system directories
    if tool_name == "Write" and input_data.get("file_path", "").startswith("/system/"):
        return {
            "behavior": "deny",
            "message": "System directory write not allowed",
            "interrupt": True
        }

    # Redirect sensitive file operations
    if tool_name in ["Write", "Edit"] and "config" in input_data.get("file_path", ""):
        safe_path = f"./sandbox/{input_data['file_path']}"
        return {
            "behavior": "allow",
            "updatedInput": {**input_data, "file_path": safe_path}
        }

    # Allow everything else
    return {
        "behavior": "allow",
        "updatedInput": input_data
    }

async def main():
    options = ClaudeAgentOptions(
        can_use_tool=custom_permission_handler,
        allowed_tools=["Read", "Write", "Edit"]
    )

    async with ClaudeSDKClient(options=options) as client:
        await client.query("Update the system config file")

        async for message in client.receive_response():
            # Will use sandbox path instead
            print(message)

asyncio.run(main())

Types

SdkMcpTool

Definition for an SDK MCP tool created with the @tool decorator.

@dataclass
class SdkMcpTool(Generic[T]):
    name: str
    description: str
    input_schema: type[T] | dict[str, Any]
    handler: Callable[[T], Awaitable[dict[str, Any]]]

ClaudeAgentOptions

Configuration dataclass for Claude Code queries.

@dataclass
class ClaudeAgentOptions:
    allowed_tools: list[str] = field(default_factory=list)
    system_prompt: str | SystemPromptPreset | None = None
    mcp_servers: dict[str, McpServerConfig] | str | Path = field(default_factory=dict)
    permission_mode: PermissionMode | None = None
    continue_conversation: bool = False
    resume: str | None = None
    max_turns: int | None = None
    disallowed_tools: list[str] = field(default_factory=list)
    model: str | None = None
    output_format: OutputFormat | None = None
    permission_prompt_tool_name: str | None = None
    cwd: str | Path | None = None
    settings: str | None = None
    add_dirs: list[str | Path] = field(default_factory=list)
    env: dict[str, str] = field(default_factory=dict)
    extra_args: dict[str, str | None] = field(default_factory=dict)
    max_buffer_size: int | None = None
    debug_stderr: Any = sys.stderr  # Deprecated
    stderr: Callable[[str], None] | None = None
    can_use_tool: CanUseTool | None = None
    hooks: dict[HookEvent, list[HookMatcher]] | None = None
    user: str | None = None
    include_partial_messages: bool = False
    fork_session: bool = False
    agents: dict[str, AgentDefinition] | None = None
    setting_sources: list[SettingSource] | None = None

OutputFormat

Configuration for structured output validation.

class OutputFormat(TypedDict):
    type: Literal["json_schema"]
    schema: dict[str, Any]

SystemPromptPreset

Configuration for using Claude Code's preset system prompt with optional additions.

class SystemPromptPreset(TypedDict):
    type: Literal["preset"]
    preset: Literal["claude_code"]
    append: NotRequired[str]

SettingSource

Controls which filesystem-based configuration sources the SDK loads settings from.

SettingSource = Literal["user", "project", "local"]

Default behavior

When setting_sources is omitted or None, the SDK does not load any filesystem settings. This provides isolation for SDK applications.

Why use setting_sources?

Load all filesystem settings (legacy behavior):

# Load all settings like SDK v0.0.x did
from claude_agent_sdk import query, ClaudeAgentOptions

async for message in query(
    prompt="Analyze this code",
    options=ClaudeAgentOptions(
        setting_sources=["user", "project", "local"]  # Load all settings
    )
):
    print(message)

Load only specific setting sources:

# Load only project settings, ignore user and local
async for message in query(
    prompt="Run CI checks",
    options=ClaudeAgentOptions(
        setting_sources=["project"]  # Only .claude/settings.json
    )
):
    print(message)

Testing and CI environments:

# Ensure consistent behavior in CI by excluding local settings
async for message in query(
    prompt="Run tests",
    options=ClaudeAgentOptions(
        setting_sources=["project"],  # Only team-shared settings
        permission_mode="bypassPermissions"
    )
):
    print(message)

SDK-only applications:

# Define everything programmatically (default behavior)
# No filesystem dependencies - setting_sources defaults to None
async for message in query(
    prompt="Review this PR",
    options=ClaudeAgentOptions(
        # setting_sources=None is the default, no need to specify
        agents={ /* ... */ },
        mcp_servers={ /* ... */ },
        allowed_tools=["Read", "Grep", "Glob"]
    )
):
    print(message)

Loading CLAUDE.md project instructions:

# Load project settings to include CLAUDE.md files
async for message in query(
    prompt="Add a new feature following project conventions",
    options=ClaudeAgentOptions(
        system_prompt={
            "type": "preset",
            "preset": "claude_code"  # Use Claude Code's system prompt
        },
        setting_sources=["project"],  # Required to load CLAUDE.md from project
        allowed_tools=["Read", "Write", "Edit"]
    )
):
    print(message)

Settings precedence

When multiple sources are loaded, settings are merged with this precedence (highest to lowest):

1. Local settings (.claude/settings.local.json)
2. Project settings (.claude/settings.json)
3. User settings (~/.claude/settings.json)

Programmatic options (like agents, allowed_tools) always override filesystem settings.

