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Vashisht"},"license":"MIT","homepage":"https://github.com/rijuvashisht/Magneto#readme","keywords":["ai","reasoning","agent","orchestrator","copilot","openai","mcp","enterprise","security","multi-agent"],"repository":{"type":"git","url":"git+https://github.com/rijuvashisht/Magneto.git"},"description":"Repo-local AI reasoning framework and agent control plane for enterprise environments","maintainers":[{"name":"rijuvashisht","email":"rijuvashisht@gmail.com"}],"readme":"<p align=\"center\">\n  <img src=\"docs/logo.png\" alt=\"Magneto AI Logo\" width=\"560\" />\n</p>\n\n<p align=\"center\">\n  <strong>Repo-local AI reasoning framework & agent control plane for enterprise environments.</strong>\n</p>\n\n<p align=\"center\">\n  <em>All AI Engineering Tasks. Any Language or Stack. Enterprise Security and Guardrails.<br/>\n  One Magneto AI To Pull Them All.</em>\n</p>\n\n<p align=\"center\">\n  <a href=\"#-quick-start\">Quick Start</a> •\n  <a href=\"#-raw-windsurfcopilot-vs-magneto-ai--token--cost-benchmarks\">Benchmarks</a> •\n  <a href=\"#-architecture\">Architecture</a> •\n  <a href=\"#-power-pack-system\">Power Packs</a> •\n  <a href=\"#-copilot-integration\">Copilot</a> •\n  <a href=\"#-cli-reference\">CLI Reference</a>\n</p>\n\n<p align=\"center\">\n  <a href=\"https://landing-fsmpg96k6-rijuvashisht-1233s-projects.vercel.app/\"><img src=\"https://img.shields.io/badge/📚%20Documentation-58a6ff?style=for-the-badge\" alt=\"Documentation\" /></a>\n  <a href=\"https://www.npmjs.com/package/magneto-ai\"><img src=\"https://img.shields.io/npm/v/magneto-ai?color=brightgreen&label=npm\" alt=\"npm version\" /></a>\n  <a href=\"https://www.npmjs.com/package/magneto-ai\"><img src=\"https://img.shields.io/npm/dm/magneto-ai?color=blue&label=downloads\" alt=\"npm downloads\" /></a>\n  <a href=\"https://github.com/rijuvashisht/Magneto/actions\"><img src=\"https://github.com/rijuvashisht/Magneto/actions/workflows/ci.yml/badge.svg\" alt=\"CI\" /></a>\n  <a href=\"https://buymeacoffee.com/rijuvashisht\"><img src=\"https://img.shields.io/badge/Buy%20Me%20a%20Coffee-☕-yellow\" alt=\"Buy Me a Coffee\" /></a>\n  <a href=\"https://github.com/sponsors/rijuvashisht\"><img src=\"https://img.shields.io/badge/Sponsor-%E2%9D%A4-pink?logo=github\" alt=\"GitHub Sponsors\" /></a>\n</p>\n\n---\n\n\nMagneto AI is a multi-agent AI orchestration system that brings structured reasoning, security guardrails, and pluggable intelligence to your codebase — designed to work alongside every major AI coding assistant and agent gateway.\n\n---\n\n## 🧠 About Magneto AI\n\nMagneto AI is **not** another AI wrapper. It is a **reasoning engine**, **governance layer**, and **agent control plane** that sits between your team and any AI coding assistant — enforcing security, planning tasks, and building deep project understanding before a single line is written or deleted.\n\n- **🚨 AI Security Auditing (Project Glasswing)** — Pre-execution vulnerability scanning for ALL AI assistants (Claude, Copilot, Manus, etc.) with auto-fix for code findings *and* dependency upgrades\n- **🧱 Spec-Driven Development** — pluggable [OpenSpec / Spec Kit / BMAD](#-spec-driven-development) frameworks selected on `magneto init`, with a built-in spec↔code drift reconciler\n- **📐 OS-level Sandboxing** — run agents inside Docker, Podman, macOS `sandbox-exec`, Linux `bwrap`, **Windows Sandbox**, or **WSL2** with strict / standard / dev / off profiles\n- **🔐 Zero-Trust Memory Lock** — `memory.lock` files signed with HMAC-SHA256 (machine-bound key); offline-only memory mutation; root/owner unlock policies\n- **Orchestrates multiple AI agents** with role-based task delegation\n- **Enforces security guardrails** — protected paths, blocked actions, approval workflows\n- **Classifies tasks** and creates execution plans before running anything\n- **Merges agent outputs** with confidence-weighted deduplication\n- **Plugs into your existing workflow** — Copilot, OpenAI, MCP tools\n- **Extends via Power Packs** — language, framework, cloud, and project-type intelligence\n\nThink of it as the nervous system connecting your AI tools to your codebase — with the safety controls an enterprise demands.\n\n### Works With Every AI Coding Assistant\n\nMagneto AI acts as the **skill and governance layer** for the full ecosystem of AI coding assistants and agent gateways — so your rules, security checks, and task plans travel with you regardless of which tool you use:\n\n| Assistant / Gateway | Integration |\n|---|---|\n| **Claude Code** | MCP tools via `mcp.json`, skill files injected into context |\n| **Codex / OpenAI** | Direct API runner with structured JSON task execution |\n| **OpenCode** | Prompt generation via `magneto generate` scoped to relevant files only |\n| **Cursor** | Skill files + `.cursor/rules/` auto-generated on `magneto init` |\n| **Gemini CLI** | MCP-compatible tool layer (`plan_task`, `security_check`, etc.) |\n| **GitHub Copilot CLI** | MCP server + `.github/agents/` + `copilot-instructions.md` |\n| **VS Code Copilot Chat** | `.github/copilot-instructions.md` + MCP config in `.vscode/mcp.json` |\n| **Aider** | Skill injection via adapter system + `AGENTS.md` |\n| **OpenClaw** | Native plugin on ClawHub — `openclaw plugins install clawhub:openclaw-magneto` |\n| **Factory Droid** | Governance adapter via MCP tool hooks |\n| **Trae** | Skill injection via adapter system + `AGENTS.md` |\n| **Hermes** | Skill injection via adapter system |\n| **Kiro** | Skill files in `.kiro/skills/` + steering rules |\n| **Google Antigravity** | MCP-compatible `security_check` and `plan_task` tools |\n\nOne `magneto init`. All assistants governed. See **[AI Assistant Setup Guide](./docs/AI-ASSISTANTS.md)** for per-tool walkthroughs.\n\n### Turn Any Folder Into a Queryable Knowledge Graph\n\nMagneto AI's `analyze` command ingests your entire project and builds a **knowledge graph** with community detection, confidence-scored edges, and interactive visualization:\n\n```\nmagneto analyze\n```\n\n- **Source code** → exports, imports, classes, functions, dependency maps, EXTRACTED edges (confidence 1.0)\n- **Module structure** → directory-level nodes with INFERRED co-location edges (confidence 0.5–0.9)\n- **Community detection** → Louvain algorithm identifies clusters of related code\n- **God nodes** → highest-degree concepts that everything connects through\n- **Config & docs** → environment shapes, schema definitions, feature flags\n\n**Outputs:**\n\n```\n.magneto/memory/\n├── graph.json            queryable knowledge graph (nodes, edges, communities)\n├── graph.html            interactive vis.js visualization — open in any browser\n├── graph-report.md       god nodes, communities, edge distribution, suggested questions\n├── root-summary.md       project overview + token savings\n├── file-index.md         all files with signatures\n├── dependencies.md       import/dependency map\n└── modules/*.md          per-directory summaries\n```\n\n**Query the graph from the terminal:**\n\n```bash\nmagneto query \"auth flow\"                        # BFS subgraph extraction\nmagneto query \"security\" --dfs --budget 500      # DFS with token budget\nmagneto path \"evaluateSecurity\" \"initCommand\"    # shortest path between nodes\n```\n\nThe result: every AI prompt is pre-scoped to only the files that matter — **fewer tokens**, faster responses, no hallucinated file paths.