Jev Fanout

What it does

When your agent uses it

• Parallel questions
• Compound commands
• One-call turn assessment
• The user runs /jev-fanout

Example prompts

• “/jev-fanout”

Requirements

• Node.js

Workflow steps

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

1. 1List the judgments the workflow might need, including speculative ones (category, compound, room, device, availability, action per device…
2. 2Put each in questions with complete instructions. Write the speculative premise into the question (If this is a light command, …)…
3. 3Mix choice, score, and noul in that one request. Pin jev-1.13.0 once thresholds are tuned; jev-latest moves.
4. 4In code, branch on the answers that apply; leave the rest unused.
5. 5Make a second HTTP call only when the next options or next state cannot be built yet.

What it can do on your machine

Read from SKILL.md and the folder at commit 77b65c6. 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:

  • npx

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

• Network

  Links to these hosts (documentation or services it may open):

  • docs.typesafe.ai

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

• Credentials

  Names no API keys, tokens, secrets or passwords.

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

Context cost

Jev Fanout loads about 603 tokens when it runs. Until then it costs about 66 tokens; SKILL.md has 187 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it

~66

When it runs · the whole SKILL.md, loaded when a task matches

~603

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

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 cobusgreyling/Jev at commit 77b65c6, republished under its MIT licence (© cobusgreyling). 187 words, ~603 tokens.

name

jev-fanout

description

Ask every independent TypeSafe Jev question in one POST /v1/systemone (speculative fan-out). Use for parallel questions, smart-home or compound commands, one-call turn assessment, or when the user runs /jev-fanout. Do not fire one HTTP call per question.

{
  "state": "I've been trying to connect Stripe for 3 days. I'm losing sales. Help ASAP.",
  "model": "jev-latest",
  "questions": {
    "department": {
      "type": "choice",
      "instructions": "Which team should handle this message?",
      "criteria": {
        "billing": "Payments, invoicing, refunds",
        "technical": "Bugs, outages, integrations",
        "other": "Neither fits"
      }
    },
    "frustration": {
      "type": "score",
      "instructions": "How frustrated does the author appear?",
      "criteria": ["Calm, just stating facts", "Frustrated but civil", "Very angry, strong language"]
    },
    "is_urgent": {
      "type": "noul",
      "instructions": "Does the message convey urgency or time-sensitivity?"
    }
  }
}

© cobusgreyling, 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 skills/jev-fanout of cobusgreyling/Jev.

Open the folder on GitHubat commit 77b65c6