AgentDefinition

Configuration for a subagent defined programmatically.

@dataclass
class AgentDefinition:
    description: str
    prompt: str
    tools: list[str] | None = None
    model: Literal["sonnet", "opus", "haiku", "inherit"] | None = None

PermissionMode

Permission modes for controlling tool execution.

PermissionMode = Literal[
    "default",           # Standard permission behavior
    "acceptEdits",       # Auto-accept file edits
    "plan",              # Planning mode - no execution
    "bypassPermissions"  # Bypass all permission checks (use with caution)
]

McpSdkServerConfig

Configuration for SDK MCP servers created with create_sdk_mcp_server().

class McpSdkServerConfig(TypedDict):
    type: Literal["sdk"]
    name: str
    instance: Any  # MCP Server instance

McpServerConfig

Union type for MCP server configurations.

McpServerConfig = McpStdioServerConfig | McpSSEServerConfig | McpHttpServerConfig | McpSdkServerConfig

McpStdioServerConfig

class McpStdioServerConfig(TypedDict):
    type: NotRequired[Literal["stdio"]]  # Optional for backwards compatibility
    command: str
    args: NotRequired[list[str]]
    env: NotRequired[dict[str, str]]

McpSSEServerConfig

class McpSSEServerConfig(TypedDict):
    type: Literal["sse"]
    url: str
    headers: NotRequired[dict[str, str]]

McpHttpServerConfig

class McpHttpServerConfig(TypedDict):
    type: Literal["http"]
    url: str
    headers: NotRequired[dict[str, str]]

SdkPluginConfig

Configuration for loading plugins in the SDK.

class SdkPluginConfig(TypedDict):
    type: Literal["local"]
    path: str

Example:

plugins=[
    {"type": "local", "path": "./my-plugin"},
    {"type": "local", "path": "/absolute/path/to/plugin"}
]

For complete information on creating and using plugins, see Plugins.

Message Types

Message

Union type of all possible messages.

Message = UserMessage | AssistantMessage | SystemMessage | ResultMessage

Note: When include_partial_messages=True, you will also receive StreamEvent messages containing real-time text deltas. See StreamEvent below.

UserMessage

User input message.

@dataclass
class UserMessage:
    content: str | list[ContentBlock]

AssistantMessage

Assistant response message with content blocks.

@dataclass
class AssistantMessage:
    content: list[ContentBlock]
    model: str

SystemMessage

System message with metadata.

@dataclass
class SystemMessage:
    subtype: str
    data: dict[str, Any]

ResultMessage

Final result message with cost and usage information.

@dataclass
class ResultMessage:
    subtype: str
    duration_ms: int
    duration_api_ms: int
    is_error: bool
    num_turns: int
    session_id: str
    total_cost_usd: float | None = None
    usage: dict[str, Any] | None = None
    result: str | None = None

StreamEvent

Streaming event message, only received when include_partial_messages=True. Contains raw Anthropic API streaming events for real-time text updates.

@dataclass
class StreamEvent:
    uuid: str
    session_id: str
    event: dict[str, Any]  # Raw Anthropic streaming event
    parent_tool_use_id: str | None = None

The event dict contains Anthropic streaming events. Key event types:

Example - Handling streaming text deltas

from claude_agent_sdk import ClaudeSDKClient, ClaudeAgentOptions, AssistantMessage, TextBlock

async def stream_responses():
    options = ClaudeAgentOptions(
        include_partial_messages=True,  # Enable streaming events
        allowed_tools=["Read"]
    )

    async with ClaudeSDKClient(options=options) as client:
        await client.query("Explain Python decorators")

        async for message in client.receive_response():
            # Handle streaming deltas
            if type(message).__name__ == "StreamEvent":
                event = message.event
                if event.get("type") == "content_block_delta":
                    delta = event.get("delta", {})
                    if delta.get("type") == "text_delta":
                        print(delta.get("text", ""), end="", flush=True)

            # Handle complete message (also received after streaming)
            elif isinstance(message, AssistantMessage):
                for block in message.content:
                    if isinstance(block, TextBlock):
                        print(f"\n[Complete]: {block.text}")

Content Block Types

ContentBlock

Union type of all content blocks.