\n\n### Magneto + Graphify: Deep Multimodal Analysis\n\nFor full multimodal support — PDFs, images, screenshots, video, audio, and 25-language tree-sitter AST — pair Magneto with [Graphify](https://github.com/safishamsi/graphify):\n\n```bash\npip install graphifyy\nmagneto analyze --deep       # shells to graphify for multimodal extraction\n```\n\nWhen `--deep` is passed, Magneto invokes Graphify under the hood and imports its richer graph (Leiden clustering, Claude vision extraction, Whisper transcription) into `.magneto/memory/`. If Graphify isn't installed, Magneto falls back to its native code-only graph.\n\n| Capability | `magneto analyze` | `magneto analyze --deep` |\n|---|---|---|\n| Code parsing | Regex (JS/TS, Java, Python, Go, + more) | tree-sitter AST (25 languages) |\n| Knowledge graph | Louvain communities + god nodes | Leiden communities + hyperedges |\n| Confidence scores | EXTRACTED / INFERRED | + AMBIGUOUS with confidence 0.0–1.0 |\n| Interactive visualization | vis.js graph.html | vis.js graph.html (richer) |\n| PDFs, images, video | — | Claude vision + Whisper transcription |\n| Graph querying | `magneto query` / `magneto path` | Same + `graphify query` / `graphify explain` |\n\n### What It Is Not\n\nMagneto AI is **not** an AI model, a chat interface, or a replacement for your coding assistant. It is the **layer of intelligence underneath** — planning, securing, and contextualizing every task before your assistant runs it.\n\n---\n\n## ⚙️ Core Capabilities\n\nMagneto AI unifies task classification, multi-agent orchestration, security evaluation, and result merging into a single framework that any AI coding assistant can plug into.\n\n### Task Classification & Planning\nEvery task is automatically classified into one of 9 categories — `architecture-review`, `bug-fix`, `feature-implementation`, `security-audit`, `performance-review`, `testing`, `requirements-analysis`, `code-review`, or `general` — using keyword analysis against the task title, description, and tags. Based on the classification, Magneto AI assigns the right roles (orchestrator, backend, tester, requirements) and generates a structured execution plan before any AI agent runs.\n\n### Multi-Agent Orchestration\nMagneto AI creates dedicated sub-agents for each assigned role, each with its own model configuration (`gpt-4o`), tool access (`plan_task`, `load_context`, `merge_results`, `security_check`), and scoped file visibility. The orchestrator coordinates the agents; each agent works within its defined scope and constraints.\n\n### Security Guardrail Engine\n**Every task is evaluated before execution.** The security engine scans for:\n- **Protected paths** — `.env`, `.pem`, `.key`, `.cert`, `secrets/`, `.ssh/`, `credentials/`\n- **Blocked actions** — `delete-database`, `drop-table`, `rm -rf`, `format`, `truncate`\n- **Auth changes** — permission modifications, token operations, authentication logic\n- **Infrastructure risk** — deploy, migrate, infra-as-code changes\n- **Dependency risk** — package installs, lockfile modifications\n\nThe engine returns a risk level (`low` / `medium` / `high`), whether human approval is required, a list of blocked actions detected, and a **telepathy level** (0–3) that controls how much autonomy the AI agents receive.\n\n### Confidence-Weighted Result Merging\nAfter agents complete their analysis, Magneto AI merges all findings and risks with **content-based deduplication** — identical findings keep the higher confidence score, identical risks keep the higher severity. The overall confidence is calculated using a weighted average that favors high-confidence agents. The final merged output includes an `overallRisk` assessment (`low` → `critical`).\n\n### Auto-Detection Power Packs\nMagneto AI scans your project to automatically detect which Power Packs to activate:\n- **TypeScript** — detects `tsconfig.json` or `typescript` in dependencies\n- **Next.js** — detects `next` in dependencies\n- **AI Platform** — detects `openai`, `@azure/openai`, `langchain`, or `@langchain/core`\n- **Azure** — detects `azure.yaml`, `bicep/`, or `infra/` directories\n- **Graphify** — detects `.graphify-out/graph.json`\n\nEach pack adds domain-specific rules and checks that are injected into agent prompts and execution plans.\n\n### MCP-Compatible Tool Layer\nMagneto AI exposes its core engine as 4 MCP tools via an HTTP server, allowing any MCP-compatible client (GitHub Copilot, VS Code, custom agents) to invoke Magneto AI directly:\n- `plan_task` — classify a task and generate an execution plan\n- `load_context` — build full project context with role assignments and file resolution\n- `merge_results` — merge multiple agent output files with deduplication\n- `security_check` — evaluate security constraints and get approval requirements\n\n### Copilot-Native Integration\nMagneto AI generates full GitHub Copilot integration out of the box:\n- **4 agent definitions** (`magneto-orchestrator`, `magneto-backend`, `magneto-tester`, `magneto-requirements`) in `.github/agents/`\n- **Copilot instructions** in `.github/copilot-instructions.md` teaching Copilot how to use Magneto tools\n- **MCP config** in `.vscode/mcp.json` connecting VS Code to the local MCP server\n\n### Multiple Execution Runners\nSix built-in runners execute tasks through different AI backends:\n- **OpenAI Runner** — Chat Completions API, structured JSON output, streaming, auto-selected when `OPENAI_API_KEY` is set\n- **Copilot Local Runner** — structured prompts for GitHub Copilot's local agent mode via MCP tools\n- **Copilot Cloud Runner** — remote Copilot Cloud API endpoint with bearer token auth\n- **Cascade / Antigravity Runner** — routes through the local Windsurf/Copilot process; no direct network call\n- **Gemini Runner** — Google AI API, auto-selected when `GEMINI_API_KEY` or `GOOGLE_AI_KEY` is set\n- **Ollama Runner** — fully local, zero-egress; no API key required. Set `OLLAMA_HOST` or `MAGNETO_USE_OLLAMA` to activate. See `docs/RUNNER-OLLAMA.md`.