home / skills / affaan-m / everything-claude-code / continuous-learning-v2

continuous-learning-v2 skill

/skills/continuous-learning-v2

This skill helps you evolve instinct-based insights from Claude Code sessions into actionable skills, commands, or agents with confidence-weighted learning.

npx playbooks add skill affaan-m/everything-claude-code --skill continuous-learning-v2

Review the files below or copy the command above to add this skill to your agents.

Files (7)
SKILL.md
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---
name: continuous-learning-v2
description: Instinct-based learning system that observes sessions via hooks, creates atomic instincts with confidence scoring, and evolves them into skills/commands/agents.
version: 2.0.0
---

# 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.

## 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

## 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:

```yaml
---
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`.

**If installed as a plugin** (recommended):

```json
{
  "hooks": {
    "PreToolUse": [{
      "matcher": "*",
      "hooks": [{
        "type": "command",
        "command": "${CLAUDE_PLUGIN_ROOT}/skills/continuous-learning-v2/hooks/observe.sh pre"
      }]
    }],
    "PostToolUse": [{
      "matcher": "*",
      "hooks": [{
        "type": "command",
        "command": "${CLAUDE_PLUGIN_ROOT}/skills/continuous-learning-v2/hooks/observe.sh post"
      }]
    }]
  }
}
```

**If installed manually** to `~/.claude/skills`:

```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

The Python CLI will create these automatically, but you can also create them manually:

```bash
mkdir -p ~/.claude/homunculus/{instincts/{personal,inherited},evolved/{agents,skills,commands}}
touch ~/.claude/homunculus/observations.jsonl
```

### 3. Use the Instinct Commands

```bash
/instinct-status     # Show learned instincts with confidence scores
/evolve              # Cluster related instincts into skills/commands
/instinct-export     # Export instincts for sharing
/instinct-import     # Import instincts from others
```

## 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`:

```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](https://skill-creator.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](https://skill-creator.app) - Generate instincts from repo history
- [Homunculus](https://github.com/humanplane/homunculus) - Inspiration for v2 architecture
- [The Longform Guide](https://x.com/affaanmustafa/status/2014040193557471352) - Continuous learning section

---

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

Overview

This skill implements an instinct-based continuous learning system that watches Claude Code sessions via deterministic hooks and converts observed patterns into atomic "instincts" with confidence scores. It stores observations locally, clusters repeated behaviors, and can evolve those instincts into reusable skills, commands, or agents. The design focuses on high-reliability observation, evidence-backed rules, and privacy by keeping raw data on-device.

How this skill works

Hooks capture every PreToolUse and PostToolUse event and append structured observations to a local JSONL store. A background observer agent reads those observations, detects patterns (user corrections, error resolutions, repeated workflows), and creates or updates atomic instincts that carry domain tags, evidence, and a confidence score. Instincts can be inspected, exported/imported, or clustered into higher-level evolved artifacts on demand.

When to use it

  • Automatically learn and codify recurring preferences from interactive sessions
  • Capture tool usage and user corrections deterministically for pattern detection
  • Tune confidence thresholds to control auto-application vs. suggestion behavior
  • Export or share distilled behavior rules without exposing raw session data
  • Evolve a set of related micro-behaviors into a formal skill, command, or agent

Best practices

  • Enable PreToolUse/PostToolUse hooks to guarantee comprehensive observation
  • Set a conservative min_confidence (e.g., 0.3) and higher auto_approve_threshold (e.g., 0.7)
  • Review new instincts regularly before trusting auto-applied behavior
  • Keep observations local and export only distilled instincts for sharing
  • Use domain tags (code-style, testing, workflow) to make clustering more reliable

Example use cases

  • Learn a developer's preference for functional patterns and suggest them in new fixes
  • Detect a recurring testing workflow and evolve it into a reusable testing skill
  • Auto-capture and reinforce preferred git or review practices across sessions
  • Turn repeated error-resolution steps into a command that automates the fix
  • Import a colleague's non-sensitive instincts to align team workflows

FAQ

Where are raw observations stored and is data shared?

Raw observations are stored locally (observations.jsonl) and are not shared; only compiled instincts can be exported.

How does confidence affect behavior?

Lower confidence is treated as a suggestion, higher confidence can be auto-approved; thresholds are configurable in the settings.