> ## Documentation Index
> Fetch the complete documentation index at: https://docs.langbot.app/llms.txt
> Use this file to discover all available pages before exploring further.
# LangBot v4.10.0: Agentic Sandbox & Skills — Letting Your Agent Work Like a Developer
> LangBot v4.10.0 brings a real sandbox (Box Runtime) and an on-demand Skills system to the built-in Agent. It can now run commands and edit files in an isolated environment, and pull in specialized know-how exactly when a task needs it.
This article is synchronized from the LangBot Blog. [Read the canonical version](https://langbot.app/en/blog/langbot-v4100-sandbox-skills).
Published 2026-06-04 · Author: LangBot Team
LangBot v4.10.0 is our biggest Agent update yet. It ships two features that point in the same direction — **letting the built-in Agent work like a real developer**:
1. **Sandbox**: the Agent now runs in a genuinely isolated environment where it can execute commands and work with files.
2. **Skills**: the Agent can load specialized know-how on demand, instead of cramming everything into its context.
Both capabilities were led by community contributor [@huanghuoguoguo](https://github.com/huanghuoguoguo). Let's dig in.
> **New to LangBot?** [LangBot](https://github.com/langbot-app/LangBot) is an open-source LLM bot platform (15k+ GitHub stars) that lets you deploy AI chatbots across **Discord, Telegram, WeChat (个人微信 / 企业微信), Slack, Lark (Feishu), DingTalk, QQ** and more — all from a single instance. It connects 20+ large language models (OpenAI GPT, Anthropic Claude, Google Gemini, DeepSeek, and others) to 13+ messaging platforms, with built-in Agent, RAG knowledge bases, MCP support, and a plugin ecosystem. You can self-host it with one Docker command or run it managed on [LangBot Cloud](https://space.langbot.app/cloud).
## 📦 Sandbox: a real workspace for your Agent
Until now, LangBot's built-in Agent could only call predefined tools. It couldn't "open a terminal and run a command," nor "write an intermediate result to a file and read it back later" — which is exactly what human developers do all day.
v4.10.0 introduces the new **Box Runtime**. It gives the Agent an isolated sandbox environment with six native tools built in:
| Tool | Purpose |
| ------- | ---------------------------- |
| `exec` | Run shell commands |
| `read` | Read file contents |
| `write` | Write files |
| `edit` | Make targeted edits to files |
| `glob` | Find files by pattern |
| `grep` | Search inside file contents |
With this toolkit, the Agent can work like a developer: run a script, save the output to a file, read it back to analyze, and post-process the result. All of it happens inside an isolated environment that never touches the host.
### Pluggable backends
The sandbox's execution backend is **pluggable**, and LangBot selects one automatically based on your deployment:
* **Docker**: spins up a dedicated `langbot_box` container that talks to the main process over WebSocket. Great for containerized deployments.
* **nsjail**: lightweight isolation based on Linux namespaces, no extra container needed. Great for bare-metal or single-container setups.
* **E2B**: cloud sandbox that runs execution in a remote isolated environment.
You don't have to pick manually — `box.enabled` is the master switch. Once on, LangBot probes for the most suitable backend and degrades gracefully if probing fails.
### It also hosts MCP Servers
Beyond native tools, the Box Runtime takes on another important job: **hosting stdio-mode MCP Servers**.
Previously, stdio-mode MCP Servers had to be spawned as subprocesses directly inside the main process — neither safe nor easy to manage. Now they all run inside the sandbox, sharing the same isolation boundary as the Agent's execution environment. `http` / `sse` mode MCP is unaffected and works as before.
## 🎯 Skills: know-how, loaded on demand
The second big update is **Skills**.
As the Agent's capabilities grow, an old problem surfaces: **the context window is finite**. If you stuff every possible instruction, procedure, and reference doc into the system prompt, the context fills up fast — and most of it is irrelevant to the task at hand.
The design idea behind Skills is simple: **keep the table of contents in view, and open the book only when you need it.**
A Skill is an **on-demand instruction pack** containing:
* **A prompt**: tells the Agent what the skill does and when to use it
* **A procedure**: the steps to accomplish a class of tasks
* **Scripts**: ready-to-run helper scripts
* **Reference files**: API docs, templates, examples, and so on
By default the Agent only sees a **list of available skills** (name + summary), which costs almost nothing in context. When it decides a task needs a particular skill, it pulls the full content just in time via the `activate` action.
The benefits are clear:
1. **Lean context**: irrelevant skill content never takes up the window.
2. **Extensible capabilities**: want to teach the Agent a new trick? Write a skill pack — no core code changes.
3. **Instant effect**: skills load dynamically during execution, no restart required.
If you've used Claude's Skills or a similar mechanism, this pattern will feel familiar — it decouples "what the Agent knows" from "what the Agent needs right now."
## 🧩 Shipped early across 4.9.x
These were planned for v4.10.0 but shipped early in the 4.9.x line:
* **Plugin Extension Pages**: plugins can render custom UI via iframe + a Page SDK ([@TyperBody](https://github.com/TyperBody), #2107)
* **Monitoring**: feedback linked to message IDs, plus feedback export ([@6mvp6](https://github.com/6mvp6), #2120)
* **Security hardening**: path-traversal fixes and removal of an authenticated RCE endpoint ([@sebastiondev](https://github.com/sebastiondev), #2087 / #2178)
## 🚀 Getting started
The sandbox needs an execution backend, depending on how you deploy:
* **Docker**: run `docker compose --profile all up`, which also launches the `langbot_box` container.
* **Manual / `uvx`**: runs as a stdio subprocess automatically, nothing to do.
* **LangBot Cloud**: ready out of the box — the sandbox is already set up for you, nothing to install.
To turn the sandbox off, set `box.enabled: false` — built-in tools, Skill create/edit, and stdio-mode MCP are all disabled; `http` / `sse` mode MCP is unaffected. See the [Sandbox docs](https://docs.langbot.app/en/usage/sandbox/readme) for details.
This release also upgrades the plugin SDK to **`langbot-plugin 0.4.1`**.
## Closing thoughts
Sandbox and Skills are, at their core, answering the same question: **how do we let an Agent handle genuinely complex, open-ended tasks?**
The sandbox solves the "**hands**" problem — giving the Agent the ability to execute and room to experiment. Skills solve the "**brain**" problem — letting the Agent reach for the right knowledge at the right moment, without drowning in irrelevant information.
The fastest way to try it is to spin up a managed instance on [LangBot Cloud](https://space.langbot.app/cloud), where the sandbox is ready to go. You can also read the [full release notes](https://github.com/langbot-app/LangBot/releases/tag/v4.10.0) for every change.
Thank you to everyone building with LangBot. We'll keep making the cloud Agent experience more stable and more capable.