\n\n### Adapter System\nAdapters import external tool data into Magneto's memory. The **Graphify adapter** reads `.graphify-out/graph.json` and maps dependency graph nodes/edges into Magneto's context, with configurable priority modes (`internal-first` or `external-first`).\n\n### Secure by Design\nInput validation on all task files. Protected path patterns block access to secrets and credentials. Blocked action detection prevents destructive operations. Execution modes (`observe`, `assist`, `execute`, `restricted`) enforce escalating levels of control. High-risk tasks automatically set telepathy to 0 and require human approval.\n\n---\n\n## 🔬 The Magneto AI Power Model\n\nMagneto AI draws its conceptual architecture from electromagnetic forces:\n\n| Ability | Magneto AI Capability |\n|---|---|\n| **Magnetokinesis** | Multi-agent orchestration — coordinate, delegate, merge |\n| **Force Field** | Security guardrails — block unsafe actions, protect secrets |\n| **Electromagnetic Sight** | Dependency & contradiction detection across the codebase |\n| **Telepathic Resistance** | Reject bad instructions — hallucination filtering, constraint enforcement |\n| **Telepathic Amplification** | Power boost when safe — higher autonomy for low-risk tasks |\n| **Sentinel Lock** | Enterprise approval workflows — human-in-the-loop for critical operations |\n\n---\n\n## 🚀 Quick Start\n\n### Install\n\n```bash\n# Install globally (recommended — use magneto without npx)\nnpm install -g magneto-ai\n\n# Or use without installing via npx\nnpx magneto-ai@latest init\n```\n\n### Initialize in Your Project\n\n```bash\nmagneto init\n```\n\nWith power packs:\n\n```bash\nmagneto init --with typescript nextjs ai-platform --adapter graphify\nmagneto init --adapter openclaw   # wire Magneto as OpenClaw governance layer\n```\n\n### Validate Setup\n\n```bash\nmagneto doctor\n```\n\n### Plan & Run a Task\n\n```bash\n# Tasks can be written as Markdown (.md), YAML (.yaml), or JSON (.json)\nmagneto plan examples/tasks/checkout-mismatch.md\nmagneto run examples/tasks/checkout-mismatch.md --runner openai --mode assist\n```\n\n### Merge Agent Outputs\n\n```bash\nmagneto merge .magneto/cache --format markdown\n```\n\n---\n\n## ⚡ See Magneto in Action\n\nSix real scenarios — pick the one that matches your stack.\n\n---\n\n### 🖥 Scenario 1 — Next.js Frontend Feature\n\nYou have a Next.js + TypeScript project. You need a new analytics dashboard. One command sets up Magneto, then it plans and executes with 4 parallel agents.\n\n```bash\n$ magneto init --with typescript nextjs\n[magneto] Initializing Magneto AI...\n[magneto] ✓ Detected stack: TypeScript · Next.js 14 · React 18\n[magneto] ✓ Base scaffolding complete  (.magneto/, .github/agents/, .vscode/mcp.json)\n[magneto] ✓ Power packs loaded         (typescript, nextjs)\n[magneto] ✓ Magneto AI initialized successfully!\n\n$ magneto plan tasks/add-dashboard.md\n[magneto] Planning task: add-dashboard\n[magneto] Classification: feature-implementation\n[magneto] Security Risk: low ✓\n[magneto] Agents: orchestrator, backend, frontend, tester\n[magneto] Subtasks:\n[magneto]   1. Design analytics API route    → backend\n[magneto]   2. Build dashboard components    → frontend\n[magneto]   3. Write integration tests       → tester\n[magneto] ✓ Plan saved to .magneto/cache/plan-add-dashboard.json\n\n$ magneto run tasks/add-dashboard.md --stream\n[magneto] ⚡ Executing with 4 agents in parallel...\n[orchestrator] Decomposing into 3 subtasks...\n[backend]      Implementing API routes...         ████████░░  80%\n[frontend]     Building dashboard components...  ██████░░░░  60%\n[tester]       Generating test suite...           ██████████ 100%\n[backend]      API routes complete ✓\n[frontend]     Dashboard components complete ✓\n[magneto] ✓ Task completed — 12 files, 847 lines, 31 tests generated\n\n$ magneto merge .magneto/cache --format markdown\n[magneto] ✓ Merged 4 agent outputs → .magneto/reports/add-dashboard.md\n[magneto]   Findings: 3 · Risks: 0 · Confidence: 0.94\n```\n\n**What Magneto caught that raw Copilot missed:** missing `'use client'` on a component using `useState`, a server/client boundary violation that would have caused a hydration error at runtime.\n\n---\n\n### 🐍 Scenario 2 — Python FastAPI Security Audit\n\nYou're about to deploy a FastAPI service. Magneto scans for the 10 most common FastAPI security mistakes before a single line ships.\n\n```bash\n$ magneto init --with python fastapi\n[magneto] ✓ Detected stack: Python 3.12 · FastAPI 0.110 · Pydantic v2\n[magneto] ✓ Power packs loaded  (python, fastapi)\n\n$ magneto run tasks/pre-deploy-audit.md --mode observe\n[magneto] ⚡ Running security audit (observe mode — read-only)...\n[magneto] Scanning 24 Python files...\n\n[python-pack]   py-hardcoded-secret     FOUND   src/config.py:14\n                → SECRET_KEY = \"my-super-secret-key-12345\"\n[python-pack]   py-shell-true           FOUND   src/utils/runner.py:38\n                → subprocess.run(cmd, shell=True)  ← command injection risk\n[fastapi-pack]  fastapi-cors-wildcard   FOUND   src/main.py:22\n                → allow_origins=[\"*\"] + allow_credentials=True  ← blocked by browsers\n[fastapi-pack]  fastapi-debug-true      FOUND   src/main.py:7\n                → FastAPI(debug=True)  ← leaks tracebacks in production\n[python-pack]   py-requests-no-timeout  FOUND   src/integrations/stripe.py:51\n                → requests.post(url, json=payload)  ← hangs on unresponsive server\n\n[magneto] ✓ Audit complete — 5 issues across 4 files (3 error, 2 warning)\n[magneto] ✓ Report saved to .magneto/reports/pre-deploy-audit.md\n\n$ magneto run tasks/pre-deploy-audit.md --mode assist\n[magneto] Generating fixes for 5 issues...\n[magneto] ✓ Fix suggestions written to .magneto/reports/pre-deploy-fixes.md\n```\n\n**Time to catch this without Magneto:** 2–3 hours of manual code review, or one very bad production incident.\n\n---\n\n### ☕ Scenario 3 — Java Spring Boot Refactor\n\nYour Spring Boot service is mysteriously slow and occasionally throws `LazyInitializationException`. Magneto finds the N+1 query, the missing transaction boundary, and the exposed actuator — all in seconds.\n\n```bash\n$ magneto init --with java spring-boot\n[magneto] ✓ Detected stack: Java 21 · Spring Boot 3.2 · PostgreSQL\n[magneto] ✓ Power packs loaded  (java, spring-boot)\n\n$ magneto run tasks/perf-audit.md --mode observe --stream\n[magneto] ⚡ Scanning 67 Java files...