# FAQ

> Answers to common questions about Raw, from what it is and which models it runs on to customizing, sharing and securing your own agent.

## About Raw

### Is Raw a coding agent or a framework?

Both. Out of the box, `raw config init` creates a coding agent that reads, edits and runs code. Underneath, Raw is a harness: the agent loop, context compaction, saved sessions, approvals, a terminal REPL, a local dashboard and the Agent Client Protocol. The tools, skills, hooks, prompts and policies are files you can change, so you can turn it into a different agent without writing that machinery yourself.

### What can I build with it?

Anything that is an agent working with tools in a loop. Common starting points are a coding agent that follows your team’s conventions, an operations agent limited to approved commands, and an internal assistant that reaches your systems through MCP without a shell. See [Design an effective agent](https://raw.tlelabs.com/docs/guides/design-an-agent/) for how to shape one.

### Is Raw free to use at work?

Yes. Raw is released under the MIT license, which allows commercial use and modification.

### Does Raw collect telemetry?

No. Raw connects to the model endpoints and MCP servers that you configure, and the dashboard is served from your own machine.

## Models

### Which models can I use?

Any model reachable through one of four wire methods: OpenAI-compatible Chat Completions, OpenAI Responses, Anthropic Messages and Google Generate Content. That covers OpenAI, Anthropic, Gemini, DeepSeek, OpenRouter, Ollama, llama.cpp and other compatible servers. See [Models and agents](https://raw.tlelabs.com/docs/guides/models-and-agents/).

### Does Raw work with small local models?

Yes, and it was built with them in mind. Each agent sends only the tools it selects, skills load on demand, and long sessions are compacted automatically once you declare the model’s context window. A small model still has limits: keep its agent lean, as described in [Design an effective agent](https://raw.tlelabs.com/docs/guides/design-an-agent/).

### Can different agents use different models?

Yes. Each agent names one model. You can run a local model for routine tasks and a hosted model for harder ones, each with its own tools and prompt.

## Customizing

### Should my system prompt be short?

Short enough to leave room for the work, long enough that the model does not have to guess. The prompt is sent on every step, so on a small context window every extra token is paid many times. But a prompt that leaves out your conventions or your definition of done costs more in wrong guesses and retries. Put occasional procedures in skills and enforce safety with rules. [Design an effective agent](https://raw.tlelabs.com/docs/guides/design-an-agent/#the-system-prompt) explains the trade-off with numbers.

### How do I change a built-in tool?

Open the tool in the dashboard Library and choose **Fork to local**, or copy it from the examples. The copy is yours to edit, including its description and schema. Select the copy in place of the built-in. See [Tools](https://raw.tlelabs.com/docs/extend/tools/#fork-a-shipped-tool).

### How do I add a tool of my own?

Write a folder with a `tool.json` manifest and an `index.mjs` entry, then select it on the agent. You can also connect an MCP server and select its tools. See [Tools](https://raw.tlelabs.com/docs/extend/tools/#write-a-local-tool) and [MCP](https://raw.tlelabs.com/docs/extend/mcp/).

### My model keeps calling a tool wrong. What should I change?

Simplify the tool’s arguments before you add instructions. Weaker models make more mistakes as a schema grows: nested objects, arrays of objects, many required fields and fields of several types are the usual causes. Prefer one action per call with flat fields, familiar names such as `path` or `command`, and one complete example in the description. See [Keep tool parameters simple](https://raw.tlelabs.com/docs/guides/design-an-agent/#keep-tool-parameters-simple).

### Why does my agent not use its skills?

An agent that selects skills must also select `builtin/list_skills` and `builtin/load_skill`. The model then decides from each skill’s description whether to load it, so the description should say when the skill applies. See [Skills](https://raw.tlelabs.com/docs/extend/skills/).

### Do I have to restart a session after changing an agent?

No. Changes to an agent, a tool or a skill apply from the next turn, including in a session that is already open.

## Sharing

### How do I share my agent with my team?

Export it as a `.rawpkg` package with its tools and skills. By default, export turns your variable values and paths into inputs that each recipient fills in, and your session history is never copied. See [Packages](https://raw.tlelabs.com/docs/extend/packages/).

### Can I use Raw from my editor?

Yes, from any editor or parent agent that speaks the Agent Client Protocol. Run `raw --acp --stdio`. See [ACP](https://raw.tlelabs.com/docs/extend/acp/).

### Can I run Raw in scripts?

Yes. `raw "task"` runs one task and exits. Redirected output stays plain, and the exit code tells a script whether the task completed. See the [CLI reference](https://raw.tlelabs.com/docs/reference/cli/).

## Safety and data

### Is Raw a sandbox?

No. Tools run with your operating system account’s permissions, and the working directory is not a boundary. Use tool rules to ask before or deny specific calls, and run untrusted work inside a container or a separate account. See [Permissions](https://raw.tlelabs.com/docs/guides/permissions/).

### Where are my sessions and settings stored?

The config is `~/.config/raw/config.json`, or under `$XDG_CONFIG_HOME` when it is set. Sessions are kept in a private database under `~/.local/state/raw/`, or under `$XDG_STATE_HOME`. On Windows, `~` is your user folder, so these are `%USERPROFILE%\.config\raw\` and `%USERPROFILE%\.local\state\raw\`. Sessions are removed after 30 days by default. See [Sessions](https://raw.tlelabs.com/docs/guides/sessions/).

### Which operating systems are supported?

Raw runs on macOS, Linux and Windows 10/11, and every change is tested on all three. It needs Node.js 22.13 or later. On Windows it runs natively, without WSL: install [Git for Windows](https://git-scm.com/download/win) for the `bash` tool, or use the `powershell` tool, which `raw config init` selects when Git Bash is missing. Managed background processes work on all three systems. See [Install Raw](https://raw.tlelabs.com/docs/start/installation/#windows).