Autonomous Work Operating System 📡

👁️ Mission Control • 🛡️ Security Cycle • 💰 Revenue Engine • 🤖 MERLIN • ⚙️ Automation • 🧠 Intelligence

Overview   Product Architecture Day Cycle Quick Start Development

Security Roadmap Branding Documentation License

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↓ Jump to Section	👁️ View Demo Assets	📖 Full Docs

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Overview 🚀

OWNEX (pronounced OH-neks) — Personal Autonomous Work Operating System.

OWNEX is an autonomous work operating system that continuously discovers, understands, evaluates, organizes and prepares digital work opportunities while coordinating tools, agents, models and information.

The concept 💡

OWNEX is not a chatbot, a dashboard, or a collection of scripts. It is an intelligent operating system that navigates the universe of work opportunities, orchestrates multiple AI providers, and executes complex workflows with minimal human intervention.

The approach 📊

Every opportunity is scored against a zero-barrier spectrum (0–100): how far is it from finding to getting paid, with no interview, no portfolio gate, no unpaid trial. The engine rank-orders thousands of candidates and surfaces the ones most likely to turn into revenue this week.

The human role 👤

The human sits at the decision gate. The system does everything before and after.

_{🔮 The Revenue Rule: no feature enters the roadmap unless it increases vulnerability detection, evidence quality, acceptance probability, or system learning. No exceptions.}

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Product 🎯

Central surfaces: Mission Control, Intelligence, Targets, Capital, MERLIN, Agents, Reports, Settings. All backed by real endpoints — nothing is a mock.

Mission Control 🎛️

Central operational surface for monitoring opportunities, agents and active work.

Endpoints: GET /api/mission/status, GET /api/activity, POST /api/hunt/start

Intelligence 🧠

Information processing and opportunity analysis surfaces — findings, hypotheses, evidence, confidence.

Targets 📍

Target intelligence and opportunity prioritization — scan queues, attack surface, prioritization.

Capital 💰

Revenue tracking and financial intelligence dashboard — USD/hour per platform, payout timelines, ROI.

MERLIN 🤖

AI assistant with persistent memory, intent analysis, Office Retro personality (calm_operator, local-first Piper TTS, native mic).

API: POST /api/voice/assistant, POST /direct-work/daily-companion

Agents 👥

Twelve departmental specialists — Security, Coding, QA, Debug, Documentation, Research, Product, Revenue, Automation, Infrastructure, Evolution, Orchestrator.

Reports 📊

Report generation, submission tracking, finder queues.

Settings ⚙️

System configuration, AI providers, credentials, scheduler, integrations.

Mobile (OMEGA) 📱

Native companion (Capacitor Android): home, agents, opportunities, MERLIN chat, notifications, watch sync.

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Architecture 🏗️

A modular monolith: one FastAPI process, EventBus-driven, single database. No microservices, no external message queue, no lock-in.

flowchart TB
    subgraph SURFACE["📡 Presentation"]
        MC["Mission Control - Vue 3 SPA"]
        DESK["💻 OWNEX Desktop - Tauri v2"]
        MOB["📱 Mobile Companion - Capacitor"]
        MERLIN["🤖 MERLIN - Copilot"]
    end

    subgraph CORE["🧩 Core Platform - FastAPI"]
        EB["🔌 EventBus"]
        SCH["⏰ Scheduler - 28 cron jobs"]
        UM["🧠 Unified Memory - SQLite"]
        DJ["📓 Decision Journal"]
        VAULT["🔐 Identity Vault"]
        HC["🩺 Health Center"]
    end

    subgraph CYCLES["🔄 Work Cycles"]
        SEC["🛡️ Security"]
        FORGE["🔨 Forge"]
        PULSE["📈 Pulse"]
        VAULT_C["💰 Vault"]
        ATLAS["🗺️ Atlas"]
        QA["🧪 QA Cycle"]
        DW["💼 Direct Work"]
    end

    subgraph ENGINES["⚙️ Engines"]
        DWE["Direct Work Engine"]
        REV["💵 Revenue Intelligence"]
        OPP["🔍 Opportunity Discovery"]
        VAL["✅ Validation & Evidence"]
        EVO["📈 Evolution Learning"]
        OAR["🤖 OAR AI Runtime"]
        CAR["🎓 Career Engine"]
    end

    subgraph AI["🤖 Multi-Provider AI"]
        RT["🧠 OAR Smart Router"]
        P1["🦙 Ollama (local)"]
        P2["🔗 FCC Proxy"]
        P3["🔑 OpenRouter (optional)"]
    end

