continuous-learning-v2
Continuous Learning v2 - Instinct-Based Architecture
An advanced learning system that turns your Claude Code sessions into reusable knowledge through atomic "instincts" - small learned behaviors with confidence scoring.
What's New in v2
| Feature | v1 | v2 |
|---|---|---|
| Observation | Stop hook (session end) | PreToolUse/PostToolUse (100% reliable) |
| Analysis | Main context | Background agent (Haiku) |
| Granularity | Full skills | Atomic "instincts" |
| Confidence | None | 0.3-0.9 weighted |
| Evolution | Direct to skill | Instincts → cluster → skill/command/agent |
| Sharing | None | Export/import instincts |
The Instinct Model
An instinct is a small learned behavior:
---
id: prefer-functional-style
trigger: "when writing new functions"
confidence: 0.7
domain: "code-style"
source: "session-observation"
---
# Prefer Functional Style
## Action
Use functional patterns over classes when appropriate.
## Evidence
- Observed 5 instances of functional pattern preference
- User corrected class-based approach to functional on 2025-01-15
Properties:
- Atomic — one trigger, one action
- Confidence-weighted — 0.3 = tentative, 0.9 = near certain
- Domain-tagged — code-style, testing, git, debugging, workflow, etc.
- Evidence-backed — tracks what observations created it
How It Works
Session Activity
│
│ Hooks capture prompts + tool use (100% reliable)
▼
┌─────────────────────────────────────────┐
│ observations.jsonl │
│ (prompts, tool calls, outcomes) │
└─────────────────────────────────────────┘
│
│ Observer agent reads (background, Haiku)
▼
┌─────────────────────────────────────────┐
│ PATTERN DETECTION │
│ • User corrections → instinct │
│ • Error resolutions → instinct │
│ • Repeated workflows → instinct │
└─────────────────────────────────────────┘
│
│ Creates/updates
▼
┌─────────────────────────────────────────┐
│ instincts/personal/ │
│ • prefer-functional.md (0.7) │
│ • always-test-first.md (0.9) │
│ • use-zod-validation.md (0.6) │
└─────────────────────────────────────────┘
│
│ /evolve clusters
▼
┌─────────────────────────────────────────┐
│ evolved/ │
│ • commands/new-feature.md │
│ • skills/testing-workflow.md │
│ • agents/refactor-specialist.md │
└─────────────────────────────────────────┘
Quick Start
1. Enable Observation Hooks
Add to your ~/.claude/settings.json:
{
"hooks": {
"PreToolUse": [{
"matcher": "*",
"hooks": [{
"type": "command",
"command": "~/.claude/skills/continuous-learning-v2/hooks/observe.sh pre"
}]
}],
"PostToolUse": [{
"matcher": "*",
"hooks": [{
"type": "command",
"command": "~/.claude/skills/continuous-learning-v2/hooks/observe.sh post"
}]
}]
}
}
2. Initialize Directory Structure
mkdir -p ~/.claude/homunculus/{instincts/{personal,inherited},evolved/{agents,skills,commands}}
touch ~/.claude/homunculus/observations.jsonl
3. Run the Observer Agent (Optional)
The observer can run in the background analyzing observations:
# Start background observer
~/.claude/skills/continuous-learning-v2/agents/start-observer.sh
Commands
| Command | Description |
|---|---|
/instinct-status |
Show all learned instincts with confidence |
/evolve |
Cluster related instincts into skills/commands |
/instinct-export |
Export instincts for sharing |
/instinct-import <file> |
Import instincts from others |
Configuration
Edit config.json:
{
"version": "2.0",
"observation": {
"enabled": true,
"store_path": "~/.claude/homunculus/observations.jsonl",
"max_file_size_mb": 10,
"archive_after_days": 7
},
"instincts": {
"personal_path": "~/.claude/homunculus/instincts/personal/",
"inherited_path": "~/.claude/homunculus/instincts/inherited/",
"min_confidence": 0.3,
"auto_approve_threshold": 0.7,
"confidence_decay_rate": 0.05
},
"observer": {
"enabled": true,
"model": "haiku",
"run_interval_minutes": 5,
"patterns_to_detect": [
"user_corrections",
"error_resolutions",
"repeated_workflows",
"tool_preferences"
]
},
"evolution": {
"cluster_threshold": 3,
"evolved_path": "~/.claude/homunculus/evolved/"
}
}
File Structure
~/.claude/homunculus/
├── identity.json # Your profile, technical level
├── observations.jsonl # Current session observations
├── observations.archive/ # Processed observations
├── instincts/
│ ├── personal/ # Auto-learned instincts
│ └── inherited/ # Imported from others
└── evolved/
├── agents/ # Generated specialist agents
├── skills/ # Generated skills
└── commands/ # Generated commands
Integration with Skill Creator
When you use the Skill Creator GitHub App, it now generates both:
- Traditional SKILL.md files (for backward compatibility)
- Instinct collections (for v2 learning system)
Instincts from repo analysis have source: "repo-analysis" and include the source repository URL.
Confidence Scoring
Confidence evolves over time:
| Score | Meaning | Behavior |
|---|---|---|
| 0.3 | Tentative | Suggested but not enforced |
| 0.5 | Moderate | Applied when relevant |
| 0.7 | Strong | Auto-approved for application |
| 0.9 | Near-certain | Core behavior |
Confidence increases when:
- Pattern is repeatedly observed
- User doesn't correct the suggested behavior
- Similar instincts from other sources agree
Confidence decreases when:
- User explicitly corrects the behavior
- Pattern isn't observed for extended periods
- Contradicting evidence appears
Why Hooks vs Skills for Observation?
"v1 relied on skills to observe. Skills are probabilistic—they fire ~50-80% of the time based on Claude's judgment."
Hooks fire 100% of the time, deterministically. This means:
- Every tool call is observed
- No patterns are missed
- Learning is comprehensive
Backward Compatibility
v2 is fully compatible with v1:
- Existing
~/.claude/skills/learned/skills still work - Stop hook still runs (but now also feeds into v2)
- Gradual migration path: run both in parallel
Privacy
- Observations stay local on your machine
- Only instincts (patterns) can be exported
- No actual code or conversation content is shared
- You control what gets exported
Related
- Skill Creator - Generate instincts from repo history
- Homunculus - Inspiration for v2 architecture
- The Longform Guide - Continuous learning section
Instinct-based learning: teaching Claude your patterns, one observation at a time.
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