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lev-learn

[WHAT] Guided learn-mode intake for ambiguous or early-stage work. [HOW] Runs a one-question-at-a-time interview, infers context when missing, writes a proposal artifact, then hands off to `work` for lifecycle continuation. [WHEN] Use for "learn", "learn <context>", "help me figure this out", or when the request needs structured context building before spec authoring. [WHY] Converts fuzzy intent into a concrete proposal without skipping lifecycle gates.

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Repository
lev-os/lev-content
Last source activity
February 13, 2026 at 18:54
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English
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SKILL.md
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name
lev-learn
description
[WHAT] Guided learn-mode intake for ambiguous or early-stage work. [HOW] Runs a one-question-at-a-time interview, infers context when missing, writes a proposal artifact, then hands off to `work` for lifecycle continuation. [WHEN] Use for "learn", "learn <context>", "help me figure this out", or when the request needs structured context building before spec authoring. [WHY] Converts fuzzy intent into a concrete proposal without skipping lifecycle gates.
version
1.0.0
skill_type
workflow
category
process-learn
extends
[]
related_skills
["work","lev-cdo","interview"]
tools
["~/.agents/skills/lev-learn/bin/learn"]
storage
{"proposals":".lev/pm/proposals/"}
# 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 ```bash ~/.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.
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