\n\n[spring-pack]  spring-open-in-view         FOUND   src/main/resources/application.yml:12\n               → spring.jpa.open-in-view=true  ← N+1 queries in every controller\n[spring-pack]  spring-transactional-priv   FOUND   src/service/OrderService.java:84\n               → @Transactional on private method  ← proxy bypass, no transaction applied\n[spring-pack]  spring-actuator-all-exposed FOUND   src/main/resources/application-prod.yml:4\n               → management.endpoints.web.exposure.include=*  ← heapdump publicly accessible\n[java-pack]    java-catch-throwable        FOUND   src/service/PaymentService.java:127\n               → catch (Throwable t)  ← swallows OutOfMemoryError and InterruptedException\n[java-pack]    java-unsafe-deserialize     FOUND   src/legacy/MessageParser.java:33\n               → new ObjectInputStream(input)  ← RCE risk on untrusted data\n\n[magneto] ✓ Found 5 issues across 5 files (3 error, 2 warning)\n[magneto] ⚡ Orchestrating fixes with 3 agents...\n[backend]  Fixing application.yml + OrderService...  ██████████ 100%\n[tester]   Updating integration tests...              ██████████ 100%\n[magneto] ✓ 6 files changed — estimated 60–80% reduction in DB query count\n```\n\n---\n\n### ☁️ Scenario 4 — AWS Infrastructure Review\n\nYou've written Terraform for a new microservice. Before `terraform apply`, Magneto scans every `.tf` file for the 16 AWS security checks — IAM, S3, SGs, encryption, hardcoded keys.\n\n```bash\n$ magneto init --with aws\n[magneto] ✓ Detected stack: Terraform 1.7 · AWS Provider 5.x\n[magneto] ✓ Power packs loaded  (aws)\n\n$ magneto run tasks/infra-pre-deploy.md --mode observe\n[magneto] ⚡ Scanning Terraform files (31 .tf files)...\n\n[aws-pack]  aws-iam-wildcard-action    FOUND   infra/iam.tf:18\n            → Action: \"*\", Resource: \"*\"  ← grants all AWS permissions\n[aws-pack]  aws-s3-public-acl          FOUND   infra/storage.tf:7\n            → acl = \"public-read\"  ← bucket contents publicly accessible\n[aws-pack]  aws-sg-ssh-open            FOUND   infra/networking.tf:44\n            → cidr_blocks = [\"0.0.0.0/0\"] on port 22  ← SSH open to internet\n[aws-pack]  aws-rds-unencrypted        FOUND   infra/database.tf:29\n            → storage_encrypted = false  ← RDS data unencrypted at rest\n[aws-pack]  aws-hardcoded-access-key   FOUND   infra/providers.tf:11\n            → access_key = \"AKIA...\"  ← hardcoded AWS key (rotate immediately)\n[aws-pack]  aws-lambda-no-timeout      FOUND   infra/lambda.tf:8\n            → No timeout set  ← unbounded execution, cost risk\n\n[magneto] ✗ 6 CRITICAL/HIGH issues found — deploy blocked pending review\n[magneto] ✓ Report: .magneto/reports/infra-pre-deploy.md\n```\n\n**Deploy blocked.** The hardcoded `AKIA` key alone would have triggered a GitHub secret scanner alert and potentially an AWS account compromise within minutes of pushing.\n\n---\n\n### 🔒 Scenario 5 — Regulated/Offline (Ollama — Zero Egress)\n\nYou work in healthcare, finance, or a classified environment. Source code cannot leave your machine. Magneto with the Ollama runner gives you full AI-powered reasoning with **zero data egress**.\n\n```bash\n# One-time setup — pull a model locally\n$ ollama pull qwen2.5-coder\n$ ollama serve\n\n# Tell Magneto to use Ollama\n$ export OLLAMA_HOST=http://localhost:11434\n$ export OLLAMA_MODEL=qwen2.5-coder\n\n$ magneto run tasks/audit-auth-module.md --runner ollama --stream\n[magneto] Runner: ollama (qwen2.5-coder @ localhost)\n[magneto] Data egress: none ✓  — all processing is local\n[magneto] ⚡ Pre-flight health check...\n[magneto] ✓ Ollama reachable · model qwen2.5-coder available\n\n[magneto] Executing task via local model...\n[ollama]  Analyzing auth module (4 files, 612 lines)...  ████████████ 100%\n\n[magneto] ✓ Task complete\n[magneto]   Findings: 4 · Risks: 1 · Tokens: 2,847 · Egress: none\n[magneto]   metadata.dataEgress = \"none\"  ← audit-ready tag on every result\n\n# Every result is tagged — verifiable in your audit log\n$ cat .magneto/audit/approvals.json | jq '.[-1].metadata.dataEgress'\n\"none\"\n```\n\n**No API key. No cloud call. No data leaving your network.** Same structured findings, same agent output format, runs on a $2,000 developer laptop.\n\n---\n\n### 🔍 Scenario 6 — Auto-Detect Any Stack\n\nDon't know which packs to install? Just run `magneto detect`. Magneto reads your project files and tells you exactly what's there — with confidence scores.\n\n```bash\n$ magneto detect\n[magneto] Scanning project structure...\n\nStack detected:\n  ✓ TypeScript      confidence: 0.98  (tsconfig.json, 47 .ts files)\n  ✓ Next.js         confidence: 0.95  (next.config.js, app/ router)\n  ✓ Python          confidence: 0.81  (requirements.txt, 12 .py files)\n  ✓ FastAPI         confidence: 0.79  (fastapi in requirements.txt)\n  ✓ AWS             confidence: 0.92  (14 .tf files, aws provider)\n\nRecommended packs:\n  → typescript   [available]   magneto init --with typescript\n  → nextjs       [available]   magneto init --with nextjs\n  → python       [available]   magneto init --with python\n  → fastapi      [available]   magneto init --with fastapi\n  → aws          [available]   magneto init --with aws\n\n$ magneto init --auto-install\n[magneto] Installing all 5 detected packs...\n[magneto] ✓ typescript · nextjs · python · fastapi · aws installed\n[magneto] ✓ Magneto AI ready — 67 checks active across your full stack\n```\n\n---\n\n## 📊 Raw Windsurf/Copilot vs Magneto AI — Token & Cost Benchmarks\n\n> **Same tasks. Measured token-by-token. Magneto AI uses 68% fewer tokens and delivers 3.5x faster.**\n\n### Real Task Comparison\n\n| Task | Raw Windsurf/Copilot | With Magneto AI | Token Savings | Cost Savings | Speed |\n|---|---|---|---|---|---|\n| **Bug fix** (checkout price mismatch) | 44,470 tokens / $0.156 | 24,400 tokens / $0.079 | **-45%** | **-49%** | **3.8x faster** |\n| **Feature** (Next.js auth flow) | 82,200 tokens / $0.247 | 29,700 tokens / $0.088 | **-64%** | **-64%** | **4.8x faster** |\n| **Security audit** (Java endpoints) | 96,500 tokens / $0.300 | 33,000 tokens / $0.098 | **-66%** | **-67%** | **3.0x faster** |\n| **Performance** (bundle optimization) | 77,000 tokens / $0.220 | 20,500 tokens / $0.060 | **-73%** | **-73%** | **3.5x faster** |\n| **Architecture** (microservice review) | 119,000 tokens / $0.370 | 29,000 tokens / $0.087 | **-76%** | **-76%** | **5.3x faster** |\n\n### Why the Difference?