> ## Documentation Index
> Fetch the complete documentation index at: https://docs.agno.com/llms.txt
> Use this file to discover all available pages before exploring further.

# Build with Coding Agents

> Use Claude Code, Codex, or Cursor to set up, build, improve, evaluate, review, and deploy an AgentOS Starter.

Use Claude Code, Codex, or Cursor to set up, build, improve, evaluate, review, and deploy an AgentOS Starter.

The repository gives your coding agent the source code, a live MCP endpoint, evals, and runtime logs in one place. It can make a change, exercise it against the running platform, and bring back a verified result.

Everything on this page runs inside a cloned AgentOS Starter. If you don't have one running yet, [pick a Starter](/deploy/introduction) first.

## Skills

Each AgentOS Starter stores its coding-agent workflows in `.agents/skills/`.

| Skill                 | Use it when                                                                   |
| --------------------- | ----------------------------------------------------------------------------- |
| `/setup-platform`     | Bring up a fresh clone, verify the platform, and build the first agent        |
| `/create-agent`       | Turn an idea into a registered agent and smoke-test it live                   |
| `/extend-agent`       | Add a tool, capability, instruction change, or targeted fix                   |
| `/improve-agent`      | Derive probes from an agent's instructions and harden its behavior            |
| `/create-evals`       | Add eval coverage for an agent from its behavior and real sessions            |
| `/eval-and-improve`   | Diagnose failing evals and repair the affected behavior                       |
| `/review-and-improve` | Check code, documentation, configuration, and registered components for drift |
| `/deploy-platform`    | Deploy with the template's provider workflow and verify the live platform     |

The setup prompt invokes the `setup-platform` skill from `.agents/skills/`. Claude Code also discovers the skills through the Starter's committed `.claude/skills` symlink. Codex and Cursor can link to the same `.agents/skills/` directory.

## Connect the live platform

Connect the local AgentOS to the supported clients on your machine:

```bash theme={null}
uvx agno connect
```

The command registers AgentOS with detected Claude Code, Claude Desktop, Codex, and Cursor clients. Your coding agent can then call `run_agent`, `run_team`, and `run_workflow` while it works on the repository.

For a deployed platform:

```bash theme={null}
uvx agno connect --url https://<your-domain>
```

See [Connect Your Clients](/cli/connect) for authentication modes and client-specific setup.

## Keep behavior stable with evals

Use the bundled eval suite to check response quality and tool calls as you change instructions, tools, and models. The evals run on the host machine, so set up the virtual environment once:

```bash theme={null}
./scripts/venv_setup.sh
source .venv/bin/activate
```

Then run:

```bash theme={null}
python -m evals --tag smoke      # fast checks of the platform agents
python -m evals --tag release    # broader pre-release confidence
python -m evals --name <case>    # one case while iterating
python -m evals -v               # stream the full run with rich panels
```

Cases wrap [AgentAsJudgeEval](/evals/agent-as-judge/overview) (LLM judge, binary pass/fail) and [ReliabilityEval](/evals/reliability/overview) (tool-call assertions). Results log to Postgres, so run history shows up at [os.agno.com](https://os.agno.com) next to sessions and traces.

If a case fails, run `/eval-and-improve`.

## Agent patterns

The bundled agents demonstrate three patterns to copy:

| Pattern          | Example                      | When to use                                                                                     |
| ---------------- | ---------------------------- | ----------------------------------------------------------------------------------------------- |
| Direct tools     | `agents/web_search.py`       | The agent needs fine-grained control over each tool call.                                       |
| Context provider | `agents/platform_manager.py` | You want many tools collapsed into one `query_<thing>` interface that hands off to a sub-agent. |
| Studio builder   | `agents/agent_builder.py`    | Users create and refine components from chat; deletes keep a confirmation gate.                 |

## Scheduled tasks

The scheduler is on by default. Two reference workflows are registered out of the box:

| Workflow         | What it does                                                                                      | Default                                       |
| ---------------- | ------------------------------------------------------------------------------------------------- | --------------------------------------------- |
| Deployment check | Daily readiness report: database, auth, scheduler, MCP, Slack config. Fixed checks, no LLM calls. | On. Disable with `ENABLE_DEPLOY_CHECK=False`. |
| Run evals        | Daily smoke-tag eval run. Uses model calls.                                                       | Off. Enable it from the AgentOS UI.           |

See [Scheduler](/agent-os/scheduler/overview) for the cron API.

## Next steps

| Task                   | Guide                                     |
| ---------------------- | ----------------------------------------- |
| Choose a Starter       | [AgentOS Templates](/deploy/introduction) |
| Connect coding clients | [Connect Your Clients](/cli/connect)      |
| Add or customize evals | [Evals](/evals/overview)                  |