continuous-learning-v2

Continuous Learning v2.1 - 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.

When to Activate

• Setting up automatic learning from Claude Code sessions
• Configuring instinct-based behavior extraction via hooks
• Tuning confidence thresholds for learned behaviors
• Reviewing, exporting, or importing instinct libraries
• Evolving instincts into full skills, commands, or agents
• Managing project-scoped vs global 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"
scope: project
---

# 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

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
• Scope-aware -- project (default) or global

How It Works

Session Activity (in a git repo)
      |
      | Hooks capture prompts + tool use (100% reliable)
      | + detect project context (git remote / repo path)
      v
+---------------------------------------------+
|  observations.jsonl (per-project or global)  |
+---------------------------------------------+
      |
      | Observer agent reads (background, Haiku)
      v
+---------------------------------------------+
|          PATTERN DETECTION                   |
|   * User corrections -> instinct             |
|   * Error resolutions -> instinct            |
|   * Repeated workflows -> instinct           |
|   * Scope decision: project or global?       |
+---------------------------------------------+
      |
      | Creates/updates instincts
      v
+---------------------------------------------+
|  instincts/personal/ (project or global)     |
+---------------------------------------------+
      |
      | /evolve clusters + /promote
      v
+---------------------------------------------+
|  evolved/ (skills, commands, agents)         |
+---------------------------------------------+

Quick Start

1. Enable Observation Hooks

Add to your settings.json:

{
  "hooks": {
    "PreToolUse": [{
      "matcher": "*",
      "hooks": [{
        "type": "command",
        "command": "path/to/skills/continuous-learning-v2/hooks/observe.sh"
      }]
    }],
    "PostToolUse": [{
      "matcher": "*",
      "hooks": [{
        "type": "command",
        "command": "path/to/skills/continuous-learning-v2/hooks/observe.sh"
      }]
    }]
  }
}

2. Use the Instinct Commands

/instinct-status     # Show learned instincts (project + global)
/evolve              # Cluster related instincts into skills/commands
/instinct-export     # Export instincts to file
/instinct-import     # Import instincts from others
/promote             # Promote project instincts to global scope
/projects            # List all known projects and their instinct counts

Scope Decision Guide

Pattern Type	Scope	Examples
Language/framework conventions	project	"Use React hooks", "Follow Django REST patterns"
File structure preferences	project	"Tests in __tests__/", "Components in src/components/"
Code style	project	"Use functional style", "Prefer dataclasses"
Security practices	global	"Validate user input", "Sanitize SQL"
General best practices	global	"Write tests first", "Always handle errors"
Tool workflow preferences	global	"Grep before Edit", "Read before Write"
Git practices	global	"Conventional commits", "Small focused commits"

Confidence Scoring

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

Instinct Promotion (Project -> Global)

When the same instinct appears in multiple projects with high confidence, it's a candidate for promotion to global scope.

Auto-promotion criteria:

• Same instinct ID in 2+ projects
• Average confidence >= 0.8

Privacy

• Observations stay local on your machine
• Project-scoped instincts are isolated per project
• Only instincts (patterns) can be exported -- not raw observations
• No actual code or conversation content is shared
• You control what gets exported and promoted

---

Instinct-based learning: teaching Claude your patterns, one project at a time.