RPCS-1 Documentation

RPCS-1 measures a configured agent with five primitives — TI, SG, FT, UE, and AR — then tells you what runtime settings to change. If you want a fast start, use the interactive tuner or connect the public MCP server.

Start here

Every recommendation flows through the same three steps:

1. Describe the workload - task, entropy, predictability, stakes, context horizon, and commitment style.
2. Receive the diagnosis - the output leads with the five-primitive profile, failure-risk score, posture, and next test.
3. Ship the change - apply the runtime settings, then rerun one harder edge case.

All outputs are deterministic and research-grade until the assay battery has been validated on fresh, procedurally generated items.

Quick links

• Free tuner - run a sample workflow in under a minute
• Paid diagnostic - the written memo and sample preview
• Getting started - install the Python SDK
• MCP integration - connect the public read-only server
• Examples - support, coding, and research calls
• Translation layer - face-preserving posture
• Five primitives - TI, SG, FT, UE, AR
• Four regimes - stable, near oscillation, near overload, near freeze

AI agent integrations

RPCS-1 is available as a public, anonymous, read-only MCP server. It requires no API key or OAuth authentication. See the MCP integration guide for the endpoint, first call, and tool details.

• OpenAPI schema - REST tool contract
• llms.txt - machine-readable product overview

Try it now

The interactive tuner requires no installation and no account. Start from support, coding, or research and get recommendations in under a minute.