    SURFACE --> CORE
    CORE --> CYCLES
    CYCLES --> ENGINES
    ENGINES --> AI

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Stack (real, no smoke) 🛠️

Layer	Technology	Notes
Backend 🐍	Python 3.11+ · FastAPI · SQLAlchemy 2.0	3,228+ tests, Ruff clean, mypy strict
Frontend 🌐	Vue 3 + TypeScript · Tailwind CSS v4 · Vite	92 routed pages, Mission Control SPA
Desktop 💻	Tauri v2 (Rust+WebView2) + PyInstaller sidecar	Native desktop, OWNEX Alpha binary
Mobile 📱	Capacitor (Android) + Expo/React Native (OMEGA)	Native mic, native voice, APK 5.2 MB
AI Stack 🤖	Free-first con fallback y modo degradado: local → free cloud → reglas	OAR runtime: routing, circuit breakers, quota tracking, observability, 13 adapters
Database 📦	SQLite (dev/desktop) · PostgreSQL (prod)	Single DB, no external queue
Security 🔐	Ed25519 licenses · AES-256-GCM vault · CSRF double-submit	IdentityVault, chmod 600 keys
Testing ✅	pytest · pytest-cov · pytest-timeout	make test, make test-fast

7 Work Cycles 🔄

OWNEX runs as 7 autonomous work cycles, coordinated by the scheduler:

Cycle	Focus	Key APIs	Schedule
🛡️ Security	Bug bounty pipeline	/api/cycles/security/*	30-min cron
🔨 Forge	Dev bounty opportunities	/api/cycles/forge/*	2-hour cron
📈 Pulse	AI work / market signals	/api/cycles/pulse/*	1-hour cron
💰 Vault	Wealth management	/api/cycles/vault/*	4-hour cron
🗺️ Atlas	Intelligence	/api/cycles/atlas/*	4-hour cron
🧪 QA Cycle	Test execution + regression	/api/cycles/qa/*	daily 08:30
💼 Direct Work	Zero-barrier opportunities	/direct-work/*	daily 06:15

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How a day runs ⏰

Time	Cycle	What happens	Key APIs
06:15	💼 Direct Work	Work Bank: discover → filter zero-barrier → rank by EV → prepare packages	POST /direct-work/workbank/cycle
06:30	🤖 MERLIN	daily-companion → consolidated briefing (system + personal + market + focus)	POST /direct-work/daily-companion
07:00	👁️ Mission Control	Top pick of the day + skill gap + learning plan	GET /api/activity
08:00	📈 Market	Platform report: friction tiers, retired sources, emerging categories	POST /api/direct-work/market-report
09:00	💰 Capital	Revenue dashboard: earned/pending/ROI per platform, projection	POST /direct-work/income-dashboard
14:00	🛡️ Security	Findings → evidence → report → auto-submit	POST /api/cycles/security/run_pipe
18:00	👨‍💼 Executive	"Did we make money this week?" USD/hour per platform	GET /api/cycles/security/dashboard
22:00	🛡️ Backup	Version backup + health snapshot persisted	/api/version-backup/*

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FAQ ❓

What is OWNEX exactly?

OWNEX is a personal autonomous work operating system — a private platform that discovers income opportunities (bug bounty, dev bounty, AI work, freelance), analyzes them with economic scoring, prepares deliverables autonomously, and tracks results. It is not a SaaS product: it runs on your machine and works for you.

Is OWNEX open source? Can I contribute?

No — the code is proprietary and private. OWNEX is a personal competitive-advantage asset, not a community project. The repository is public for presentation, but the license is Proprietary and contributions are not accepted.

What can it actually do today?

Verified working features (not roadmap): discovery from 135 curated sources (HackerOne, Bugcrowd, Intigriti, YesWeHack, Opire, IssueHunt, Freelancer, OpenCollective…), zero-barrier scoring, Work Bank that prepares jobs to 100% ready-to-deliver, EV ranking, Daily Brief/Companion, market evolution engine (OVOS + friction tiers), career/skill gap engine, revenue tracking + projections, security pipeline (recon → hypothesis → validation → evidence → report), scheduler with 28 cron jobs, 7 work cycles, mobile Android companion (APK), desktop (Tauri + PyInstaller), voice assistant, MERLIN chat, CSRF/rate-limit/auth security layers.

