Sandboxes

Outline of potential Tool Defintions for a Sandbox.

# Read a file from the sandbox
read(path: string): string

# Write a file in the sandbox
write(path: string, content: string): string

# Apply a patch/edit to an existing file
edit(path: string, diff: string): string

# Execute code and return stdout/stderr
exec(code: string): string

# Run a command/process in the sandbox
process(command: string, args: string[]): string

Sandboxes (What & Why)

A sandbox is an isolated execution environment where an LLM can safely run code or tools without access to the host system.

LLMs use sandboxes to:

Execute code securely
Prevent data leaks or system damage
Enforce resource limits (CPU, memory, time)
Run untrusted or user-generated instructions

In agentic systems, sandboxes enable safe autonomy:

The model can act, experiment, and fail — without breaking production.

Common sandbox examples:

Python execution environments
Containerized tool runners
WASM-based runtimes

No sandbox → no safe tool execution → no real agent behavior.

Sandboxes

Sandboxes (What & Why)

Further Reading