\n\n```\nRaw Windsurf/Copilot:\n  ├─ Loads 15–40 files (shotgun)          → bloated context\n  ├─ 5–10 back-and-forth exchanges        → wasted tokens on \"show me more\"\n  ├─ Re-explains project every session    → no memory\n  ├─ 1 generic agent pass                 → misses cross-cutting issues\n  └─ Manual cross-referencing             → slow and error-prone\n\nMagneto AI:\n  ├─ Loads 4–8 files (task-classified)    → 50–70% fewer tokens\n  ├─ 0 back-and-forth                     → all files pre-scoped\n  ├─ Persistent .magneto/memory/          → no re-explaining\n  ├─ 3–4 parallel role-focused agents     → catches contradictions\n  └─ Automatic merge + deduplication      → instant consolidated report\n```\n\n### Long-Term Savings\n\n| Team Size | Annual AI Cost (Raw) | Annual AI Cost (Magneto AI) | **Annual Savings** |\n|---|---|---|---|\n| 1 developer | $1,322 | $429 | **$893** |\n| 10 developers | $13,216 | $4,289 | **$8,927** |\n| 50 developers | $66,080 | $21,447 | **$44,633** |\n\n*Based on 15 AI tasks/developer/day at GPT-4o pricing. Excludes developer time savings.*\n\n### Developer Time Savings\n\n| Team Size | Hours Saved/Year | Value (@ $75/hr) |\n|---|---|---|\n| 1 developer | 480 hours | $36,000/year |\n| 10 developers | 4,800 hours | $360,000/year |\n| 50 developers | 24,000 hours | $1,800,000/year |\n\n> 📊 **[See full benchmark details with step-by-step token breakdowns →](./examples/METRICS.md)**\n\n---\n\n## �� Architecture\n\n<p align=\"center\">\n  <img src=\"docs/images/magneto-architecture.png\" alt=\"Magneto Architecture Diagram\" width=\"800\" />\n</p>\n\n<details>\n<summary>Text-based architecture diagram</summary>\n\n```\n┌─────────────────────────────────────────────────────┐\n│                   CLI (commander)                     │\n│   init │ refresh │ doctor │ plan │ run │ merge       │\n├─────────────────────────────────────────────────────┤\n│                   Core Engine                         │\n│   context │ security │ merge │ scaffold │ packs      │\n├──────────────┬──────────────┬────────────────────────┤\n│   Runners    │   MCP Server │   Power Packs          │\n│  ┌─────────┐ │  ┌──────────┐│  ┌──────────────────┐  │\n│  │ OpenAI  │ │  │plan_task ││  │ TypeScript        │  │\n│  │ Copilot │ │  │load_ctx  ││  │ Next.js           │  │\n│  │  Local  │ │  │merge_res ││  │ AI Platform       │  │\n│  │  Cloud  │ │  │sec_check ││  │ Azure             │  │\n│  └─────────┘ │  └──────────┘│  └──────────────────┘  │\n├──────────────┴──────────────┴────────────────────────┤\n│                  Adapter Layer                         │\n│            Graphify │ (extensible)                     │\n└─────────────────────────────────────────────────────┘\n```\n</details>\n\n---\n\n## 🛡 Security Engine\n\nThe security engine evaluates **every task** before execution:\n\n```typescript\nevaluateSecurity(task): {\n  securityRisk: \"low\" | \"medium\" | \"high\"\n  approvalRequired: boolean\n  telepathyLevel: 0 | 1 | 2 | 3\n  reasons: string[]\n  blockedActions: string[]\n  protectedPathsAccessed: string[]\n}\n```\n\n### Execution Modes\n\n| Mode | Description |\n|---|---|\n| `observe` | Read-only analysis, no changes |\n| `assist` | Suggestions only, human applies changes |\n| `execute` | Automated execution with guardrails |\n| `restricted` | Locked down — requires explicit approval for everything |\n\n### What Gets Checked\n\n- **Protected paths** — `.env`, `.pem`, `.key`, secrets directories\n- **Blocked actions** — database drops, destructive shell commands\n- **Dependency risk** — package changes, install operations\n- **Auth changes** — permission modifications, token operations\n- **Infrastructure** — deploy, migrate, infra-as-code changes\n\n---\n\n## � Spec-Driven Development\n\nMagneto ships pluggable support for the three leading SDD frameworks. On `magneto init` you're prompted to choose; on existing repos the framework is auto-detected.\n\n| Framework | Best for | Layout |\n|---|---|---|\n| **OpenSpec** *(default)* | Brownfield / existing code | `openspec/{project.md, specs/, changes/<name>/{proposal,design,tasks}.md}` — delta-based (ADDED/MODIFIED/REMOVED) |\n| **Spec Kit** | Greenfield / new projects | `.specify/constitution.md` + `specs/<slug>/{spec,plan,tasks}.md` — branch-per-spec |\n| **BMAD-METHOD** | Regulated / SOC2 audit | `bmad-core/agents/*.md` (Analyst→PM→Architect→SM→Dev→QA) + versioned PRDs |\n\n```bash\nmagneto sdd init                              # interactive prompt\nmagneto sdd new add-dark-mode \"Theme toggle\"  # scaffold a change\nmagneto sdd status                            # show active framework + changes\nmagneto sdd sync                              # reconcile spec ↔ code drift (CI: exit 1 on drift)\n```\n\n**Constitution-as-code.** The default constitution template enforces a **WHY → WHAT → HOW** rule format that LLMs actually follow (single-line \"don't do X\" rules are routinely ignored — see [EPAM Spec Kit case study](https://www.epam.com/insights/ai/blogs/using-spec-kit-for-brownfield-codebase)).\n\n**Drift reconciler.** Catches three drift kinds statically (no LLM call): `spec-only` (spec references missing files), `code-undocumented` (`src/` subtrees with no spec coverage), `mismatch` (tasks marked done that reference missing files). Writes `.magneto/sdd-drift.md`.\n\nReferences: [OpenSpec](https://openspec.dev) · [GitHub Spec Kit](https://github.com/github/spec-kit) · [BMAD-METHOD](https://docs.bmad-method.org)\n\n---\n\n## 📐 Sandbox & Isolation\n\nRun Magneto, OpenClaw, and AI-generated code inside an OS-level sandbox. Magneto auto-detects the best runtime and falls back transparently.\n\n| Profile | Filesystem | Network | Process | Use |\n|---|---|---|---|---|\n| `strict` | Read-only project | Allowlist (LLM APIs only) | `nobody`, no shell | Audits |\n| `standard` | RW project, denied `/etc /var /usr` | Allowlist + npm/pypi/maven | `magneto`, no sudo | Default for `execute` |\n| `dev` | RW project | Open | `magneto`, no sudo | Local dev |\n| `off` | Host | Host | Host | Trusted CI only |\n\n| Runtime | Platform | Mechanism |\n|---|---|---|\n| `docker` / `podman` | All | Container with cap-drop, read-only mounts, network policy |\n| `sandbox-exec` | macOS | Native Apple sandbox with `.sb` profile + port-based net allowlist |\n| `bwrap` | Linux | `bubblewrap` user namespace + bind mounts |\n| **`windows-sandbox`** | Windows 10/11 Pro | `.wsb` XML config + `WindowsSandbox.exe` |\n| **`wsl`** | Windows | `wsl.exe` with DNS-leak hardening (`--resolv-conf`) |\n\n```bash\nmagneto sandbox status                                   # detected runtimes + profiles\nmagneto sandbox build                                    # build the magneto-sandbox container\nmagneto sandbox run --profile strict -- magneto security audit\nmagneto sandbox shell --profile dev                      # interactive shell inside sandbox\nmagneto sandbox doctor                                   # validate setup\n```\n\n---\n\n## 🔐 Zero-Trust Memory Lock\n\n`.magneto/memory/` is the agent's persistent context. Tampering with it can poison every future agent run. Magneto locks it with cryptographic integrity:\n\n```bash\nmagneto memory lock                          # SHA-256 each file, sign manifest with HMAC\nmagneto memory lock --require-root           # only root may unlock\nmagneto memory verify                        # exit 1 on tamper\nmagneto memory unlock                        # owner unlocks; offline-only by default\nmagneto memory status\n```\n\n- **Manifest signature**: HMAC-SHA256 with a key derived from `~/.magneto-key + hostname + uid` — copying lock files between machines fails verification.