Does OWNEX submit reports and work by itself?

No — by design (Human Control layer). OWNEX prepares everything: packages, reports, submissions, and negotiation analysis. The human is the final authority for actions that send data out (submissions, deliveries, payouts). Automations run only for internal preparation, discovery and analysis.

Do I need to be a bug bounty expert?

No. The Direct Work Engine scores opportunities by entry barrier and prioritizes zero-barrier public tasks; the career engine detects skill gaps and builds a daily training plan; the guided onboarding covers the fundamentals. You can start from zero and progress by category.

Does it require an internet connection or cloud services?

No. Everything runs 100% local: FastAPI backend, SQLite, local model via Ollama. Optional integrations (SMTP for email verification, platform APIs, cloud backup) are opt-in and never required. There is no telemetry, no account cloud.

Which AI models does it use? Do I need API keys?

No keys required to start. OWNEX prioritizes local (Ollama) and free providers (OpenCode, OmniRoute) with automatic fallback. When a provider fails or hits quotas, the circuit breaker routes to the next in the chain — and if all LLMs are unavailable, deterministic engines keep the system running in degraded mode. Paid providers exist but are disabled by default (daily_budget = $0).

Does it really make money?

The system optimizes probability × reward × speed and tracks real outcomes (earnings, acceptance rates, USD/hour per platform) — it never fabricates rates. Revenue figures in the UI come from actual tracked payouts. Results depend on the market and on delivery; OWNEX maximizes the odds and removes the busywork.

What platforms does it integrate with?

Bug bounty: HackerOne, Bugcrowd, Intigriti, YesWeHack. Dev bounty: Opire, IssueHunt, OpenCollective, Algora. Freelance: Fiverr engine (11 gigs), Freelancer. Plus 135 curated discovery sources across 36 categories. Connectors for crypto/wealth (CoinGecko, Polymarket) and data annotation categories.

How do I install it?

git clone https://github.com/AdriDob/OWNEX.git && cd OWNEX
python3 -m venv .venv && source .venv/bin/activate
pip install -r requirements.txt
python run.py

Open http://127.0.0.1:8000 — the guided personalization wizard takes you through setup. See Quick Start.

What platforms does it run on?

• Desktop: Linux, Windows, macOS (Python 3.11+; Tauri bundle + PyInstaller sidecar)
• Mobile companion: Android (Capacitor APK, ~5 MB, native mic/voice)
• The mobile app connects to your local backend; it does not require a cloud server.

Is my data safe?

Security is layered: AES-256-GCM IdentityVault (random key, chmod 600), Ed25519 licenses, double-submit CSRF, identity-based rate limiting, session tokens with device binding, audit log (append-only JSONL, rotated), 100% local storage. Details in .ai/SECURITY_POLICY.md.

Is there a mobile/desktop app?

Yes — an Android APK (OMEGA companion: dashboard, agents, opportunities, MERLIN chat, notifications, watch sync) and a Tauri desktop bundle (OWNEX OMEGA). Both are build-verified; see Project Status.

What is the "Work Bank"?

The Work Bank is an autonomous production engine: it discovers public zero-barrier jobs, filters and ranks them by EV, prepares each one to 100% ready-to-deliver (README, proposal, work package) and accumulates them (target: 10/day, 1000/month). You only review and deliver the best ones.

How is OWNEX different from a SaaS bounty tool?

SaaS tools are multi-tenant dashboards; OWNEX is a private autonomous operator. It doesn't just display findings — it discovers opportunities, prepares deliverables, projects income, learns from outcomes and runs a full daily cycle with zero external infrastructure. And your data never leaves your machine.

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Table of Contents

Click to expand 📖

1. Overview
2. Product
3. Architecture
4. How a day runs
5. FAQ
6. Quick Start
7. Development
8. Security
9. Project Status
10. Roadmap
11. Branding
12. Documentation
13. License

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Quick Start 🚀

Multi-Platform Installation

Choose your platform:

🪟 Windows 11 (with WSL) — Desktop Installer (Recommended)

