`fabricatio-tool`

Python Versions

Tool execution layer for Fabricatio — wraps Python callables as discoverable tools, lets LLMs generate orchestration code, and executes it with safety validation.

Installation

pip install fabricatio[tool]
# or
uv pip install fabricatio[tool]

For all Fabricatio packages:

pip install fabricatio[full]

Overview

fabricatio-tool enables Fabricatio agents to use arbitrary Python functions as tools. Tools are grouped into toolboxes, discovered by an LLM-driven selection process, composed into execution code (also LLM-generated), and run inside a ToolExecutor with import/call safety checks. Results are collected in a ResultCollector for downstream use.

The package also includes built-in filesystem tools, MCP (Model Context Protocol) client integration, and optional user-confirmation guards for destructive operations.

Core concepts

Concept	Description
`Tool`	A named, described callable with auto-extracted signature and briefing
`ToolBox`	A named collection of related `Tool` instances
`ToolExecutor`	Runs LLM-generated code that invokes tools; validates imports and calls
`ResultCollector`	Key-value container for tool execution results and errors
`Handle` / `HandleTask`	Mixin classes that wire tool discovery, code generation, and execution

Key classes and functions

`fabricatio_tool.models.tool`

Tool(source, name, description) — wraps a callable with metadata. invoke(*args, **kwargs) calls through. .signature and .briefing are auto-generated.
ToolBox(name, description) — collects tools. add_tool(func) appends a tool; collect_tool() works as a decorator. get(name) looks up a tool by name. .briefing produces an LLM-friendly description.

`fabricatio_tool.models.collector`

ResultCollector — submit(key, val), revoke(key), take(key) for typed retrieval, error() for retrieving execution errors.
ApplicationError — captures exception type, message, traceback, and the generated source for retry.

`fabricatio_tool.models.executor`

ToolExecutor(candidates, data) — execute(source) runs tool-usage code asynchronously. inject_tools(cxt), inject_data(cxt), inject_collector(cxt) prepare the execution context. from_recipe(recipe, toolboxes) constructs an executor by selecting tools by name.

`fabricatio_tool.capabilities`

UseTool — LLM-driven selection: choose_toolboxes(request), choose_tools(request), gather_tools(request), gather_tools_fine_grind(request).
Handle — draft_tool_usage_code(request, tools, data) generates Python code via LLM. handle(request, data) and handle_fine_grind(request, data) run the full pipeline.
HandleTask — extends Handle with handle_task(task, data) for Fabricatio Task objects.

`fabricatio_tool.fs`

Filesystem utilities callable as tools:

Function	Description
`dump_text(path, text)`	Write text to a file
`copy_file(src, dst)`	Copy a file
`move_file(src, dst)`	Move/rename a file
`delete_file(path)`	Delete a file
`create_directory(path)`	Create a directory
`delete_directory(path)`	Recursively delete a directory
`absolute_path(path)`	Resolve to absolute POSIX path
`gather_files(directory, ext)`	Glob for files by extension
`safe_text_read(path)`	Read file as UTF-8 text
`safe_json_read(path)`	Read and parse JSON file
`treeview(path, max_depth)`	Render a directory tree (Rust)

`fabricatio_tool.mcp`

get_global_mcp_manager(conf) — singleton MCP manager (Rust-backed).
mcp_tool_to_function(client_id, tool_name) — converts an MCP tool to an async callable.
mcp_to_toolbox(client_id) — converts all tools from an MCP client into a ToolBox.

`fabricatio_tool.decorators`

confirm_to_execute(func) — wraps a function with an interactive confirmation prompt via questionary.

`fabricatio_tool.toolboxes`

fs_toolbox — pre-built ToolBox containing all filesystem tools listed above.

Configuration

All options below are read through the fabricatio configuration chain (see the Configuration Guide at ../../docs/source/configuration.rst). Set them under the [ext.tool] table in fabricatio.toml, equivalently under [tool.fabricatio.ext.tool] in pyproject.toml, or via FABRICATIO_EXT__TOOL__<FIELD_UPPER> environment variables.

# fabricatio.toml
[ext.tool]
draft_tool_usage_code_template = "built-in/draft_tool_usage_code"
confirm_on_ops = true
logging_on_ops = true
error_key = "__error__"

Option	Type	Default	Description
`draft_tool_usage_code_template`	`str`	`"built-in/draft_tool_usage_code"`	The name of the draft tool usage code template which will be used to draft tool usage code.
`check_modules`	`CheckConfigModel`	`(see config.py)`	Modules that are forbidden/allowed to be imported.
`check_imports`	`CheckConfigModel`	`(see config.py)`	Imports that are forbidden/allowed to be used.
`check_calls`	`CheckConfigModel`	`(see config.py)`	Calls that are forbidden/allowed to be used.
`mcp_servers`	`Dict[str, ServiceConfig]`	`{}`	MCP servers that are allowed to be used.
`confirm_on_ops`	`bool`	`True`	Whether to confirm operations before executing them.
`logging_on_ops`	`bool`	`True`	Whether to log operations before executing them.
`error_key`	`str`	`"__error__"`	The key to use for error reporting.

CheckConfigModel fields:

targets: Set[str] — set of strings to check; default set()
mode: Literal["whitelist", "blacklist"] — check mode; default "whitelist"

ServiceConfig fields:

type: Literal["stdio", "sse", "stream", "worker"] — transport protocol; default "stdio"
command: Optional[str] — execution command for stdio-type services
url: Optional[str] — endpoint URL for SSE/stream/worker-type services
args: List[str] — command-line arguments for stdio services
env: Dict[str, JsonValue] — environment variables for the service process

Access at runtime: from fabricatio_tool.config import tool_config.

Usage example

from fabricatio_tool.models.tool import Tool, ToolBox
from fabricatio_tool.models.executor import ToolExecutor

# Define a tool
def add(a: int, b: int) -> int:
    """Add two integers."""
    return a + b

# Build a toolbox
box = ToolBox(name="math", description="Math operations")
box.add_tool(add, confirm=False, logging=True)

# Execute LLM-generated tool-usage code
executor = ToolExecutor(candidates=box.tools, data={})
source = """
async def execute(collector):
    result = await add(3, 4)
    collector.submit('sum', result)
"""
await executor.execute(source)
print(executor.collector.take('sum'))  # 7

With filesystem toolbox

from fabricatio_tool.toolboxes import fs_toolbox

# Use the built-in filesystem tools
executor = ToolExecutor(candidates=fs_toolbox.tools, data={})
source = """
async def execute(collector):
    import pathlib
    await dump_text(pathlib.Path('example.txt'), 'Hello, Fabricatio!')
    content = await safe_text_read(pathlib.Path('example.txt'))
    collector.submit('content', content)
"""
await executor.execute(source)
print(executor.collector.take('content'))  # Hello, Fabricatio!

Using capability mixins

from fabricatio_tool.capabilities.handle import Handle

class MyAgent(Handle):
    ...

agent = MyAgent()
result = await agent.handle(
    "Find all Python files and count their total lines",
    data={"dir": "src/"},
    model="default",
)
if result and not result.error():
    print(result.take("output"))

Safety

ToolExecutor validates generated code against configurable whitelists or blacklists for modules, imports, and function calls. By default, only safe builtins (str, int, float, bool, dict, set, list, pathlib.Path, print, len) and math are permitted. Destructive tools can be gated behind confirm_to_execute, which prompts the user interactively.

Dependencies

fabricatio-core — core interfaces and utilities
pydantic>=2.11.7
questionary>=2.1.0

License

MIT — see LICENSE

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