\n- **Runtime gating**: while a task is running, `assertMemoryWritable()` blocks any memory mutation.\n- **Offline-only updates**: by default, `unlock` refuses to run when a network interface is up. Override with `--allow-online` (audited).\n- **chmod 0400** while locked. `git` ignores the lock files via `.gitignore`.\n\n---\n\n## ⚡ Power Skills (24 Built-in Commands)\n\nMagneto AI includes **24 power skills** — graph-grounded, multi-LLM, governance-enforcing commands that agents can invoke via slash commands or CLI:\n\n### Core Skills\n| Skill | CLI | Purpose |\n|-------|-----|---------|\n| `/think` | `magneto think` | Structured reasoning with chain-of-thought |\n| `/plan` | `magneto plan` | Strategic planning with dependencies |\n| `/review` | `magneto review` | Graph-aware code review with trace links |\n| `/investigate` | `magneto investigate` | Root-cause debugging with auto-freeze |\n| `/ship` | `magneto ship` | Release automation (sync, test, PR, trace) |\n| `/retro` | `magneto retro` | Sprint retrospective from audit log |\n| `/audit` | `magneto audit` | Read/verify tamper-evident audit log |\n| `/learn` | `magneto learn` | Memory management (patterns, bugs, decisions) |\n| `/guard` | `magneto guard` | Combined careful + freeze safety |\n\n### Traceability Skills\n| Skill | CLI | Purpose |\n|-------|-----|---------|\n| `/trace` | `magneto trace` | Requirement-to-code coverage analysis |\n| `/drift` | `magneto drift` | Detect spec-to-code drift |\n| `/qa` | `magneto qa` | Browser-based QA testing (Playwright) |\n\n### Cross-Model Skills\n| Skill | CLI | Purpose |\n|-------|-----|---------|\n| `/codex review` | `magneto codex review` | Multi-LLM review with convergence |\n| `/codex challenge` | `magneto codex challenge` | Adversarial code challenge |\n| `/codex consult` | `magneto codex consult` | Multi-model architectural consult |\n| `/codex backends` | `magneto codex backends` | Show configured LLM backends |\n\n### Safety Skills\n| Skill | CLI | Purpose |\n|-------|-----|---------|\n| `/careful` | `magneto careful` | Warn before destructive commands |\n| `/freeze` | `magneto freeze` | Lock edits to specific paths |\n| `/unfreeze` | `magneto unfreeze` | Release freeze lock |\n\n### Review Gates\n| Skill | CLI | Purpose |\n|-------|-----|---------|\n| `/plan-ceo-review` | `magneto plan-ceo-review` | Business readiness gate |\n| `/plan-design-review` | `magneto plan-design-review` | Architecture readiness gate |\n| `/plan-eng-review` | `magneto plan-eng-review` | Engineering readiness gate |\n\n### Operations Skills\n| Skill | CLI | Purpose |\n|-------|-----|---------|\n| `/autoplan` | `magneto autoplan` | Auto-generate plan from task |\n| `/benchmark` | `magneto benchmark` | Run performance benchmarks |\n| `/canary` | `magneto canary` | Canary deployment management |\n| `/land-and-deploy` | `magneto land-and-deploy` | Land PR and deploy |\n\n**Example usage:**\n```bash\nmagneto review --base main --sprint s-20260517\nmagneto ship --draft --skip-tests\nmagneto retro --week --output retro.md\nmagneto audit --verify --tail 50\nmagneto guard src/payments src/auth\n```\n\n---\n\n## 🧩 Power Pack System\n\nPower Packs add domain-specific intelligence to Magneto AI.\n\n### Built-in Packs\n\n| Pack | Category | What It Does |\n|---|---|---|\n| **TypeScript** | Language | Import graph analysis, type safety checks, `any` detection |\n| **Python** | Language | Type hints (PEP 484), security checks (eval/SQL injection/pickle), Django/FastAPI/Flask guidance |\n| **Next.js** | Framework | Server/client boundaries, hydration safety, routing validation |\n| **Java** | Language | Modern Java idioms (records/sealed/pattern matching/virtual threads), concurrency safety, security (RCE/SQLi/XXE) |\n| **FastAPI** | Framework | Pydantic validation, async correctness, CORS/auth security, lifespan hygiene |\n| **Spring Boot** | Framework | Spring Security review, JPA N+1 detection, transaction boundaries, actuator hardening |\n| **AI Platform** | Project Type | Prompt injection detection, RAG pipeline validation, token limits |\n| **AWS** | Cloud | IAM least-privilege, S3 public-exposure, SG wide-open ports, encryption at rest, Terraform/CDK practices |\n| **Azure** | Cloud | Infrastructure reasoning, RBAC validation, networking checks |\n\n### Using Packs\n\n```bash\n# Include during init\nmagneto init --with typescript nextjs\n\n# Packs are detected automatically on refresh\nmagneto refresh\n```\n\nPacks live in `.magneto/power-packs/` and contain:\n- `pack.json` — rules, checks, and configuration\n- `rules.md` — detailed reasoning guidelines for agents\n\n---\n\n## 🔌 Adapter System\n\nAdapters integrate external tools into Magneto AI's memory system.\n\n### Graphify Adapter\n\nImports dependency graph data from Graphify:\n\n```bash\nmagneto init --adapter graphify\n```\n\nReads from `.graphify-out/graph.json` and maps into Magneto AI memory.\n\n**Memory modes:**\n\n| Mode | Behavior |\n|---|---|\n| `internal-first` | Magneto AI's own analysis takes priority; Graphify supplements |\n| `external-first` | Graphify data takes priority; Magneto AI enriches it |\n\n### OpenClaw Adapter\n\nIntegrates Magneto AI as the **governance and reasoning layer for OpenClaw agents**. [OpenClaw](https://docs.openclaw.ai) is a self-hosted AI agent gateway that routes messages from Telegram, Slack, WhatsApp, Discord, and more to AI agents.\n\n```bash\nmagneto init --adapter openclaw\n```\n\nThis installs a **Magneto skill** into your OpenClaw project that teaches agents to use Magneto for all software engineering tasks:\n\n```\n.openclaw/\n  skills/\n    magneto.SKILL.md     ← teaches OpenClaw agents when/how to use Magneto\n  magneto-adapter.json   ← adapter config (minimal JSON)\n```\n\n**How it works:**\n\n```\nUser → Telegram/Slack/WhatsApp\n          ↓\n     OpenClaw Gateway\n          ↓\n     AI Agent (reads magneto.SKILL.md)\n          ↓\n     magneto analyze         ← understands the codebase\n     magneto plan task.md    ← structured plan + security check\n     magneto generate task.md ← scoped implementation prompt\n          ↓\n     Governed, secure AI response back to user\n```\n\nAfter running `magneto init --adapter openclaw`, restart your OpenClaw gateway:\n\n```bash\nopenclaw gateway restart\n```\n\nOpenClaw agents will now automatically use Magneto for task planning, security checks, and context loading on every engineering request.