Lev Learn: Guided Proposal Intake

Use this skill when the user wants a guided, question-by-question flow:

• learn
• learn <context>
• "guide me"
• "help me shape this"

Command

~/.agents/skills/lev-learn/bin/learn [context]

Behavior Contract

1. Infer context when none is provided (git repo/workspace fallback).
2. Run interview loop one question at a time.
3. Create proposal-*.md in ${LEV_PM_PROPOSALS:-.lev/pm/proposals/}.
4. Emit lifecycle handoff command back to work:
   • work --stage=crystallized "Create spec from <proposal>"

Agent Routing Notes

• If request includes learn, route to this skill first.
• After proposal creation, transition back to work for crystallized/spec flow.
• Do not skip prior-art checks; work owns those gates.

Status: v1.0.0

Technique Map

• Role definition - Clarifies operating scope and prevents ambiguous execution.
• Context enrichment - Captures required inputs before actions.
• Output structuring - Standardizes deliverables for consistent reuse.
• Step-by-step workflow - Reduces errors by making execution order explicit.
• Edge-case handling - Documents safe fallbacks when assumptions fail.

Technique Notes

These techniques improve reliability by making intent, inputs, outputs, and fallback paths explicit. Keep this section concise and additive so existing domain guidance remains primary.

Prompt Architect Overlay

Role Definition

You are the prompt-architect-enhanced specialist for lev-learn, responsible for deterministic execution of this skill's guidance while preserving existing workflow and constraints.

Input Contract

• Required: clear user intent and relevant context for this skill.
• Preferred: repository/project constraints, existing artifacts, and success criteria.
• If context is missing, ask focused questions before proceeding.

Output Contract

• Provide structured, actionable outputs aligned to this skill's existing format.
• Include assumptions and next steps when appropriate.
• Preserve compatibility with existing sections and related skills.

Edge Cases & Fallbacks

• If prerequisites are missing, provide a minimal safe path and request missing inputs.
• If scope is ambiguous, narrow to the highest-confidence sub-task.
• If a requested action conflicts with existing constraints, explain and offer compliant alternatives.