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continuous-learning-v2

Turn Claude Code session patterns into reusable behavior rules with confidence scores. Keep project-specific lessons separate, review and share learned rules, and combine related patterns into skills, commands, or agents.

OriginalShow the original 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. Use when capturing lessons from a session, managing instincts, or promoting them into skills, commands, or agents.

AI rating90/ 100See how to install

Good for

  • Capture lessons from corrections and repeated workflows
  • Keep learned conventions separate for each project
  • Turn related behavior rules into skills or commands
  • Review, export, and import learned rules

Overview

What it does

Capture corrections, error resolutions, and repeated procedures from work in Claude Code, then turn them into reusable behavior rules. Each rule, called an “instinct,” includes a trigger, an action, supporting evidence, and a confidence score. Project-specific rules are managed separately from shared rules. Related rules can be combined into skills, commands, or agents.

When it helps

Use it when you repeat the same instructions or want to accumulate development conventions without mixing rules from different projects. You can inspect learned rules, export or import them, and promote rules shared by several projects into a common scope.

Example requests

  • “Show the rules learned in this project and their confidence scores.”
  • “Combine related rules into a reusable command.”

Notes

Hooks must be configured to record work. Plugin installations load them automatically in Claude Code v2.1 or later; manual installations require additional configuration. Background analysis is disabled by default and requires WSL2, Linux, or macOS. It does not run on native Windows. Observation records are stored locally. Exports contain learned rules, rather than raw conversations or code.

This overview was written by AI (OpenAI Codex) from the public SKILL.md. Check the original below for the exact behavior.

Objective evaluation

AI rated this skill on four points using only the contents of its SKILL.md. Stars and popularity are not taken into account.

Clear instructionsIs it clear when to use it and what it does?
AGoodIt explicitly describes extracting rules from session records, managing confidence, separating projects, and sharing rules.
Concrete stepsAre steps, inputs, outputs, and examples spelled out?
AGoodIt provides hook configuration examples, rule structure and storage locations, plus commands for inspection, consolidation, import, and export.
SafetyAre sending data, deleting files, and running commands disclosed?
BPartly lackingIt discloses recording prompts and tool activity, but the supplied excerpt gives no procedure for excluding secrets.
Easy setupDoes it need few tools or API keys, and are they documented?
AGoodIt distinguishes plugin and manual installation and provides required hook configuration and initialization steps.

The total counts each point as A = 25, B = 15, C = 5. Rated by AI (OpenAI Codex) as of Oct 19, 2026. Treat it as a guide and read the original before installing.

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Files included (12)

  • SKILL.md13.8 KB
  • agents/observer-loop.sh19.4 KB
  • agents/observer.md6.7 KB
  • agents/session-guardian.sh6.2 KB
  • agents/start-observer.sh8.4 KB
  • config.json135 B
  • hooks/observe.sh27.9 KB
  • scripts/detect-project.sh10.8 KB
  • scripts/instinct-cli.py89.1 KB
  • scripts/lib/homunculus-dir.sh1010 B
  • scripts/migrate-homunculus.sh2.2 KB
  • scripts/test_parse_instinct.py52.0 KB

SKILL.md (original)

Review the instructions the agent will receive before you install.

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

Featurev2.0v2.1
StorageGlobal (~/.claude/homunculus/)Project-scoped (${XDG_DATA_HOME:-~/.local/share}/ecc-homunculus/projects/<hash>/)
ScopeAll instincts apply everywhereProject-scoped + global
DetectionNonegit remote URL / repo path
PromotionN/AProject → global when seen in 2+ projects
Commands4 (status/evolve/export/import)6 (+promote/projects)
Cross-projectContamination riskIsolated by default

What's New in v2 (vs v1)

Featurev1v2
ObservationStop hook (session end)PreToolUse/PostToolUse (100% reliable)
AnalysisMain contextBackground agent (Haiku)
GranularityFull skillsAtomic "instincts"
ConfidenceNone0.3-0.9 weighted
EvolutionDirect to skillInstincts -> cluster -> skill/command/agent
SharingNoneExport/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) 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]     |
+---------------------------------------------+
      |
      | /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:

  1. CLAUDE_PROJECT_DIR env var (highest priority) -- honored as an explicit override even when the directory is not a git repo (hashed by its absolute path)
  2. git remote get-url origin -- hashed to create a portable project ID (same repo on different machines gets the same ID)
  3. git rev-parse --show-toplevel -- fallback using repo path (machine-specific)
  4. 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:

  1. CLV2_HOMUNCULUS_DIR when set to an absolute path
  2. $XDG_DATA_HOME/ecc-homunculus
  3. $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

CommandDescription
/instinct-statusShow all instincts (project-scoped + global) with confidence
/evolveCluster related instincts into skills/commands, suggest promotions
/instinct-exportExport instincts (filterable by scope/domain)
/instinct-import <file>Import instincts with scope control
/promote [id]Promote project instincts to global scope
/projectsList 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
  }
}
KeyDefaultDescription
observer.enabledfalseEnable the background observer agent
observer.run_interval_minutes5How often the observer analyzes observations
observer.min_observations_to_analyze20Minimum 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.

Observer platform support

The background observer requires WSL2, Linux, or macOS. On native Windows (Git Bash / MSYS2) it starts and reports success, but the process is killed when the spawning hook exits and its Job Object closes, so no analysis ever runs — setting observer.enabled: true there is effectively a no-op (see issue #2489).

observe.sh detects this on the following hook invocation and writes an explanatory warning to observer-start.log once the observer has failed to survive several times in a row.

Env varDefaultDescription
ECC_OBSERVER_NOSURVIVE_WARN_AFTER3Consecutive non-survivals before the warning is logged

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 TypeScopeExamples
Language/framework conventionsproject"Use React hooks", "Follow Django REST patterns"
File structure preferencesproject"Tests in __tests__/", "Components in src/components/"
Code styleproject"Use functional style", "Prefer dataclasses"
Error handling strategiesproject"Use Result type for errors"
Security practicesglobal"Validate user input", "Sanitize SQL"
General best practicesglobal"Write tests first", "Always handle errors"
Tool workflow preferencesglobal"Grep before Edit", "Read before Write"
Git practicesglobal"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:

ScoreMeaningBehavior
0.3TentativeSuggested but not enforced
0.5ModerateApplied when relevant
0.7StrongAuto-approved for application
0.9Near-certainCore 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/ with scripts/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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