continuous-learning-v2
affaan-m/everything-claude-code
Automatic learning system that observes your Claude Code sessions and builds reusable instincts with confidence scoring.
What is continuous-learning-v2?
Continuous Learning v2.1 captures patterns from your Claude Code work through hooks, creates atomic "instincts" (small learned behaviors with confidence scores), and evolves them into skills, commands, or agents. Project-scoped instincts prevent cross-project contamination while universal patterns are shared globally.
- Observes Claude Code sessions via PreToolUse/PostToolUse hooks with 100% reliability
- Creates atomic instincts with confidence scoring (0.3–0.9) backed by evidence
- Isolates project-scoped instincts by git remote hash to prevent cross-project contamination
- Automatically promotes instincts from project to global scope when seen in 2+ projects
- Clusters related instincts and evolves them into full skills, commands, or agents
- Exports and imports instinct libraries for sharing across teams
How to install continuous-learning-v2
npx skills add https://github.com/affaan-m/everything-claude-code --skill continuous-learning-v2- Claude Code v2.1+ (auto-loads plugin hooks)
- Git repository (for project detection via remote URL)
- XDG_DATA_HOME or ~/.local/share directory writable
How to use continuous-learning-v2
- 1.Install the skill via npx skills add
- 2.Verify hooks are enabled (auto-loaded in Claude Code v2.1+, or manually add to settings.json if needed)
- 3.Work normally in Claude Code; the system observes prompts and tool use automatically
- 4.Run /instinct-status to view learned instincts with confidence scores
- 5.Run /evolve to cluster related instincts and suggest evolution into skills/commands
- 6.Run /promote to move validated project instincts to global scope
- 7.Export instincts with /instinct-export to share with teammates
Use cases
- Automatically capture your preferred coding style (e.g., functional over class-based) and apply it to future work
- Learn testing patterns from your corrections and apply them project-wide
- Build reusable commands from repeated workflows you perform across sessions
- Share instincts with teammates by exporting and importing instinct libraries
- Promote project-specific patterns (React hooks, Python conventions) to global scope once validated across projects
- Claude Code users who want automatic knowledge capture from their sessions
- Teams building shared coding standards and patterns
- Developers working across multiple projects who want project-isolated learning
- Anyone seeking to turn observed behaviors into reusable skills and commands
continuous-learning-v2 FAQ
The system detects your project via git remote URL (hashed for portability), CLAUDE_PROJECT_DIR env var, or repo path. Instincts learned in one project stay isolated there by default. Once an instinct is observed in 2+ projects, /evolve suggests promoting it to global scope.
v2.1 adds project-scoped instincts stored outside ~/.claude (in XDG_DATA_HOME) to prevent cross-project contamination. v2.0 stored all instincts globally. v2.1 also adds /promote and /projects commands for managing scope.
Confidence ranges from 0.3 (tentative) to 0.9 (near certain) based on evidence: user corrections, error resolutions, repeated workflows, and observation frequency. Each instinct tracks the observations that created it.
Yes. Run bash skills/continuous-learning-v2/scripts/migrate-homunculus.sh to move data from ~/.claude/homunculus to XDG_DATA_HOME/ecc-homunculus.
Use /instinct-export to save instincts to a file, then teammates can import them with /instinct-import <file>. You can filter by scope (project/global) and domain when exporting.
Full instructions (SKILL.md)
Source of truth, from affaan-m/everything-claude-code.
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. metadata: origin: ECC version: 2.1.0
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.
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 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
What's New in v2.1
| Feature | v2.0 | v2.1 |
|---|---|---|
| Storage | Global (~/.claude/homunculus/) | Project-scoped (${XDG_DATA_HOME:-~/.local/share}/ecc-homunculus/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 |
What's New in v2 (vs v1)
| 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"
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) orglobal
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] |
+---------------------------------------------+
|
| /evolve clusters + /promote
v
+---------------------------------------------+
| projects/<hash>/evolved/ (project-scoped) |
| evolved/ (global) |
| * commands/new-feature.md |
| * skills/testing-workflow.md |
| * agents/refactor-specialist.md |
+---------------------------------------------+
Project Detection
The system automatically detects your current project:
CLAUDE_PROJECT_DIRenv var (highest priority)git remote get-url origin-- hashed to create a portable project ID (same repo on different machines gets the same ID)git rev-parse --show-toplevel-- fallback using repo path (machine-specific)- Global fallback -- if no project is detected, instincts go to global scope
Each project gets a 12-character hash ID (e.g., a1b2c3d4e5f6). A registry file at ${XDG_DATA_HOME:-~/.local/share}/ecc-homunculus/projects.json maps IDs to human-readable names.