Auto-contained bundle — no Python/Node required

1. Build or download the installer:
   • Canonical (Tauri): run .github/workflows/ownex-tauri-windows.yml → artifact OWNEX-Tauri-Windows (OWNEX Alpha_7.0.0_x64-setup.exe / .msi)
   • Legacy (PySide6 NSIS): dispatch ownex-alpha-windows.yml (manual) → artifact OWNEX-Alpha-Windows-Installer; last deployed build: ownexinstalador/windows/OWNEX-Desktop-Alpha-Setup.exe
   • GitHub Releases (when published)
2. Run the installer (accept SmartScreen warning — debug build)
3. Launch OWNEX Desktop from Start menu
4. Backend starts automatically at http://127.0.0.1:8000
5. Data persists in %APPDATA%\OWNEX (survives reinstalls)

Detailed guide: README-INSTALACION.md

🐧 Linux — Development Setup

# 1️⃣ Clone
git clone https://github.com/AdriDob/OWNEX.git
cd OWNEX

# 2️⃣ Virtual environment + deps
python -m venv .venv
source .venv/bin/activate
pip install -r requirements.txt          # backend
cd frontend && npm install               # frontend

# 3️⃣ Start everything
python run.py                              # → FastAPI on http://localhost:8000
# in another terminal:
cd frontend && npm run dev                # → Mission Control on http://localhost:5173

📱 Android — Mobile Companion

cd android
./gradlew assembleDebug                  # → android/app/build/outputs/apk/debug/app-debug.apk
# Install via ADB or transfer to device

Detailed guide: android/BUILD_RELEASE_APK.md

⌚ WearOS — Smartwatch Companion

cd android
./gradlew :wear:assembleDebug           # → android/wear/build/outputs/apk/debug/wear-debug.apk
# Install via ADB to WearOS device

Detailed guide: .ai/WEAROS_DECISION.md

Guided install (Linux/Dev)

The universal installer (install.py) configures everything interactively:

python install.py
# → Wizard: use case → modules → experience level → platforms → integrations
# → sets up .venv, DB, credentials, desktop, notifications

Next steps

Action	Command / Route	Docs
Health check	curl localhost:8000/api/health	.ai/CURRENT_STATE.md
Add a bug bounty target	python run.py --add-target "demo" --domain example.com	Agent Charter
Run the QA cycle	POST /api/cycles/qa/run	.ai/ROADMAP.md
Daily briefing	POST /direct-work/daily-companion	.ai/CURRENT_STATE.md
Create version backup	python scripts/version_backup.py backup	DECISIONS.md
Quality gate	make check	.ai/TESTING_POLICY.md
Fast smoke tests	python scripts/dev test-fast	.ai/TESTING_POLICY.md
Generate docs diagrams	scripts/brand/regenerate.sh	docs/README.md

Tip: make is your friend. Other targets: make test, make fmt, make backup, make typecheck-fast.

Environment variables

API keys go to IdentityVault (AES-256-GCM, random key, chmod 600) or .env (never committed):

# AI providers (at least one)
OLLAMA_URL=http://localhost:11434                  # local (default)
OPENROUTER_API_KEY=                                 # optional premium
FCC_PROXY_URL=http://localhost:8082                 # free Claude proxy

# Platforms (bug bounty etc.)
HACKERONE_API_KEY=
BUGCROWD_API_KEY=
SYNACK_API_KEY=

# Email verification (optional)
OWNNEX_MAIL_SMTP_HOST=                              # set to enable email verification

See .ai/SECURITY_POLICY.md for the full security model.

---

Development 🛠️

OWNEX is developed as a single source of truth system. Everything operational lives in .ai/:

.ai/                          ← Sistema de verdad única
├── AGENT_CHARTER.md          # 🏛️ Constitución, Agent Loop, Regla de Oro
├── PRODUCTION_RULES.md       # 📋 Reglas de producción (extend, never break)
├── CURRENT_STATE.md          # 📊 Estado verificado feature por feature
├── TASK_QUEUE.md             # 📋 Cola priorizada con criterios de cierre
├── ROADMAP.md                # 🗺️ Roadmap general
├── DECISIONS.md              # 📓 Decisiones arquitectónicas con evidencia
├── KNOWN_DEBT.md             # ⚠️ Deuda técnica conocida
├── DO_NOT_TOUCH.md           # 🚫 Componentes estables (licencia, vault, auth)
├── STRATEGIC_AUDIT.md        # 🔍 Marco de auditoría permanente
├── CODE_QUALITY.md           # 🧹 Standards de calidad
├── TESTING_POLICY.md         # ✅ Política de testing
├── SECURITY_POLICY.md        # 🔐 Principios de seguridad
├── PROJECT_CONTEXT.md        # 📐 Contexto del proyecto
├── LESSONS.md                # 📚 Lecciones aprendidas
├── MEMORY.md                 # 🧠 Unified Memory subsystem
└── OWNEX_OMEGA_ARCHITECTURE.md  # 🏢 Arquitectura OMEGA

Golden rule: when code, docs, or agent memory conflict — .ai/ wins.

