grill-jev

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Broad Jev interrogation: generate up to 50 context-specific questions about a plan, spec, design, code artifact, or any topic — using all primitive shapes and structured forms to surface hidden problems before they ship.

AI & Automation 425 stars 46 forks Updated yesterday MIT

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Skill Content

# Grill-Jev Generate a context-specific Jev interrogation battery against a plan, spec, design, code artifact, or any topic. Questions are generated from the artifact itself — not from a static list — so they target the actual risks and gaps in what you provide. ## When to invoke - User says "grill this", "validate my plan", "find holes in my spec", "sanity check", "stress test this", "50 questions", "interrogate", "grill-jev" - **Automatically after any planning output.** When a plan, spec, or design is produced — before execution begins — pass it through grill-jev. Any structured output with phases, steps, or checklist items qualifies. - When the user says "does this look right", "approve this", "is this ready", "review my plan" ## How it works 1. **Read the artifact** — the plan, spec, design, or code being interrogated 2. **Generate questions** — the LLM executing this skill produces up to 50 context-specific Jev questions tailored to the artifact. It writes the JSON battery to a temporary file; no secondary model call or API key is used. Questions use all structured shapes: - Noul with `{true: {what, examples}, false: {what, examples}}` criteria - Choice with `{what, not_for, examples}` per option - Score with `{summary, signals}` per level - Noul with array `compare` instructions when two state paths need comparison 3. **Send to Jev** — evaluate the questions against the artifact as state. Use Vercel AI Gateway. Too much context is the most common failu...

Details

Author
notque
Repository
notque/vexjoy-agent
Created
6 months ago
Last Updated
yesterday
Language
Python
License
MIT

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