lev-self
[WHAT] Self-improvement system transforming event streams into actionable system improvements [HOW] Analyze events.jsonl for patterns, generate proposals with confidence scores, human-approve, apply to skills/config/daemons [WHEN] Use when asking what lev can learn, proposing improvements, or conducting fail-forward root cause analysis [WHY] Enables proactive system evolution based on observed failures and patterns instead of reactive fixes Triggers: "what can lev learn", "propose improvements", "self-learn", "why did X fail", "improve lev", "fail-forward"
Informações da origem
- Repositório
- lev-os/agents
- Última atividade na origem
- 7 de março de 2026 às 00:14
- Idioma detectado do SKILL.md
- inglês
- Estrelas
- 21
- Forks
- 2
Opções de instalação
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Revise os arquivos de origem
Leia o SKILL.md e os arquivos complementares exibidos pelo SkillsMP antes de decidir se vai instalar.
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SKILL.md
Instruções da origem · Visualização somente leitura- name
- lev-self
- description
- [WHAT] Self-improvement system transforming event streams into actionable system improvements [HOW] Analyze events.jsonl for patterns, generate proposals with confidence scores, human-approve, apply to skills/config/daemons [WHEN] Use when asking what lev can learn, proposing improvements, or conducting fail-forward root cause analysis [WHY] Enables proactive system evolution based on observed failures and patterns instead of reactive fixes Triggers: "what can lev learn", "propose improvements", "self-learn", "why did X fail", "improve lev", "fail-forward"
- version
- 1.0.0
- storage
- {"events":"~/lev/.lev/events.jsonl","proposals":"~/.config/lev/proposals/","patterns":"~/.config/lev/patterns.jsonl"}
- lifecycle_integration
- {"stage":"all stages (meta-improvement)","input_artifact":"events.jsonl + patterns","output_artifact":"improvement-proposals.md"}
# Lev Self-Improvement
Transform event streams into actionable system improvements. Proactive learning (not just reactive fixes).
## Quick Reference
| Trigger | Action |
|---------|--------|
| "what can lev learn?" | Full analysis cycle |
| "propose improvements" | Generate proposals from patterns |
| "why did X fail?" | Root cause analysis (fail-forward) |
| "self-learn" | Automated improvement cycle |
## Architecture
```
events.jsonl → Analyze → Patterns → Proposals → Human Review → Apply
↑ │
└──────────── feedback loop ──────────────────┘
```
## Core Workflows
### 1. Event Analysis
```bash
lev learn analyze # Detect patterns in events.jsonl
lev learn analyze --since 24h # Last 24 hours only
```
See: `references/event-analysis.md`
### 2. Fail-Forward Protocol
When something fails, extract learning:
1. Capture: What happened? (exact error, context)
2. Root Cause: Why? (5 whys, dependencies)
3. Proposal: How to prevent? (skill patch, config change)
4. Confidence: How sure? (low/medium/high)
See: `references/fail-forward.md`
### 3. Proposal Workflow
```yaml
# ~/.config/lev/proposals/{id}.yaml
id: prop-abc123
type: skill-patch | config-change | new-workflow
target: ~/.claude/skills/lev/SKILL.md
confidence: 0.85
description: "Add timeout handling"
diff: |
+ timeout: 30s
status: pending | approved | rejected | applied
```
See: `references/proposals.md`
## Evolution Targets
| Target | Location | When |
|--------|----------|------|
| Skills | ~/.claude/skills/*/SKILL.md | Behavior improvements |
| Config | ~/lev/.lev/config.yaml | Settings optimization |
| Daemons | ~/.config/lev/daemons.yaml | Process tuning |
| Workflows | ~/lev/workflows/*.yaml | Pattern codification |
## Relationship to Other Skills
- **skill-evolver** (absorbed): Reactive skill fixes
- **lev** (sibling): Behavior definition (lev-self improves it)
- **bd** (integration): Track proposals as issues
## Storage Schema
```
~/.config/lev/
├── proposals/ # Pending proposals
│ └── {id}.yaml
├── memory/
│ ├── patterns.jsonl # Detected patterns
│ ├── proposals.jsonl # Proposal history
│ └── applied.jsonl # Applied changes + outcomes
└── patterns.jsonl # Active patterns for matching
```
## Confidence Thresholds
| Confidence | Action |
|------------|--------|
| ≥90% | Auto-apply (after notification) |
| 70-89% | Propose with recommendation |
| 50-69% | Propose, request review |
| <50% | Log only, don't propose |
See: `references/tracking-schema.md`
## CLI Quick Reference
```bash
# Analysis
lev learn analyze # Full event analysis
lev learn patterns # Show detected patterns
# Proposals
lev learn propose # Generate proposals from patterns
lev learn review # Interactive proposal review
lev learn apply <id> # Apply approved proposal
# Tracking
lev learn status # Show pending proposals
lev learn history # Show applied changes
```
## Human-in-the-Loop
**All changes require confirmation:**
1. Proposal generated → notification
2. Human reviews diff
3. Approve/reject/modify
4. Applied changes logged with outcome
**Rollback:**
```bash
lev learn rollback <id> # Revert applied proposal
```
---
*For detailed schemas and protocols, see references/*
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