Commands

# Testing
python scripts/dev test              # full suite (excluye test_security.py)
python scripts/dev test-fast         # smoke: scoring + scheduler + DWE
make test                            # alias

# Lint + typecheck (CI-equivalent)
make check                            # ruff + mypy scoped + fast tests
make fmt                             # write fixes

# Backend
python run.py                        # full system
python run.py --add-target <name> --domain <domain>
python run.py --backup
python scripts/version_backup.py backup --notes "pre-update"

# Frontend (from frontend/)
npm run dev                          # dev server
npm run build                        # production build
npx vite preview                     # serve dist
npx vue-tsc --noEmit                  # typecheck

# Branding pipeline
scripts/brand/regenerate.sh          # logo + banners + README badge sync
scripts/brand/regenerate.sh --shots  # + screenshots (dark + light)

Stack

Concern	Tool	Config
Python lint	Ruff	pyproject.toml[tool.ruff]
Python types	mypy	strict on core/
Frontend lint	Biome	frontend/biome.json
Python tests	pytest	tests/test_*.py, --timeout=60
Frontend build	Vite	frontend/vite.config.ts

---

Security 🔐

Measure	Implementation	Docs
Local-first	100% local by default — nothing leaves the machine	.ai/SECURITY_POLICY.md
Credential vault	IdentityVault AES-256-GCM, random key, chmod 600	core/identity_vault.py
License validation	Ed25519 asymmetric, 25-char format	cores/license/
CSRF protection	Double-submit cookie on all mutantes	api/middleware/csrf_middleware.py
Rate limiting	Per-identity with IP fallback	api/middleware/rate_limit_middleware.py
Audit log	Append-only JSONL, 10 MB rotation	cores/audit_log.py
Session security	AES-256-GCM, device binding, 30-min expiry	cores/auth/session.py

See .ai/SECURITY_POLICY.md for the complete security model.

---

Project Status 🩺

Honest state of the system — nothing here is a mock:

Layer	State	EVIDENCE
🛡️ Security pipeline (7 stages, auto-submit)	✅ production-hardened	tests/test_e2e_security_pipeline.py — 8 passed
💼 Direct Work Engine + Work Bank + Daily Companion + Evolution	✅ production	cores/direct_work_engine/ (engine + filters + feedback)
🔄 7 Work Cycles · 28 scheduled jobs · Mission Control · Executive Dashboard	✅ production	tests/test_scheduler_jobs.py — 40 passed
🤖 OAR AI Runtime (routing + resilience + observability) + Career Engine	✅ production	tests/test_oar.py · test_ai_resilience.py 46 ✓ · AI Runtime →
💰 Income Target Engine + Economic Engine + Payment Pipeline canónico	✅ production	tests/test_income_target.py · test_payment_pipeline.py · test_economics_ssot.py
💻 Desktop (Tauri v2) · Mobile (Capacitor) · MERLIN	✅ build-verified	APKs 5.1 MB · Tauri cargo check OK
📱 OMEGA mobile (Expo/React Native)	🟡 experimental skeleton	functional shell
⌚ Wear OS native	✅ COMPLETED	.ai/WEAROS_DECISION.md — fully implemented

Single-user, local-first. New surfaces ship as experimental until they pass the end-to-end gate (persistence, restart survival, real output — no mocks).

_{🐝 Bee Monitor active: every /api/health, /api/system/health and /api/system/status is live. Check .ai/CURRENT_STATE.md for the latest honey — findings, reports, payouts.}

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Roadmap 🗺️

See .ai/ROADMAP.md for the full roadmap.