ContentBlock = TextBlock | ThinkingBlock | ToolUseBlock | ToolResultBlock

TextBlock

Text content block.

@dataclass
class TextBlock:
    text: str

ThinkingBlock

Thinking content block (for models with thinking capability).

@dataclass
class ThinkingBlock:
    thinking: str
    signature: str

ToolUseBlock

Tool use request block.

@dataclass
class ToolUseBlock:
    id: str
    name: str
    input: dict[str, Any]

ToolResultBlock

Tool execution result block.

@dataclass
class ToolResultBlock:
    tool_use_id: str
    content: str | list[dict[str, Any]] | None = None
    is_error: bool | None = None

Error Types

ClaudeSDKError

Base exception class for all SDK errors.

class ClaudeSDKError(Exception):
    """Base error for Claude SDK."""

CLINotFoundError

Raised when Claude Code CLI is not installed or not found.

class CLINotFoundError(CLIConnectionError):
    def __init__(self, message: str = "Claude Code not found", cli_path: str | None = None):
        """
        Args:
            message: Error message (default: "Claude Code not found")
            cli_path: Optional path to the CLI that was not found
        """

CLIConnectionError

Raised when connection to Claude Code fails.

class CLIConnectionError(ClaudeSDKError):
    """Failed to connect to Claude Code."""

ProcessError

Raised when the Claude Code process fails.

class ProcessError(ClaudeSDKError):
    def __init__(self, message: str, exit_code: int | None = None, stderr: str | None = None):
        self.exit_code = exit_code
        self.stderr = stderr

CLIJSONDecodeError

Raised when JSON parsing fails.

class CLIJSONDecodeError(ClaudeSDKError):
    def __init__(self, line: str, original_error: Exception):
        """
        Args:
            line: The line that failed to parse
            original_error: The original JSON decode exception
        """
        self.line = line
        self.original_error = original_error

Hook Types

HookEvent

Supported hook event types. Note that due to setup limitations, the Python SDK does not support SessionStart, SessionEnd, and Notification hooks.

HookEvent = Literal[
    "PreToolUse",      # Called before tool execution
    "PostToolUse",     # Called after tool execution
    "UserPromptSubmit", # Called when user submits a prompt
    "Stop",            # Called when stopping execution
    "SubagentStop",    # Called when a subagent stops
    "PreCompact"       # Called before message compaction
]

HookCallback

Type definition for hook callback functions.

HookCallback = Callable[
    [dict[str, Any], str | None, HookContext],
    Awaitable[dict[str, Any]]
]

Parameters:

• input_data: Hook-specific input data (see hook documentation)
• tool_use_id: Optional tool use identifier (for tool-related hooks)
• context: Hook context with additional information

Returns a dictionary that may contain:

• decision: "block" to block the action
• systemMessage: System message to add to the transcript
• hookSpecificOutput: Hook-specific output data

HookContext

Context information passed to hook callbacks.

@dataclass
class HookContext:
    signal: Any | None = None  # Future: abort signal support

HookMatcher

Configuration for matching hooks to specific events or tools.

@dataclass
class HookMatcher:
    matcher: str | None = None        # Tool name or pattern to match (e.g., "Bash", "Write|Edit")
    hooks: list[HookCallback] = field(default_factory=list)  # List of callbacks to execute

Hook Usage Example

from claude_agent_sdk import query, ClaudeAgentOptions, HookMatcher, HookContext
from typing import Any

async def validate_bash_command(
    input_data: dict[str, Any],
    tool_use_id: str | None,
    context: HookContext
) -> dict[str, Any]:
    """Validate and potentially block dangerous bash commands."""
    if input_data['tool_name'] == 'Bash':
        command = input_data['tool_input'].get('command', '')
        if 'rm -rf /' in command:
            return {
                'hookSpecificOutput': {
                    'hookEventName': 'PreToolUse',
                    'permissionDecision': 'deny',
                    'permissionDecisionReason': 'Dangerous command blocked'
                }
            }
    return {}

async def log_tool_use(
    input_data: dict[str, Any],
    tool_use_id: str | None,
    context: HookContext
) -> dict[str, Any]:
    """Log all tool usage for auditing."""
    print(f"Tool used: {input_data.get('tool_name')}")
    return {}

options = ClaudeAgentOptions(
    hooks={
        'PreToolUse': [
            HookMatcher(matcher='Bash', hooks=[validate_bash_command]),
            HookMatcher(hooks=[log_tool_use])  # Applies to all tools
        ],
        'PostToolUse': [
            HookMatcher(hooks=[log_tool_use])
        ]
    }
)

async for message in query(
    prompt="Analyze this codebase",
    options=options
):
    print(message)

Tool Input/Output Types

Documentation of input/output schemas for all built-in Claude Code tools. While the Python SDK doesn't export these as types, they represent the structure of tool inputs and outputs in messages.