Data Directory
Continuous-learning-v2 stores observer data outside ~/.claude so Claude Code's sensitive-path guard does not block background instinct writes:
CLV2_HOMUNCULUS_DIRwhen set to an absolute path$XDG_DATA_HOME/ecc-homunculus$HOME/.local/share/ecc-homunculus
Existing users with data at ~/.claude/homunculus can migrate once:
bash skills/continuous-learning-v2/scripts/migrate-homunculus.sh
Quick Start
1. Enable Observation Hooks
If installed as a plugin (recommended):
No extra settings.json hook block is required. Claude Code v2.1+ auto-loads the plugin hooks/hooks.json, and observe.sh is already registered there.
If you previously copied observe.sh into ~/.claude/settings.json, remove that duplicate PreToolUse / PostToolUse block. Duplicating the plugin hook causes double execution and ${CLAUDE_PLUGIN_ROOT} resolution errors because that variable is only available inside plugin-managed hooks/hooks.json entries.
If installed manually to ~/.claude/skills, add this to your ~/.claude/settings.json:
{
"hooks": {
"PreToolUse": [{
"matcher": "*",
"hooks": [{
"type": "command",
"command": "~/.claude/skills/continuous-learning-v2/hooks/observe.sh"
}]
}],
"PostToolUse": [{
"matcher": "*",
"hooks": [{
"type": "command",
"command": "~/.claude/skills/continuous-learning-v2/hooks/observe.sh"
}]
}]
}
}
2. Initialize Directory Structure
The system creates directories automatically on first use, but you can also create them manually:
# Global directories
mkdir -p "${XDG_DATA_HOME:-$HOME/.local/share}/ecc-homunculus"/{instincts/{personal,inherited},evolved/{agents,skills,commands},projects}
# Project directories are auto-created when the hook first runs in a git repo
3. 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
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:
{
"version": "2.1",
"observer": {
"enabled": false,
"run_interval_minutes": 5,
"min_observations_to_analyze": 20
}
}
| Key | Default | Description |
|---|---|---|
observer.enabled | false | Enable the background observer agent |
observer.run_interval_minutes | 5 | How often the observer analyzes observations |
observer.min_observations_to_analyze | 20 | Minimum observations before analysis runs |
Other behavior (observation capture, instinct thresholds, project scoping, promotion criteria) is configured via code defaults in instinct-cli.py and observe.sh.
File Structure
${XDG_DATA_HOME:-~/.local/share}/ecc-homunculus/
+-- identity.json # Your profile, technical level
+-- projects.json # Registry: project hash -> name/path/remote
+-- observations.jsonl # Global observations (fallback)
+-- instincts/
| +-- personal/ # Global auto-learned instincts
| +-- inherited/ # Global imported instincts
+-- evolved/
| +-- agents/ # Global generated agents
| +-- skills/ # Global generated skills
| +-- commands/ # Global generated commands
+-- projects/
+-- a1b2c3d4e5f6/ # Project hash (from git remote URL)
| +-- project.json # Per-project metadata mirror (id/name/root/remote)
| +-- observations.jsonl
| +-- observations.archive/
| +-- instincts/
| | +-- personal/ # Project-specific auto-learned
| | +-- inherited/ # Project-specific imported
| +-- evolved/
| +-- skills/
| +-- commands/
| +-- agents/
+-- f6e5d4c3b2a1/ # Another project
+-- ...
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" |
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
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
The /evolve command also suggests promotion candidates.
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
v2.1 is fully compatible with v2.0 and v1:
- Existing global instincts can be migrated from
~/.claude/homunculus/instincts/withscripts/migrate-homunculus.sh - Existing
~/.claude/skills/learned/skills from v1 still work - Stop hook still runs (but now also feeds into v2)
- Gradual migration: run both in parallel
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
Related
- ECC-Tools GitHub App - Generate instincts from repo history
- Homunculus - Community project that inspired the v2 instinct-based architecture (atomic observations, confidence scoring, instinct evolution pipeline)
- The Longform Guide - Continuous learning section
Instinct-based learning: teaching Claude your patterns, one project at a time.
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