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typesafe-ai

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TypeSafe integration craft for System One models (sometimes called Decision Models) such as Jev, which answer typed questions about text, images, and application state with calibrated probabilities. Use when building, reviewing, or debugging code that calls TypeSafe; when writing its questions or state; when replacing an LLM prompt-and-parse step, keyword matching, or a brittle heuristic with a typed question; or when brainstorming where programmable common sense fits in an app.

skills/typesafe-ai/SKILL.md

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# Build with TypeSafe

TypeSafe's **Jev**, the first public **System One model**, answers typed questions about state your
application supplies. State is the text, images, and application data your code sends with a
request. Jev can answer a Choice among options, a Noul (the probability that a statement is true), a
Score on levels you describe, or a Box that locates something in an image. Each answer comes back as
typed data with calibrated probabilities, for your code to use.

The rest of this skill is guidance: patterns that tend to produce reliable integrations. None of it
is absolute. Models change, applications differ, and edge cases exist. When a situation calls for
something else, test the alternative and use your judgment.

## Judgments from Jev, decisions in code
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