> ## Documentation Index > Fetch the complete documentation index at: https://docs.tracks.alpic.ai/llms.txt > Use this file to discover all available pages before exploring further. # Agents and models > The coding agents Tracks runs, the models each accepts, and the tools you can give them An agent is a coding agent program and the model it uses. You pick both for every run, and for every agent of an experiment. ## Agents | Agent | `harness` | What it is | Model provider | Offered first | | - | - | - | - | - | | Claude Code | `claude-code` | Anthropic's command-line coding agent. | Anthropic | `claude-sonnet-5-5` | | Claude Cowork | `claude-desktop` | The agent workspace of Anthropic's Claude desktop app, for documents, research and longer tasks. | Anthropic | `claude-sonnet-5-5` | | Codex | `codex` | OpenAI's command-line coding agent. | OpenAI | `gpt-5.5` | | Codex app | `codex-app` | The Codex mode of OpenAI's ChatGPT desktop app, with its own browser, computer-use and document tools. | OpenAI | `gpt-5.5` | | Cursor | `cursor` | Cursor's command-line coding agent. | Cursor | `auto` | The `harness` value is what you pass to `--harness` in the CLI, or to `agent.harness` in the API. "Offered first" is the model the web app picks for you; with the API, CLI and MCP server the model is always required. ```bash theme={null} tracks runs create "Explain how this app is deployed" \ --harness cursor --model auto \ --repository https://github.com/alpic-ai/apps-sdk-template ``` ## Models Each agent accepts the models of its provider that Tracks can price. **Claude Code, Claude Cowork** `claude-fable-5-1`, `claude-fable-5`, `claude-opus-5-5`, `claude-opus-5`, `claude-opus-4-8`, `claude-opus-4-7`, `claude-opus-4-6`, `claude-sonnet-5-5`, `claude-sonnet-5`, `claude-sonnet-4-6`, `claude-haiku-5-5`, `claude-haiku-4-5` **Codex, Codex app** `gpt-6.1-sol`, `gpt-6.1-terra`, `gpt-6-astra`, `gpt-6-sol`, `gpt-6-luna`, `gpt-5.6-sol`, `gpt-5.6-terra`, `gpt-5.6-luna`, `gpt-5.5`, `gpt-5.4`, `gpt-5.4-mini`, `gpt-5.4-nano` **Cursor** The models Cursor offers Tracks' account, read from Cursor and kept up to date. Use `auto` to let Cursor choose, or a Cursor model id. Ids can end in an effort level, such as `gpt-5.6-luna-low`, and in `-thinking` or `-fast`. These lists change as providers release models. The web app always shows the current ones in its model picker. A run asking for a model its agent can't use is refused, and the error lists the models it can use. A follow-up prompt can switch the model, never the agent: `tracks runs send-prompt "..." --model claude-opus-5-5`. ## Differences between agents * **Browser.** Claude Cowork and the Codex app always use their own browser and ignore the `browser` option. The other agents get a browser only when you ask for one. * **Cursor** runs its agent loop on Cursor's servers. Tracks learns what each step cost only once Cursor reports it, so a Cursor run can go over its budget by about the last 2 or 3 model calls. * **Skills** are installed in each agent's own skills folder, so every agent finds them the way it usually does. ## Agent tools Agent tools are what you give an agent on top of the repository. In an experiment, each variant picks its own set from your library; keep one with none as a baseline. | Tool | What the agent gets | | - | - | | **Skill** | Instructions, and the files they point to, that the agent loads when a task calls for them. A folder with a `SKILL.md` giving its name and description. | | **MCP server** | The tools of a server you name, called through Tracks. Its credentials never enter the sandbox. See [MCP servers](https://docs.tracks.alpic.ai/guides/mcp-servers.md). | | **Command-line tool** | A program installed in the sandbox by its install script, before your setup script runs. The agent runs it by its name. | | **Browser** | A headless Chromium the agent drives through tools. Pages can offer it their own tools through WebMCP. | > [!NOTE] > > A command-line tool is never announced to the agent: nothing in its prompt says the tool exists. The agent has to find > it on its own, as it would on a real machine. That is what makes it useful to measure whether agents discover your > CLI. Add skills, MCP servers and command-line tools to your organization's **Library** in the web app. To see whether agents actually used them, read [agent tool use](https://docs.tracks.alpic.ai/concepts/reading-results.md#agent-tool-use). This documentation is built and hosted on [Mintlify](https://mintlify.com), a developer documentation platform.