\n\n### Adapter Management Commands\n\nMagneto provides a full CLI for managing adapters after initialization:\n\n```bash\n# List available and installed adapters\nmagneto adapter list\n\n# Install an adapter\nmagneto adapter install claude\nmagneto adapter install manus --api-key=your_key_here\nmagneto adapter install antigravity\n\n# Configure an adapter (especially for API-based ones)\nmagneto adapter config manus\nmagneto adapter config manus --set apiKey --value xxx\nmagneto adapter config manus --set sync.autoPushTasks --value true\n\n# Validate all installed adapters\nmagneto adapter doctor\n\n# Remove an adapter\nmagneto adapter remove claude --force\n```\n\n### Claude Code Adapter\n\nInstall the Claude Code adapter to use `/magneto` commands directly in Claude Code:\n\n```bash\nmagneto adapter install claude\n```\n\nThis creates `.claude/` with:\n- `CLAUDE.md` — Project instructions\n- `skills/magneto/SKILL.md` — `/magneto` slash command\n\n### Google Antigravity Adapter\n\nInstall the Antigravity adapter for the Google Antigravity IDE:\n\n```bash\nmagneto adapter install antigravity\n```\n\nThis creates `.agents/` with Magneto skill files for `/magneto-*` commands.\n\n### Paperclip Adapter\n\nInstall the Paperclip adapter to expose all 24 Magneto skills as Paperclip tools with full governance integration:\n\n```bash\nmagneto init --adapter paperclip\n```\n\nThis creates a Paperclip plugin in `packages/paperclip-plugin/` that:\n- Registers all 24 Magneto skills as Paperclip tools\n- **Risk assessment** — Auto-evaluates risk level for each skill invocation\n- **Human-in-the-loop** — High-risk operations trigger Paperclip approval workflows\n- **Governance bridge** — CEO agents use Magneto for strategic decision gates\n- **Audit sync** — Tamper-evident audit log flows to Paperclip Activity\n- **Cost tracking** — LLM usage reported for budget control\n\n**Paperclip CEO agent with Magneto governance:**\n```yaml\nplugins:\n  - name: '@magneto/paperclip-plugin'\n    config:\n      magnetoPath: 'magneto'\n      syncAudit: true\n      governance:\n        autoApproveLowRisk: true\n        requireApprovalForRisk: medium\n\nagents:\n  - id: ceo-agent\n    name: \"CEO Agent\"\n    tools: [magneto.plan-ceo-review, magneto.guard, magneto.ship, magneto.audit]\n    permissions: [governance.read, governance.approve]\n    heartbeat:\n      on_issue_labeled:\n        # 1. Guard sensitive paths\n        - tool: magneto.guard\n          args: { paths: ['src/payments', 'src/auth'] }\n        \n        # 2. CEO review gate (requires human approval)\n        - tool: magneto.plan-ceo-review\n          args: { sprint: '{{issue.sprintId}}', strict: true }\n        \n        # 3. Ship with full audit trail (requires approval)\n        - tool: magneto.ship\n          args: { sprint: '{{issue.sprintId}}', base: main }\n        \n        # 4. Verify audit chain\n        - tool: magneto.audit\n          args: { verify: true }\n```\n\n**Risk levels:**\n- `magneto.audit`, `magneto.trace` — Low risk, auto-approved\n- `magneto.review`, `magneto.retro` — Medium risk, requires approval\n- `magneto.ship`, `magneto.guard` — High/Critical risk, requires CEO/board approval\n\nSee `packages/paperclip-plugin/` for full plugin source and example company configuration.\n\n### Manus AI Adapter\n\nInstall the Manus adapter for API-based integration:\n\n```bash\nmagneto adapter install manus\nmagneto adapter config manus  # Set your API key\n```\n\n---\n\n## 🤖 Copilot Integration\n\nMagneto AI generates full Copilot integration:\n\n### Agent Definitions (`.github/agents/`)\n\n- **magneto-orchestrator** — coordinates multi-agent tasks\n- **magneto-backend** — backend analysis specialist\n- **magneto-tester** — test generation and validation\n- **magneto-requirements** — requirements tracing\n\n### MCP Integration (`.vscode/mcp.json`)\n\nExposes tools to Copilot:\n- `plan_task` — generate execution plans\n- `load_context` — load project context\n- `merge_results` — merge agent outputs\n- `security_check` — validate security constraints\n\n---\n\n## 🌐 Runners\n\nMagneto selects a runner automatically via `detectAgentEnvironment()` — priority order: Cascade/Windsurf → Copilot → Antigravity → Gemini → OpenAI → Ollama (fallback).\n\n| Runner | How to activate | Data egress |\n|--------|----------------|-------------|\n| `openai` | Set `OPENAI_API_KEY` | OpenAI API |\n| `copilot` | Set `MAGNETO_COPILOT_CLOUD_TOKEN` | GitHub Copilot |\n| `cascade` | Auto-detected in Windsurf | Local process |\n| `gemini` | Set `GEMINI_API_KEY` | Google AI API |\n| `ollama` | Set `OLLAMA_HOST` or `MAGNETO_USE_OLLAMA` | **None — fully local** |\n\n### OpenAI Runner\n```bash\nmagneto run task.json --runner openai --mode assist\n```\nRequires `OPENAI_API_KEY`. Builds structured system prompt, parses JSON findings/risks, saves results to `.magneto/cache/`.\n\n### Ollama Runner\n```bash\nmagneto run task.md --runner ollama\n```\nNo API key. No data leaves your machine. Requires [Ollama](https://ollama.com) running locally. See [`docs/RUNNER-OLLAMA.md`](./docs/RUNNER-OLLAMA.md) for setup, hardware guidance, and team self-hosting.\n\n---\n\n## 📊 Why Magneto AI vs. Graphify?\n\n| Feature | Graphify | Magneto AI |\n|---|---|---|\n| Dependency graphs | ✅ Core strength | ✅ Via adapter or native |\n| Multi-agent orchestration | ❌ | ✅ Core feature |\n| Security guardrails | ❌ | ✅ Built-in engine |\n| Copilot integration | ❌ | ✅ Native agents + MCP |\n| OpenAI API runner | ❌ | ✅ Built-in |\n| Power pack system | ❌ | ✅ Extensible |\n| Task planning | ❌ | ✅ Plan → Execute → Merge |\n| Enterprise approvals | ❌ | ✅ Sentinel Lock system |\n\n**Magneto AI doesn't replace Graphify — it can consume it.** Use the Graphify adapter to import dependency data into Magneto AI's reasoning pipeline.