Jers documentation

Plain Markdown pages, the same ones /llms.txt lists for coding agents.

• Introduction Jers is a decision API with memory. Send a state and typed questions; get typed answers with probabilities and confidence that your code can branch on. Name a s
• Getting started in five minutes You need a running Jers gateway (port 8797 on the machine that runs it) and a key. Everything below was run for real; your numbers will differ a little.
• Quick start Jers listens on port 8797 of the machine that runs it. Three steps.
• Examples Every request on this page was sent to a Jers gateway on 2026-09-23 and every answer came back from it (`jers-english` unless the request names a model). The an
• Jers versus Jev Jev is TypeSafe AI's System One model, served at `api.typesafe.ai`. Jers is this API. The request and answer shape is the same on purpose, so code written for o
• State The state is what the engine evaluates: a support message, a document, an application record. It goes in the `state` field next to the questions.
• Primitives Three question types, one request. Each is evaluated on its own against the same state.
• Choice Select one option from a defined set. The answer has the chosen option, a probability for every option, and a confidence.
• Score Rate the state against ordered levels. The answer has a score, a probability per level, the legend, and a confidence.
• Noul A yes/no statement. The answer is the probability that the answer is yes, with a `confidence` that is the larger of it and 1 minus it.
• Confidence Choice and Score answers carry `probabilities`, the full distribution, and `confidence`, one number from 0 to 1 that says how concentrated that distribution is.
• Request options Options on `POST /v1/systemone` beyond `state`, `questions`, `model` and `subject`. Each says what it costs.
• Warnings Every answer carries `warnings`: known traps in this request, found by checks that cost nothing. The answer is returned either way; a warning says where it may
• Memory A memory is a list of lines that belongs to one subject of one tenant: facts, events your software reports, rules with conditions, decisions you choose to keep.
• Rules in memory The memory is read by a one-pass decision engine, not a reasoner. Measured while building the demos and cookbooks with the English checkpoint, four things decid
• Quality Jers tells you how often it is right on your own decisions, and tunes its confidence to them. Everything here works from labels: the right answer for a question
• Batches Many decisions as one background job: a backlog to classify, a nightly re-scoring, a golden set of your own.
• Patterns Code owns the control flow. Jers appears where the code needs a judgment. Four patterns from stateless decision APIs, then two that exist because of the memory.
• Cookbooks End-to-end recipes in `cookbooks/`, each a Python script that runs against your gateway with `JERS_API_KEY` set and prints what it measured. The outputs below a
• Models `GET /v1/models` lists what this gateway offers, whether each engine answers right now, and what is pinned.
• API reference Base URL: `http://<host>:8797`. Every `/v1` route except sign-up needs `Authorization: Bearer <key>`, and every POST `Content-Type: application/json`. Bodies ar
• Pricing Input is free. You pay per answer and per memory line written. This is the mirror image of TypeSafe's pricing for Jev (paid input tokens, free output): with Jer
• Python SDK `jers-sdk` 0.2 needs Python 3.10 or newer and nothing else; Pydantic is used only if you give it a Pydantic model.
• JavaScript and TypeScript `sdk/typescript` is a TypeScript client with no dependencies: it uses the `fetch` built into Node, Deno, Bun and browsers, and Node 22.18+ runs its source direc
• Claude and MCP Jers ships as an MCP server and a Claude Code plugin, so Claude can make typed decisions with memory as tool calls.
• Agent skill For Claude Code and other coding agents: the file `skills/jers/SKILL.md` in the checkout tells an agent what Jers is, when to use it inside the software it writ
• FAQ **Is Jers a chat model?** No. It never generates text. You send a state and typed questions; you get typed answers with probabilities. Use it inside software, f
• Troubleshooting Every error is JSON: `{"error": {"type": "...", "message": "..."}}`. The message says what to fix.
• Jaggedness What Jers gets wrong, as measured, so that you design around it rather than find out later. Measured on 2026-09-22 and 2026-09-23 with the Jers checkpoints on a