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Agent skill

Jev Slalom

by autonomous-ai in autonomous-ai/openharness

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

MITAuto-check passed

Install Jev Slalom

skills CLI
$ npx skills add autonomous-ai/openharness --skill jev-slalom -a claude-code

Project install by default; add -g for ~/.claude/skills/.

GitHub CLI
$ gh skill install autonomous-ai/openharness jev-slalom --agent claude-code

Project scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).

Manual copy
$ git clone --depth 1 https://github.com/autonomous-ai/openharness.git skills-src && mkdir -p .claude/skills && cp -r skills-src/store/agents/jev-slalom/skills/slalom .claude/skills/jev-slalom && rm -rf skills-src

Use ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.

Claude Code skills documentation · loads skills from .claude/skills/

Facts

Skill name
jev-slalom
GitHub stars
1.2k
Token cost
~649 tokens
SKILL.md length
310 words
Files
1
Skills in repo
100
Repo updated
First seen
Licence
MIT

At a glance

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

  • Works in 3 steps: Update slalom.json (title, speed, gates,… → node "$JEV_DSH/toolchain/check.mjs"… → Watch the descent. Does Jev line up on…
  • SKILL.md covers The loop, Reading the run, Verifying a course and Driving Jev yourself
  • Calls node; needs TYPESAFE_API_KEY

What it does

Jev Slalom is an agent skill from autonomous-ai/openharness. Design and verify Jev's slalom courses in OpenHarness's viewer, where Jev is the racer steering to thread every gate.

Its SKILL.md is about 650 tokens, which your agent loads only when the skill is triggered. It is a single SKILL.md file with no bundled scripts.

The repository describes itself as: The ultimate harness for coding agents and beyond. All your agents. All your machines. One command center. Start with code, then follow your curiosity and build across… The licence is MIT.

Example prompts

  • “s slalom courses in OpenHarness”
  • “/jev-slalom”

Requirements

  • A credential in TYPESAFE_API_KEY

Workflow steps

3 steps, taken from the first numbered list in SKILL.md.

  1. Update slalom.json (title, speed, gates, valleyWidth, optional gateGap, a style line that tells Jev a line
  2. node "$JEV_DSH/toolchain/check.mjs" verifies the workspace's slalom.json is valid. Run it
  3. Watch the descent. Does Jev line up on the next gate, commit as it arrives, and thread a clean

What it can do on your machine

Read from SKILL.md and the folder at commit cc4983e. It shows what the files ask for, not the result of running them.

  • Tool permissions

    Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.

    From allowed-tools in the SKILL.md frontmatter.

  • Runs code

    Shell commands in SKILL.md call:

    • node

    From the folder's file list and the shell code blocks in SKILL.md.

  • Network

    No URLs in SKILL.md.

    From URLs in SKILL.md, links to its own repository left out.

  • Credentials

    Names these keys or tokens, usually read from environment variables:

    • TYPESAFE_API_KEY

    From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.

Context cost

Jev Slalom loads about 649 tokens when it runs. Until then it costs about 32 tokens; SKILL.md has 310 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~32
When it runs · the whole SKILL.md, loaded when a task matches
~649

Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.

Safety

Auto-check passed

The automated check found no risky patterns in SKILL.md.

Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); files beside SKILL.md are not scanned.

SKILL.md

The full file from autonomous-ai/openharness at commit cc4983e, republished under its MIT licence (© autonomous-ai). 310 words, ~649 tokens.

Download SKILL.mdSave it as .claude/skills/jev-slalom/SKILL.md (or your agent's skills folder).
name
jev-slalom
description
Design and verify Jev's slalom courses in OpenHarness's viewer, where Jev is the racer steering to thread every gate.

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.

© autonomous-ai, MIT. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file

Files

Just SKILL.md in store/agents/jev-slalom/skills/slalom of autonomous-ai/openharness.

Open the folder on GitHubat commit cc4983e

Compare with similar skills

Jev Slalom next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.

Jev Slalom compared with similar skills
SkillStarsUsed inTokensAuto-checkLicenceRepo updated
Jev Slalom this skillautonomous-ai/openharness1.2k—~649Automated safety check: PassMIT
Course Viewermadhvantyagi/Gnos339—~1.8kAutomated safety check: PassMIT
Developing PDF ViewerTriliumNext/Trilium38k—~1.8kAutomated safety check: PassAGPL-3.0
Jev Socialsickn33/agentic-awesome-skills47k1 repos~3.4kAutomated safety check: PassMIT
Jev Usesickn33/agentic-awesome-skills47k1 repos~2.5kAutomated safety check: PassMIT
Testing Course Samplesmicrosoft/ai-agents-for-beginners77k—~1.1kAutomated safety check: NotesMIT

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Questions about Jev Slalom

What does Jev Slalom do?

Design and verify Jev's slalom courses in OpenHarness's viewer, where Jev is the racer steering to thread every gate. Jev Slalom is an agent skill from autonomous-ai/openharness. Design and verify Jev's slalom courses in OpenHarness's viewer, where Jev is the racer steering to thread every gate.

How do I install Jev Slalom in Claude Code?

Run `npx skills add autonomous-ai/openharness --skill jev-slalom -a claude-code`. Or copy the skill folder (store/agents/jev-slalom/skills/slalom in autonomous-ai/openharness) into .claude/skills/jev-slalom in your project. Claude Code loads it when a task matches its description.

How do I install Jev Slalom in Codex?

Run `npx skills add autonomous-ai/openharness --skill jev-slalom -a codex`. Or copy the skill folder (store/agents/jev-slalom/skills/slalom in autonomous-ai/openharness) into .agents/skills/jev-slalom in your project. Codex loads it when a task matches its description.

Can I use Jev Slalom in Cursor, Gemini CLI or GitHub Copilot?

Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add autonomous-ai/openharness --skill jev-slalom -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/jev-slalom, .gemini/skills/jev-slalom, .github/skills/jev-slalom and .opencode/skills/jev-slalom in your project.

What does Jev Slalom need to run?

Going by SKILL.md and its folder, Jev Slalom needs the command-line tools its instructions call (node) and credentials named TYPESAFE_API_KEY. Our summary lists: A credential in TYPESAFE_API_KEY.

Does Jev Slalom access the network?

SKILL.md contains no URLs. Any network use would come from the scripts or tools the agent runs. This is read from the text; nothing was executed.

Is Jev Slalom safe to install?

Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. Review the folder before installing.

What licence does Jev Slalom use?

Jev Slalom is published under the MIT licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.

How many tokens does Jev Slalom use?

About 649 tokens (SKILL.md is roughly 2.6k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full.

What are the alternatives to Jev Slalom?

Skills that share tags, products or a category with Jev Slalom: Course Viewer (madhvantyagi/Gnos, 339 stars), Developing PDF Viewer (TriliumNext/Trilium, 38k stars), Jev Social (sickn33/agentic-awesome-skills, 47k stars) and Jev Use (sickn33/agentic-awesome-skills, 47k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Jev Slalom?

autonomous-ai (a GitHub organization) maintains it in autonomous-ai/openharness, which has 1,210 GitHub stars. The repository holds 100 skills in this directory. The repository was last updated on October 10, 2026.

Source: autonomous-ai/openharness on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.