Status	Item	Docs
✅ DONE	Security pipeline (7 stages) — auto-submit to finder queues	Security Cycle
✅ DONE	Direct Work Engine + Work Bank + Daily Companion + Evolution	DWE
✅ DONE	7 Work Cycles, 28 scheduled jobs, Mission Control, Executive Dashboard	Auditoría
✅ DONE	Desktop (Tauri v2 + PyInstaller sidecar), mobile companion, MERLIN	PRESENTATION
✅ DONE	OAR AI Runtime — engine + tests + API mounted (/oar/*, /career/*)	DECISIONS
🟡 IN PROGRESS	OMEGA mobile (Expo/React Native) — functional skeleton	.ai/ROADMAP.md
🔲 PLANNED	OAR smart-routing wired into API decisions · more discovery adapters (Algora, OpenCollective, Superteam)	.ai/TASK_QUEUE.md
✅ INCLUDED	Wear OS native — fully implemented with API integration and themes	.ai/WEAROS_DECISION.md

---

Branding 🎨

OWNEX mark — The Aperture Nexus: octagonal ring + X of rays + central node that breaks the ring. Generated by a deterministic, GPU-free pipeline (scripts/brand/), zero generative AI, 100% reproducible.

scripts/brand/regenerate.sh          # logo system + banners + PNG renders + README badge sync
scripts/brand/regenerate.sh --shots  # + real product screenshots (dark + light, Playwright)

Design language: Tesla dark — pure black surfaces, white primary accent, deep blue #1E40FF as the only saturated accent, no noise, no glow.

📦 Assets live at: docs/assets/branding/ and docs/assets/screenshots/. See the Asset Registry.

docs/assets/branding/
├── logo/      # O+X mark (white/black/mono/omega), wordmark, lockup, favicon
├── banners/   # hero-banner 2400×900 — footer-banner, lockup, showdown
├── social/    # open-graph preview 1200×630
└── themes/    # design tokens SSOT (assets/branding/themes/tesla.json)
docs/assets/screenshots/
├── desktop/           # dark product screenshots
└── desktop-light/     # light product screenshots

Branded deliverables 🖼️

Color palette:

Role	Color	Usage
--ownex-bg	#05060A	Page/surface backgrounds
--ownex-blue	#1E40FF	Primary action, links
--ownex-accent	#e82127	Tesla red — the only saturated accent
--ownex-white	#F6F8FB	Text and icons

---

Documentation 📚

The project runs on a single source of truth: everything operational lives in .ai/.

Core (.ai/)

Document	Purpose
AGENT_CHARTER.md	🏛️ Constitution, Agent Loop, Golden Rule
PRODUCTION_RULES.md	📋 Reglas de producción (never break stable)
CURRENT_STATE.md	📊 Estado verificado feature por feature
TASK_QUEUE.md	📋 Cola de tareas priorizada
ROADMAP.md	🗺️ Roadmap general
DECISIONS.md	📓 Decisiones arquitectónicas con evidencia
KNOWN_DEBT.md	⚠️ Deuda técnica conocida
DO_NOT_TOUCH.md	🚫 Componentes estables
STRATEGIC_AUDIT.md	🔍 Marco de auditoría permanente (10 questions, 18 dimensions)
SECURITY_POLICY.md	🔐 Principios de seguridad
TESTING_POLICY.md	✅ Política de testing
CODE_QUALITY.md	🧹 Standards de calidad
PROJECT_CONTEXT.md	📐 Contexto completo del proyecto
LESSONS.md	📚 Lecciones aprendidas
MEMORY.md	🧠 Unified Memory subsystem

Design & Audit (/docs)

Document	Purpose
docs/README.md	📚 Documentation hub
docs/audit/INTERNAL_AUDIT.md	🔍 Auditoría completa del sistema
docs/audit/GITHUB_PRESENTATION_REPORT.md	🐝 Branding + presentation report
docs/design/ASSET_REGISTRY.md	🎨 Asset registry
docs/diagrams/architecture.mmd	🏗️ Architecture diagram (Mermaid)

Quick references

• API: curl http://localhost:8000/docs → FastAPI interactive docs (Swagger + ReDoc)
• CLI: python run.py --help → all commands (backup, add-target, dev tools)
• Makefile: make help → all targets

---

License 📄

Proprietary. All rights reserved.

OWNEX is a private competitive-advantage asset. It does not sell a service to a customer. OWNEX works for me.

---

OWNEX does not sell a service to a customer. OWNEX works for me.

_{🔮 Personal Autonomous Work Operating System · The Aperture Nexus}

🏛️ Charter • 🗺️ Roadmap • 🔐 Security • 📚 Docs • 💻 GitHub

_{🐝 Bee Monitor: curl localhost:8000/api/health · built with make check}