# Jev Slalom

> Design and verify Jev's slalom courses in OpenHarness's viewer, where Jev is the racer steering to thread every gate.

- Skill: `autonomous-ai/jev-slalom` (Agent Skill)
- Install (CLI): `npx skillmds@latest add autonomous-ai/jev-slalom`
- Raw SKILL.md: https://api.skillmd.com/api/skills/autonomous-ai/jev-slalom/raw
- Safety review: pending
- Works with: Claude Code, Claude.ai, OpenAI Codex
- Category: Coding & Dev Tools
- Author: autonomous-ai (https://skillmd.com/u/autonomous-ai)
- Updated: 2026-09-21
- Page: https://skillmd.com/skills/autonomous-ai/jev-slalom

---


# Jev Slalom course design

Jev Slalom runs a live course: a line of gates sweeps down a valley and Jev (TypeSafe's System One
model) reads its position and the next gate each tick and steers left/right to thread each gap. The
agent shapes `slalom.json`: the descent speed, the valley width, and how many gates.

## The loop

1. Update `slalom.json` (title, speed, gates, valleyWidth, optional gateGap, a `style` line that tells Jev a line
   strategy). The viewer watches it and Jev adapts live — no restart, no second server.
2. `node "$JEV_DSH/toolchain/check.mjs"` verifies the workspace's `slalom.json` is valid. Run it
   before you call a run done.
3. Watch the descent. Does Jev line up on the next gate, commit as it arrives, and thread a clean
   run — or never fall (dull) or fall even at calm speed (bad)? That observation is the finding.

## Reading the run

The viewer shows a top-down course: the skier descends with a snow trail, gates sweep toward it and
light up green as they're threaded, a dashed line marks the target gate, and a finished run shows a
CLEAN RUN or FELL banner plus a run log. Good courses produce a readable loop: Jev carves across the
valley to the next gate, threads it, and builds a rhythm; `speed` is the difficulty dial — crank it
up and Jev's aim wobbles and it clips a gate and falls.

## Verifying a course

`node "$JEV_DSH/toolchain/check.mjs"` returns non-zero when `slalom.json` is invalid (no title, a
non-positive speed, out-of-range gates/valleyWidth/gateGap/tickMs). It doesn't replace watching the run:
confirm Jev threads the gates at the speed you set, and that cranking `speed` up makes it visibly
fall.

## Driving Jev yourself

`toolchain/jev.mjs` exports a small client. Example (from the workspace) — ask Jev's read on a
gate before you commit to it:

```bash
node --input-type=module -e '
import { evaluate, jev } from "$JEV_DSH/toolchain/jev.mjs";
const res = await evaluate({
  state: "You are skiing the slalom. The skier descends at 3.0 rows/tick. Next gate: x 14.5, gap 6.0. skier x 9.0  gate x 14.5  gate in 1.2. Which way do you steer? LEFT_FAST / LEFT / HOLD / RIGHT / RIGHT_FAST",
  questions: {
    steer: jev.choice(["LEFT_FAST", "LEFT", "HOLD", "RIGHT", "RIGHT_FAST"], "Which way do you steer this tick?"),
  },
});
console.log(JSON.stringify(res.answers, null, 2));
'
```

Without `TYPESAFE_API_KEY` this uses the deterministic mock; set the key to hit live Jev.