How do I install the Lev Learn skill?

Run npx skillmds@latest add lev-os/lev-learn in your terminal (requires Node.js), paste this page's agent-chat prompt into Claude, Cursor, or any MCP-connected agent, or download the SKILL.md file and copy it into your agent's skills directory.

What does the Lev Learn skill do?

[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 ", "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. It is listed under Coding & Dev Tools on SkillMD.

Is Lev Learn safe to use?

This skill has not completed SkillMD's automated safety review yet. SkillMD never runs a skill's scripts for you; review the SKILL.md before installing.

Which AI agents work with Lev Learn?

This skill is tagged as working with Claude Code, Claude.ai, OpenAI Codex. SKILL.md is an open format, so most agents that read a skills directory can load it too.

Is Lev Learn free to use?

Yes. Installing skills from SkillMD is free, and the skill stays under its author's original license.

Who published Lev Learn?

lev-os (@lev-os) published this skill. Their other Agent Skills are listed on their SkillMD profile.

Lev Learn by lev-os — Agent Skill

Name: Lev Learn
Author: lev-os

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.

lev-os 6cbc053 2.8 KB Updated Sep 17, 2026

File contents

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

Infer context when none is provided (git repo/workspace fallback).
Run interview loop one question at a time.
Create proposal-*.md in ${LEV_PM_PROPOSALS:-.lev/pm/proposals/}.
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.

---name: lev-learndescription: [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.---# Lev Learn: Guided Proposal IntakeUse 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 Contract1. 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 NotesThese 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 DefinitionYou 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.

Frequently asked questions