Instinct-based learning system that observes sessions via hooks, creates atomic instincts with confidence scoring, and evolves them into skills/commands/agents. v2.1 adds project-scoped instincts to prevent cross-project contamination.
Scanned 6/4/2026
Install via CLI
openskills install lidge-jun/cli-jaw-skills---
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. v2.1 adds project-scoped instincts to prevent cross-project contamination.
---
# Continuous Learning v2.1 — Instinct-Based Architecture
An advanced learning system that turns agent sessions into reusable knowledge through atomic "instincts" — small learned behaviors with confidence scoring.
v2.1 adds **project-scoped instincts** — React patterns stay in your React project, Python conventions stay in your Python project, and universal patterns (like "always validate input") are shared globally.
## When to Activate
- Setting up automatic learning from agent 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
## What Changed in v2.1
| Feature | v2.0 | v2.1 |
|---------|------|------|
| Storage | Global only | 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 | 6 (+promote/projects) |
## What Changed in v2 (vs v1)
| Feature | v1 | v2 |
|---------|----|----|
| Observation | Stop hook (session end) | PreToolUse/PostToolUse (100% reliable) |
| Analysis | Main context | Background agent (fast model) |
| Granularity | Full skills | Atomic "instincts" |
| Confidence | None | 0.3–0.9 weighted |
| Evolution | Direct to skill | Instincts → cluster → skill/command/agent |
## 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"
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 |
+---------------------------------------------+
|
| Observer agent reads (background, fast model)
v
+---------------------------------------------+
| PATTERN DETECTION |
| * User corrections -> instinct |
| * Error resolutions -> instinct |
| * Repeated workflows -> instinct |
| * Scope decision: project or global? |
+---------------------------------------------+
|
| Creates/updates
v
+---------------------------------------------+
| projects/<hash>/instincts/personal/ |
| * prefer-functional.yaml (0.7) [project] |
+---------------------------------------------+
| instincts/personal/ (GLOBAL) |
| * always-validate-input.yaml (0.85) |
+---------------------------------------------+
```
## Project Detection
The system automatically detects your current project:
1. **`AGENT_PROJECT_DIR` env var** (highest priority)
2. **`git remote get-url origin`** — hashed for a portable project ID
3. **`git rev-parse --show-toplevel`** — fallback using repo path
4. **Global fallback** — if no project is detected, instincts go to global scope
Each project gets a 12-character hash ID (e.g., `a1b2c3d4e5f6`).
## Hook Setup
Add observation hooks to your agent settings. The hooks call `observe.sh` on every tool use:
```json
{
"hooks": {
"PreToolUse": [{
"matcher": "*",
"hooks": [{
"type": "command",
"command": "<skills-path>/continuous-learning-v2/hooks/observe.sh"
}]
}],
"PostToolUse": [{
"matcher": "*",
"hooks": [{
"type": "command",
"command": "<skills-path>/continuous-learning-v2/hooks/observe.sh"
}]
}]
}
}
```
## Commands
| Command | Description |
|---------|-------------|
| `/instinct-status` | Show all instincts (project-scoped + global) with confidence |
| `/evolve` | Cluster related instincts into skills/commands, suggest promotions |
| `/instinct-export` | Export instincts (filterable by scope/domain) |
| `/instinct-import <file>` | Import instincts with scope control |
| `/promote [id]` | Promote project instincts to global scope |
| `/projects` | List all known projects and their instinct counts |
## Configuration
Edit `config.json` to control the background observer:
```json
{
"version": "2.1",
"observer": {
"enabled": false,
"run_interval_minutes": 5,
"min_observations_to_analyze": 20
}
}
```
## File Structure
```
~/.config/agent/homunculus/
+-- identity.json
+-- projects.json # Registry: hash -> name/path/remote
+-- observations.jsonl # Global observations (fallback)
+-- instincts/
| +-- personal/ # Global auto-learned
| +-- inherited/ # Global imported
+-- evolved/
| +-- agents/
| +-- skills/
| +-- commands/
+-- projects/
+-- a1b2c3d4e5f6/ # Per-project directory
| +-- project.json
| +-- observations.jsonl
| +-- instincts/personal/
| +-- evolved/
+-- f6e5d4c3b2a1/
+-- ...
```
## 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", "Handle errors explicitly" |
| Tool workflow preferences | **global** | "Grep before Edit", "Read before Write" |
## Instinct Promotion (Project → Global)
When the same instinct appears in multiple projects with high confidence, promote it to global scope.
**Auto-promotion criteria:**
- Same instinct ID in 2+ projects
- Average confidence ≥ 0.8
```bash
python3 instinct-cli.py promote prefer-explicit-errors # specific
python3 instinct-cli.py promote # auto-promote all
python3 instinct-cli.py promote --dry-run # preview
```
## Confidence Scoring
| Score | Meaning | Behavior |
|-------|---------|----------|
| 0.3 | Tentative | Suggested, 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 accepts the behavior, similar instincts agree.
**Confidence decreases** when: user explicitly corrects, pattern goes unobserved, contradicting evidence appears.
## Privacy
- Observations stay **local** on your machine
- Project-scoped instincts are isolated per project
- Only **instincts** (patterns) can be exported — raw observations stay local
- You control what gets exported and promoted
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