Common tasks
Use this page as the task index for the public documentation. The website, terminal client, existing agents, model API, pipeline applications and data tools share an account, with permissions and spending checked for each service.
| Task | Guide | Current access |
|---|---|---|
| Set up an account and use the hosted website | Quickstart | Check account access; request an invitation when signup is closed |
| Add tools to an existing agent | Setup prompt and skills | Account key; service permissions checked separately |
| Connect without local binaries | Hosted MCP | Account key and authorization for each declared API operation |
| Install the terminal client | Install the client | Available with an API key |
| Search the web and inspect sources | Search and browsers | Search/browser permissions and authorized spending |
| Recover decisions and conversation history | Memory and conversation search | Configured backends and accessible indexes |
| Run remote builds, checks and tests | Remote build setup | Project-specific builder, credential and budget |
| Import JSONL or Parquet and compare datasets | Data import | Existing declared schema and configured engine access |
| Finish a useful first project task | First-task walkthrough | Account and configured workspace |
| Carry one project from idea through launch and maintenance | Build, launch, and grow | Account; setup varies by stage |
| Add customer access rules and payments | Users and payments | App-specific implementation and payment account |
| Ship and verify a tested web release | Test and publish | Onboarded managed environment or connected hosting |
| Prepare an Android or iOS store release | Mobile distribution | Account connections and iOS signing available; submission pending |
| Reach customers and measure useful outcomes | Discovery and marketing | Campaign preparation; provider setup for paid delivery |
| Build or change a managed backend application | Pipeline application walkthrough | Managed preview |
| Give repository work to a persistent coding agent | Coding agents | Available |
| Organize application work across agents and sessions | Agent operations | Managed onboarding |
| Understand the managed request and delivery paths | Architecture | Public guide |
| Call hosted models from an existing application | First API call | Available with an API key |
| Use Redgold models from a coding client | Coding-client setup | Available with an API key |
| Query data owned by your workspace | Query application data | Preview onboarding |
Set up your account and clients
The quickstart covers the hosted website, repository access, API keys, the terminal client, and the first model-list request. Use the installation recipe when you need platform-specific terminal instructions and troubleshooting.
Add tools to your existing agent
Use the setup prompt to install redgold, rac,
rci and persistent skills, or connect MCP for remote API
discovery and calls. Keep your model provider and add the service you need:
search, managed browsing with residential routing and bounded CAPTCHA help,
memory, managed Kubernetes workspaces, or remote CI and testing.
The RAC command guide covers current search tiers, skill inventory, data import and diff, support, integrations and managed diagnostics. Each service still requires its corresponding access.
Build, launch, and grow a project
Start with one useful result: a working page, a repair, research, or a first application feature. Continue the same project with Build, launch, and grow. Its class-booking example develops into a product with customer access rules, payments, tested web delivery, and mobile-store preparation. The launch page, distribution work, and later fixes use the same product context.
The marketing stage covers search, communities, social content, existing customers, and partnerships. A USD 200 monthly budget draft is an optional worked example. Settings → Marketing connects Google Ads and sets monthly spend limits; paid delivery still uses your own advertising account. Follow the lifecycle guide's current availability notes when planning payment integrations and store submission.
Build and understand pipeline applications
A pipeline application is the main application-building model. Its reviewed contract consists of Rust schemas, a pipeline manifest, transforms, inline tests, and API routes. Redgold operates the edge, executor, data engine, storage, and deployment around that contract.
The walkthrough shows one complete managed application at an introductory level. The developer Pipeline apps section covers the deeper architecture, current runtime, portable application preview, and release lifecycle. The Applications section documents concrete products and case studies built on the platform.
Work with coding agents
Coding agents work in persistent repository checkouts with inspectable conversations, tool calls, and diffs. Fleet controls, budgets, live Stream sessions, pull-request review, and CI all belong to this path. Start with Coding agents for the product model and available access paths.
For ongoing work, follow workstreams and issues, agent lifecycle, and the application workstream example. These connect individual tasks to a verified managed deployment.
Agents can author changes to a pipeline application. Coding agents also work in repositories deployed elsewhere, and pipeline applications can be maintained directly through Git. The quickstart covers account and repository setup before the first task.
Use hosted models
Existing OpenAI and Anthropic clients can use https://api.redgold.ai/v1 with
an sk-rg- API key. Redgold provides the account's model list, authentication,
usage accounting, and provider routing. Follow the first API call
recipe, configure a supported coding
client, or use the model API
reference.
Access application data
Pipeline applications and agent activity write owner-scoped records to the platform data layer. Onboarded workspaces can run read-only queries over their datasets through the supported MCP query path. The pipeline application guides cover application schemas, transforms, and datasets. Dataset onboarding remains coordinated during the preview.