Examples

Start with the result you need: build something useful, prepare a launch, improve an existing project, or connect your tools. These recipes cover agents, the downloadable terminal client, model APIs, and managed applications. Each recipe stays focused on one outcome.

Recipes explain the goal, what you need first, the steps or commands, the result you should see, and what to check when it does not work. Source links connect the walkthroughs to the relevant product and reference pages.

Build, launch, and improve your project

• Finish your first project task — turn an idea, repair, or research question into one deliverable you can inspect.
• Download the terminal client — work with agents from your terminal using your account's configured access.
• Build, launch, and grow one project — continue from a working app through users, payments, tests, web delivery, mobile-store preparation, marketing, and maintenance. The USD 200 budget draft is an optional example.

Pipeline applications

Use this learning track to understand and review a managed pipeline application:

1. Pipeline application walkthrough — inspect one pipeline TOML and Rust transform together with the customer/Redgold ownership boundary.
2. Managed application artifacts — understand the schema, manifest, transform, tests, and contract reviewed in Git.
3. Validate a pipeline application change — check schema evolution, manifest lowering, transforms, and the public contract in one reviewable change.
4. Build a vertical — see how Redgold connects ingestion, datasets, transforms, routes, and deployment into the application repository.
5. Verify a managed application deployment — match the approved application version to a healthy environment and run a bounded owner-scoped smoke request.

Pipeline-app routes are managed-preview routes. The generated V1 route inventory is the authority for self-service public routes; it currently lists the model API routes only. Redgold coordinates application creation, dataset provisioning, route review, publication, and environment deployment directly during the preview.

Model API

• Create an API key and make your first call — mint a key, set it in your environment, and confirm it against the model list.
• Call the model API from Python — drive /v1/chat/completions with the OpenAI SDK.
• Use the Anthropic Messages API — point the Anthropic SDK at the same endpoint with a bearer token.
• Check your model-API credit balance — read /v1/credits before a long run.
• Retry model API calls under rate limits — handle 429, 402, and 502 the way the API expects.

Your data and agents

• Connect an MCP client and query your data — attach Claude Code (or any MCP client) and run read-only SQL against a dataset you own.
• Run a pipeline from an MCP client — prepare a bounded plan, accept its quote and inspect durable results.
• Connect the hosted MCP server — discover and invoke API operations from your agent using your account key.
• Delegate a task to another agent — choose the customer REST or authorized managed agent-cli path for a bounded subtask.

Repositories and pipeline applications

• Set up managed reviews and project memory — agree a paid pilot, configure review depth and spending limits, and inspect retained project context.
• Connect GitHub review automation — prepare an onboarded repository for App-based reviewer and fixer workflows.
• Validate a pipeline application change — check schema, manifest, transform, tests, and generated references together.
• Walk through the tickets API — exercise a complete owner-scoped application's lifecycle.
• Verify a managed application deployment — match a deployed version to its repository change and smoke result.

Terminal client

• Install the terminal client — install redgold and rac with one command and confirm the client picked up your key.
• Point the terminal client at another API host — connect the client to a self-hosted instance.
• Run a one-shot agent task in CI — drive a single task to completion with an exit code you can gate on.