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lean-jev-usage

Explain what the `lean-jev` plugin does and how to use it. Use when someone invokes `/lean-jev-usage`, asks what this plugin covers, or wants to know how to hand a judgment call to Jev and how to add a recipe for a recurring one.

Quellinformationen

Repository
leancodepl/ai-plugins
Letzte Quellaktivität
23. September 2026 um 10:12
Erkannte Sprache von SKILL.md
Englisch
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2
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0

Installationsoptionen

Standardmäßig ist der Prompt ausgewählt, der zuerst die Quelle prüft. Sie können zu einem direkten Befehl wechseln oder eine lokale Kopie herunterladen.

Quelldateien prüfen

Lesen Sie SKILL.md und alle von SkillsMP angezeigten Begleitdateien, bevor Sie sich für eine Installation entscheiden.

SKILL.md wird angezeigt

SKILL.md
Quellanweisungen · Schreibgeschützte Vorschau
name
lean-jev-usage
description
Explain what the `lean-jev` plugin does and how to use it. Use when someone invokes `/lean-jev-usage`, asks what this plugin covers, or wants to know how to hand a judgment call to Jev and how to add a recipe for a recurring one.
# lean-jev One skill, one job: when a task turns on a judgment rather than on writing something, hand that judgment to a model built for judgments — and frame it the way that model needs it framed. ## What it gives you `/lean-jev:ask-jev`, or simply asking to have Jev score something, routes a decision to Jev, TypeSafe's System One model, through `scripts/jev.py`. What comes back is typed: a probability for a yes/no, a position on a rubric you wrote, a pick from a fixed set with the distribution behind it. Numbers only, 70–500 ms, a fraction of a cent. The framing is the work. Jev reads a question literally, answers each one in isolation, and explains nothing, so a question that bundles two factors returns a confident number about neither. The skill holds the rules that keep a question answerable — one factor per question, the right type for the job, state cut down to what the question needs, every number reported next to the question that produced it. ## Ad-hoc questions and recipes **Ad-hoc** covers the one-off: score these candidates, rate each of these tests, does this clear the bar. The general guidelines are enough — the skill picks the type, splits what needs splitting, and batches the lot into a single call. **Recipes** are for questions that keep coming back. A recipe is a written decomposition of one high-level question into Jev-shaped sub-questions, with the criteria spelled out and an honest note on what it leaves unanswered. The plugin ships one, `references/evaluating-a-test.md`, for judging whether a test is worth its lines. `references/writing-a-recipe.md` covers adding your own, including the honesty rules that keep a recipe from promising more than it measures. Recipes are where our own vocabulary accumulates: what "severe" means here, what counts as worth raising, which house pattern a file is being held to. ## Why hand the judgment over at all Three properties the agent's own read lacks: - **No drift down a list.** Every question in a call is evaluated independently and in parallel, so item 40 gets the same attention as item 1. - **No stake in the work.** An agent judging code it wrote an hour ago is a compromised reviewer. - **Consistency.** The same rubric means the same thing next week, which is what makes a threshold worth tuning. ## When to keep it Choosing between architectures or tools, anything needing several hops of reasoning or simulated consequences, arithmetic, counting, dates. That is System Two work — keep it in the agent, or in code. A single judgment with nothing at stake is also cheaper to just answer. ## Requirements The `evaluate` binary installed and a `TYPESAFE_API_KEY` exported; the plugin ships the launcher only. Whatever goes in `state` leaves the machine. Both are covered in the plugin `README.md`, and in `skills/ask-jev/references/setup.md` for when the tool turns out to be missing mid-session.
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