\n\n---\n\n##  Project Structure\n\n```\nmagneto-ai/\n  src/\n    cli.ts                          # CLI entry point\n    commands/                       # CLI commands\n      init.ts                       #   magneto init\n      refresh.ts                    #   magneto refresh\n      doctor.ts                     #   magneto doctor\n      plan.ts                       #   magneto plan\n      run.ts                        #   magneto run\n      merge.ts                      #   magneto merge\n    core/                           # Core engine\n      scaffold.ts                   #   Project scaffolding\n      detect-packs.ts               #   Auto-detect power packs\n      context.ts                    #   Task classification & context\n      merge-results.ts              #   Agent output merging\n      security-engine.ts            #   Security evaluation\n      power-pack-loader.ts          #   Power pack loading\n      adapter-loader.ts             #   Adapter loading\n    runners/                        # Execution runners\n      types.ts                      #   Runner interface\n      openai.ts                     #   OpenAI API runner\n      copilot-local.ts              #   Copilot local agent runner\n      copilot-cloud.ts              #   Copilot cloud runner\n    mcp/                            # MCP server\n      server.ts                     #   HTTP MCP server\n      tools/                        #   MCP tool handlers\n        plan-task.ts\n        load-context.ts\n        merge-results.ts\n        security-check.ts\n    utils/                          # Utilities\n      logger.ts\n      paths.ts\n      fs.ts\n    templates/                      # Scaffolding templates\n      base/                         #   Base project templates\n      power-packs/                  #   Power pack templates\n  examples/\n    README.md                       # Examples overview + cost narrative\n    METRICS.md                      # Full token & cost benchmarks\n    tasks/                          # Standalone example tasks\n    nextjs-frontend/                # Next.js dashboard example\n      tasks/                        #   Auth, bundle, architecture tasks\n    java-backend/                   # Spring Boot API example\n      tasks/                        #   Payment, security, microservice tasks\n  package.json\n  tsconfig.json\n  README.md\n  LICENSE\n```\n\n---\n\n## 🧪 CLI Reference\n\n| Command | Description |\n|---|---|\n| `magneto init` | Initialize Magneto AI (auto-detects stack and prompts to install matching packs) |\n| `magneto init --with <packs>` | Initialize with specific power packs |\n| `magneto init --adapter <name>` | Initialize with an adapter |\n| `magneto init --auto-install` | CI mode: auto-install all detected packs without prompting |\n| `magneto init --no-suggest` | Skip auto-detection prompt |\n| `magneto detect` | Print detected stack (languages, frameworks, clouds) and recommend packs — read-only |\n| `magneto detect --json` | Detection output as JSON for tooling |\n| `magneto refresh` | Refresh configuration and detect packs |\n| `magneto doctor` | Validate setup and diagnose issues |\n| `magneto plan <task>` | Generate execution plan (.md, .yaml, or .json) |\n| `magneto plan <task> --dry-run` | Preview plan without saving |\n| `magneto run <task>` | Execute a task |\n| `magneto run <task> --runner openai` | Execute with specific runner |\n| `magneto run <task> --runner ollama` | Execute locally via Ollama (no API key, no data egress) |\n| `magneto run <task> --mode observe` | Execute in observe mode |\n| `magneto run <task> --approve-each` | Execute with step-by-step approval workflow |\n| `magneto merge <outputDir>` | Merge agent results |\n| `magneto merge <outputDir> --format md` | Merge as Markdown report |\n| `magneto generate <task>` | Generate scoped prompt for Windsurf/Copilot |\n| `magneto generate <task> --role backend` | Generate prompt for a specific agent role |\n| `magneto generate <task> --output prompt.md` | Save prompt to file |\n| `magneto analyze` | Analyze codebase and build structured memory |\n| `magneto analyze --include src lib` | Analyze specific directories only |\n| `magneto analyze --depth 3` | Limit directory scan depth |\n| `magneto skills list` | List all registered skills |\n| `magneto skills install <skill>` | Install a skill to IDE |\n| `magneto skills verify` | Verify all skills have SKILL.md |\n| `magneto review` | Graph-aware code review |\n| `magneto review --diff <file>` | Review specific diff |\n| `magneto investigate --error <msg>` | Debug with auto-freeze |\n| `magneto ship` | Release automation |\n| `magneto ship --draft` | Create draft PR |\n| `magneto retro --sprint <id>` | Sprint retrospective |\n| `magneto audit --verify` | Verify audit hash chain |\n| `magneto learn --save <text>` | Save a learning |\n| `magneto guard <paths...>` | Activate safety guard |\n| `magneto careful` | Enable careful mode |\n| `magneto freeze <paths...>` | Freeze paths for editing |\n| `magneto unfreeze` | Unfreeze all paths |\n| `magneto trace --coverage` | Show trace coverage |\n| `magneto drift --spec <file>` | Detect spec drift |\n| `magneto codex review` | Cross-model code review |\n| `magneto plan-ceo-review` | CEO review gate |\n\n---\n\n## 🛣 Roadmap\n\n### Shipped\n\n- [x] Interactive plan approval workflow\n- [x] Ollama Runner (local, zero-egress)\n- [x] Python, Java, FastAPI, Spring Boot, AWS Power Packs\n- [x] Streaming runner output (Ollama NDJSON streaming)\n- [x] **Project Glasswing** — AI Security Audit & Vulnerability Detection (SAST + secrets + OSV.dev dep scan + auto-fix)\n- [x] **Compliance engine** — SOC2 / HIPAA / GDPR / PCI-DSS evaluation\n- [x] **OS-level sandboxing** — Docker, Podman, sandbox-exec, bwrap, Windows Sandbox, WSL2\n- [x] **Zero-trust memory lock** — HMAC-signed manifest, offline-only mutation, runtime gating\n- [x] **Spec-Driven Development** — OpenSpec, Spec Kit, BMAD with shared reconciler\n- [x] Skill scanning via `snyk-agent-scan` (ToxicSkills detection)\n\n### In flight / next\n\n- [ ] VS Code extension with agent panel\n- [ ] Custom power pack authoring guide\n- [ ] Multi-repo orchestration\n- [ ] GitHub Actions integration\n- [ ] Cost tracking and budget limits\n- [ ] Plugin marketplace\n- [ ] Living-spec mode (bidirectional spec↔code updates during agent runs)\n\nFull detail: [ROADMAP.md](./ROADMAP.md).\n\n---\n\n## 📄 License\n\nMIT — see [LICENSE](./LICENSE)\n\n---\n\n## ☕ Support This Project\n\nMagneto AI is free and open source. If it saves you time, consider supporting continued development:\n\n<p align=\"center\">\n  <a href=\"https://buymeacoffee.com/rijuvashisht\">\n    <img src=\"https://cdn.buymeacoffee.com/buttons/v2/default-yellow.png\" alt=\"Buy Me A Coffee\" height=\"50\" />\n  </a>\n  &nbsp;&nbsp;\n  <a href=\"https://github.com/sponsors/rijuvashisht\">\n    <img src=\"https://img.shields.io/badge/Sponsor%20on%20GitHub-%E2%9D%A4-pink?style=for-the-badge&logo=github\" alt=\"GitHub Sponsors\" height=\"50\" />\n  </a>\n</p>\n\nYour support helps fund:\n- New integrations and power packs\n- Better documentation and examples\n- Long-term maintenance and security updates\n\n---\n\n<p align=\"center\">\n  <img src=\"docs/images/magneto-helmet.svg\" alt=\"Magneto\" width=\"40\" /><br/>\n  Built with ⚡ by the Magneto AI team.\n</p>\n","readmeFilename":"README.md"}