# System-1 Gateway

The System-1 Gateway gives Claude Code fast multiple-choice decisions from a small local engine, through
one MCP server with three stable tools. You pick the engine (Laya, Von, Liquid AI d1 through llama.cpp, any
Ollama chat model, a Hugging Face reranker through a small local server, a hosted Claude model, or one you add),
and Claude sees the same tools whichever one answers. Python 3.11 or later and the standard library
only; version 0.2.0, released 2026-10-20.

In Claude Code, three commands install it:

```
/plugin marketplace add TheMattHub/Sys1-AI-Gateway
/plugin install system1@system1-gateway
/system1:setup
```

After a restart Claude can ask it a judgement call. One `system1_decide` call and its answer, here from the
built-in `mock` provider (latencies set to 0):

```json
{"question": "Rerun the flaky pipeline or block the merge?",
 "options": ["rerun the pipeline", "block the merge"]}
```

```json
{"schema_version": "1", "request_id": "demo-1", "status": "decided",
 "decision": "rerun the pipeline", "confidence": 0.9,
 "rationale": "mock provider: always picks the first option", "provider": "mock",
 "probabilities": {"rerun the pipeline": 0.9, "block the merge": 0.09999999999999998},
 "calibrated": false, "latency_ms": 0,
 "attempts": [{"provider": "mock", "outcome": "ok", "latency_ms": 0, "detail": null}], "error": null}
```

Three things set it apart. It abstains instead of guessing: below the confidence threshold the answer is
`abstained` and Claude reasons it through itself. The threshold means something, because each engine's
probabilities are calibrated on labelled decisions. And the choice of engine rests on measurement: the
[naga decisions study](studies/naga-decisions.md) compares every engine we tried on frozen blind test sets.

<div class="pareto-chart" data-src="assets/engines.json"><noscript><img src="screenshots/hero.png" alt="Accuracy against median latency for the engines in the naga decisions study"></noscript></div>

<div class="grid cards" markdown>

-   **Claude Code user**

    ---

    Install it, pick an engine, make a first decision, then turn on model routing.

    [Your first decision](tutorial/first-decision.md), [Install an engine](how-to/engines.md) and
    [Turn on model routing](how-to/routing.md)

-   **Choosing a decision model**

    ---

    Speed against accuracy on real decisions, on one laptop GPU, with the caveats.

    [Which model for naga decisions](studies/naga-decisions.md) and [Providers](reference/providers.md)

-   **Contributor**

    ---

    Add an engine adapter: one file and one registry line; the tools stay the same.

    [Add a provider](how-to/add-provider.md) and
    [CONTRIBUTING.md](https://github.com/TheMattHub/Sys1-AI-Gateway/blob/main/CONTRIBUTING.md)

-   **AI agent**

    ---

    Read the site as plain text and validate against the published schema.

    [llms.txt](https://thematthub.github.io/Sys1-AI-Gateway/llms.txt),
    [llms-full.txt](https://thematthub.github.io/Sys1-AI-Gateway/llms-full.txt) and [Tools and schema](reference/tools.md)

</div>

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