AI and agents
Redgold provides managed coding-agent sessions, an HTTP model API and tools for agents running in an existing workflow. Agents can author pipeline applications or work in repositories deployed elsewhere. Search, browsers, memory and remote builds can be adopted individually with their corresponding permissions.
Tools for an existing agent
The setup guide connects an existing agent through
a prompt, hosted MCP or local CLI installation. rac supplies search, browser,
memory, data and build commands; rci implements its CI and publication
families. The command guide covers current usage and access.
Hosted MCP exposes declared API operations and data tools. Filesystem uploads, interactive terminals and local checkout operations still need the native client. Tool setup preserves the agent's model provider; configuring the model API below is a separate choice.
Coding agents
A coding agent runs in an isolated workspace associated with a repository and conversation. The workspace provides the filesystem and allowed tools. Session history lets users inspect messages and tool activity and continue work later.
Agents can delegate independent subtasks to additional agents when a problem benefits from parallel investigation. Each child has a bounded assignment, and its result returns to the parent conversation.
Model API and routing
The model API accepts supported OpenAI and Anthropic request formats at https://api.redgold.ai/v1. Callers authenticate with an account token or sk-rg- key. /v1/models reports the identifiers available to the current account.
Model routing handles platform authentication, metering, and backend selection. Provider errors and rate limits can still reach the caller; clients should honor Retry-After and use bounded exponential backoff where appropriate.
One-shot application benchmark
The platform's internal benchmark suite includes a paired one-shot full-application benchmark. Its habit-tracker task gives Codex, Claude, and the Redgold Fusion runtime the same prompt and verifier in fresh workspaces, with explicit time, step, token, and USD caps. Its companion report keeps pass@1, artifacts, and observed cost comparable without guessing a provider price; paid sweeps remain operator-authorized.
Persistence and replay
Persisted messages and tool events support review, search, and context reconstruction. A replay can differ when model weights, sampling, tools, external APIs, repository state, or datasets differ. Treat a run as reproducible only when those inputs are pinned.
Continue with the coding agents guide or LLM API reference.