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 v2.1
v2.1 adds project-scoped instincts — React patterns stay in your React project, Python conventions stay in your Python project, and universal patterns are shared globally.
| Feature | v2.0 | v2.1 |
|---|
| Storage | Global (~/.claude/homunculus/) | Project-scoped (projects/<hash>/) |
| Scope | All instincts apply everywhere | Project-scoped + global |
| Detection | None | git remote URL / repo path |
| Promotion | N/A | Project → global when seen in 2+ projects |
| Commands | 4 (status/evolve/export/import) | 6 (+promote/projects) |
| Cross-project | Contamination risk | Isolated by default |
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
- Promoting instincts from project to global scope
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
project_id: "a1b2c3d4e5f6"
project_name: "my-react-app"
---
# 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
- 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
+---------------------------------------------+
| projects/<project-hash>/observations.jsonl |
| (prompts, tool calls, outcomes, project) |
+---------------------------------------------+
|
| Observer agent reads (background, Haiku)
v
+---------------------------------------------+
| PATTERN DETECTION |
| * User corrections -> instinct |
| * Error resolutions -> instinct |
| * Repeated workflows -> instinct |
| * Scope decision: project or global? |
+---------------------------------------------+
|
| Creates/updates
v
+---------------------------------------------+
| projects/<project-hash>/instincts/personal/ |
| * prefer-functional.yaml (0.7) [project] |
| * use-react-hooks.yaml (0.9) [project] |
+---------------------------------------------+
| instincts/personal/ (GLOBAL) |
| * always-validate-input.yaml (0.85) [global]|
| * grep-before-edit.yaml (0.6) [global] |
+---------------------------------------------+
Project Detection
The system automatically detects your current project:
CLAUDE_PROJECT_DIR env var (highest priority)
git remote get-url origin — hashed to create a portable project ID
git rev-parse --show-toplevel — fallback using repo path
- Global fallback — if no project is detected, instincts go to global scope
Each project gets a 12-character hash ID (e.g., a1b2c3d4e5f6).
Quick Start
Add to your ~/.claude/settings.json:
{
"hooks": {
"PreToolUse": [{
"matcher": "*",
"hooks": [{
"type": "command",
"command": "${CLAUDE_PLUGIN_ROOT}/skills/continuous-learning-v2/hooks/observe.sh"
}]
}],
"PostToolUse": [{
"matcher": "*",
"hooks": [{
"type": "command",
"command": "${CLAUDE_PLUGIN_ROOT}/skills/continuous-learning-v2/hooks/observe.sh"
}]
}]
}
}
Initialize Directory Structure
The system creates directories automatically on first use:
# Global directories
mkdir -p ~/.claude/homunculus/{instincts/{personal,inherited},evolved/{agents,skills,commands},projects}
# Project directories are auto-created when the hook first runs in a git repo
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” |
| Error handling strategies | project | ”Use Result type for errors” |
| 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” |
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
How to promote:
# Promote a specific instinct
python3 instinct-cli.py promote prefer-explicit-errors
# Auto-promote all qualifying instincts
python3 instinct-cli.py promote
# Preview without changes
python3 instinct-cli.py promote --dry-run
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
Why Hooks vs Skills?
“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
Instinct-based learning: teaching Claude your patterns, one project at a time.