This release is a pre-release and may not be stable for production use.
agent-framework-tools
Beta built-in tools for the Microsoft Agent Framework. A home for first-party
Python tools that plug into any chat client's shell / function surface. The
first tool is LocalShellTool.
Installation
pip install agent-framework-tools --pre
LocalShellTool quick start
import asyncio
from agent_framework import Agent
from agent_framework.openai import OpenAIChatClient
from agent_framework.tools import LocalShellTool
async def main() -> None:
client = OpenAIChatClient(model="gpt-5.4-nano")
async with LocalShellTool() as shell:
agent = Agent(
client=client,
instructions="You are a helpful assistant that can run shell commands.",
tools=[client.get_shell_tool(func=shell.as_function())],
)
result = await agent.run("Print the current working directory.")
print(result.text)
asyncio.run(main())
Modes
- Persistent (default): a single long-lived shell session.
cd,export, and shell functions persist across tool invocations. - Stateless (
mode="stateless"): each command runs in a fresh subprocess.
Safety
LocalShellToolis not a sandbox. It runs commands directly on the host with the agent process's permissions. Human approval provides a check before agent-requested commands run, but does not isolate the shell. Production use needs separately enforced isolation and restricted permissions. For untrusted input use a sandboxed executor, such asDockerShellToolfor shell commands — see alsoagent-framework-hyperlight.
Defenses (in priority order):
- Approval-in-the-loop — when an agent calls the tool returned by
as_function()withapproval_mode="always_require"(the default), commands require approval through auser_input_requestbefore they run. Disabling this requiresacknowledge_unsafe=True. Direct calls torun()do not request approval, regardless of the configured approval mode. - Process-tree termination on timeout via
psutil, so child processes (make, watchers, network tools) cannot survive the timeout. On Windows, a timed-out persistent session is closed even if the interrupted command emits its completion marker. The next command starts a fresh shell; shell-local variables and working-directory changes from that session are lost. - Output truncation to 64 KiB (head + tail with marker).
- Audit hook (
on_command=…) for SIEM / append-only logs. - Optional command-pattern filter via
ShellPolicy(denylist=[...], allowlist=[...]). Empty by default. This is a UX pre-filter, not a security boundary — operators are expected to supply patterns that match their workload (and they can be defeated by trivial obfuscation such as\rm -rf /,${RM:=rm} -rf /,python -c "…", encoded payloads, or PowerShell-native equivalents). Isolation must be enforced separately, for example by the sandbox tier (DockerShellTool); neither approval nor command filters isolate the shell. Seetests/test_security.pyfor the documented residual risk surface.
Command-text filtering with ShellPolicy and required human approval:
from agent_framework.tools import LocalShellTool, ShellPolicy
shell = LocalShellTool(
policy=ShellPolicy(allowlist=[r"^ls\b", r"^cat\b", r"^git status$"]),
approval_mode="always_require",
)
Expose this tool to the agent through shell.as_function() and handle its
approval requests with human review. Calling shell.run() directly does not
request approval.
Cross-OS
- Windows:
pwsh -NoProfile -Command -(falls back topowershell.exe). - Linux / macOS:
/bin/bash --noprofile --norc(falls back to/bin/sh). - Override via the
shell=constructor argument or theAGENT_FRAMEWORK_SHELLenvironment variable.
ShellEnvironmentProvider — context provider
A model talking to a PowerShell session will sometimes default to bash
syntax (export FOO=bar, ls -la, > /dev/null) and vice versa.
ShellEnvironmentProvider is an AIContextProvider that probes the live
shell once per session — family, version, OS, working directory, and a
configurable list of CLI tools (git, node, python, docker by
default) — and injects a system-prompt block describing the shell idiom
to use and the available CLIs.
from agent_framework.tools import (
LocalShellTool,
ShellEnvironmentProvider,
ShellEnvironmentProviderOptions,
)
shell = LocalShellTool()
provider = ShellEnvironmentProvider(
shell,
ShellEnvironmentProviderOptions(probe_tools=("git", "uv", "node")),
)
agent = Agent(
client=client,
tools=[client.get_shell_tool(func=shell.as_function())],
context_providers=[provider],
)
Probe failures from expected error types (timeouts, policy rejections,
spawn failures) are recorded as None fields in the snapshot rather
than raised; a missing CLI never fails the agent. A failed first probe
does not poison the cache — the next call retries.
DockerShellTool — sandboxed tier
When commands originate from untrusted input (e.g. the model is acting on
prompt-injected document content), prefer DockerShellTool. With the
default isolation flags and a trusted container runtime, the container
is the intended security boundary and approval gating becomes optional.
import asyncio
from agent_framework.tools import DockerShellTool
async def main() -> None:
async with DockerShellTool(
image="mcr.microsoft.com/azurelinux/base/core:3.0",
approval_mode="never_require", # container is the boundary
) as shell:
result = await shell.run("uname -a && id")
print(result.stdout)
asyncio.run(main())
Defaults applied to every container:
--network none— no host or external network.--user 65534:65534— runs asnobody:nogroup.--read-onlyroot filesystem; only mounted host paths are writable.--cap-drop ALLand--security-opt no-new-privileges.--memory 512m,--pids-limit 256, ephemeraltmpfs /tmp.
To expose a host directory, pass host_workdir="/path" (mounted
read-only by default; mount_readonly=False to allow writes). Swap the
container runtime with docker_binary="podman".
Applications that must pass additional Docker options can use
unsafe_extra_run_args. These trusted setup options are appended verbatim
and must come only from developer-controlled configuration. Never use values
from users, model output, or other untrusted sources. These options can weaken
or completely remove isolation. Review every option carefully. In particular,
avoid --privileged, --network=host, host-path volume mounts, and added
capabilities unless the application explicitly requires and secures them.
Arbitrary Docker configuration is trusted application setup. The model-facing function accepts only a shell command and cannot choose Docker options, but the restrictive profile is effective only when the complete application configuration preserves it.
Sandbox tiers at a glance
| Use case | Tool | Sandbox |
|---|---|---|
| Run code (untrusted) | HyperlightCodeActProvider.execute_code (agent-framework-hyperlight) |
Hyperlight WASM microVM |
| Run shell (untrusted) | DockerShellTool |
OCI container (network-off, non-root, capabilities dropped) |
| Run shell (trusted dev) | LocalShellTool |
None; human approval for agent calls by default |
Relationship to agent-framework-hyperlight
agent-framework-hyperlight is a code sandbox (a single WASM guest
loaded into a microVM, called via a hostcall ABI — there is no kernel,
userland, or shell binary inside). It is the right tier for executing
generated code. For sandboxing shell commands, the realistic tier is
OCI, which DockerShellTool provides.
Metadata
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