Task

Tool name: Task

Input:

{
    "description": str,      # A short (3-5 word) description of the task
    "prompt": str,           # The task for the agent to perform
    "subagent_type": str     # The type of specialized agent to use
}

Output:

{
    "result": str,                    # Final result from the subagent
    "usage": dict | None,             # Token usage statistics
    "total_cost_usd": float | None,  # Total cost in USD
    "duration_ms": int | None         # Execution duration in milliseconds
}

Bash

Tool name: Bash

Input:

{
    "command": str,                  # The command to execute
    "timeout": int | None,           # Optional timeout in milliseconds (max 600000)
    "description": str | None,       # Clear, concise description (5-10 words)
    "run_in_background": bool | None # Set to true to run in background
}

Output:

{
    "output": str,              # Combined stdout and stderr output
    "exitCode": int,            # Exit code of the command
    "killed": bool | None,      # Whether command was killed due to timeout
    "shellId": str | None       # Shell ID for background processes
}

Edit

Tool name: Edit

Input:

{
    "file_path": str,           # The absolute path to the file to modify
    "old_string": str,          # The text to replace
    "new_string": str,          # The text to replace it with
    "replace_all": bool | None  # Replace all occurrences (default False)
}

Output:

{
    "message": str,      # Confirmation message
    "replacements": int, # Number of replacements made
    "file_path": str     # File path that was edited
}

Read

Tool name: Read

Input:

{
    "file_path": str,       # The absolute path to the file to read
    "offset": int | None,   # The line number to start reading from
    "limit": int | None     # The number of lines to read
}

Output (Text files):

{
    "content": str,         # File contents with line numbers
    "total_lines": int,     # Total number of lines in file
    "lines_returned": int   # Lines actually returned
}

Output (Images):

{
    "image": str,       # Base64 encoded image data
    "mime_type": str,   # Image MIME type
    "file_size": int    # File size in bytes
}

Write

Tool name: Write

Input:

{
    "file_path": str,  # The absolute path to the file to write
    "content": str     # The content to write to the file
}

Output:

{
    "message": str,        # Success message
    "bytes_written": int,  # Number of bytes written
    "file_path": str       # File path that was written
}

Glob

Tool name: Glob

Input:

{
    "pattern": str,       # The glob pattern to match files against
    "path": str | None    # The directory to search in (defaults to cwd)
}

Output:

{
    "matches": list[str],  # Array of matching file paths
    "count": int,          # Number of matches found
    "search_path": str     # Search directory used
}

Grep

Tool name: Grep

Input:

{
    "pattern": str,                    # The regular expression pattern
    "path": str | None,                # File or directory to search in
    "glob": str | None,                # Glob pattern to filter files
    "type": str | None,                # File type to search
    "output_mode": str | None,         # "content", "files_with_matches", or "count"
    "-i": bool | None,                 # Case insensitive search
    "-n": bool | None,                 # Show line numbers
    "-B": int | None,                  # Lines to show before each match
    "-A": int | None,                  # Lines to show after each match
    "-C": int | None,                  # Lines to show before and after
    "head_limit": int | None,          # Limit output to first N lines/entries
    "multiline": bool | None           # Enable multiline mode
}

Output (content mode):

{
    "matches": [
        {
            "file": str,
            "line_number": int | None,
            "line": str,
            "before_context": list[str] | None,
            "after_context": list[str] | None
        }
    ],
    "total_matches": int
}

Output (files_with_matches mode):

{
    "files": list[str],  # Files containing matches
    "count": int         # Number of files with matches
}

NotebookEdit

Tool name: NotebookEdit

Input:

{
    "notebook_path": str,                     # Absolute path to the Jupyter notebook
    "cell_id": str | None,                    # The ID of the cell to edit
    "new_source": str,                        # The new source for the cell
    "cell_type": "code" | "markdown" | None,  # The type of the cell
    "edit_mode": "replace" | "insert" | "delete" | None  # Edit operation type
}

Output:

{
    "message": str,                              # Success message
    "edit_type": "replaced" | "inserted" | "deleted",  # Type of edit performed
    "cell_id": str | None,                       # Cell ID that was affected
    "total_cells": int                           # Total cells in notebook after edit
}

WebFetch

Tool name: WebFetch

Input:

{
    "url": str,     # The URL to fetch content from
    "prompt": str   # The prompt to run on the fetched content
}

Output:

{
    "response": str,           # AI model's response to the prompt
    "url": str,                # URL that was fetched
  

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