yana-rt 0.42.3

$ yana-ai
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│                                                                                                                                            │
│ v0.42.2 · Personal Agent OS                │ Tips for getting started                                                                      │
│ 162 agents · 1,983 skills                   │ yana-ai doctor                                                                               │
│ 66 rules · 49 hooks · 101 scripts          │ yana-ai init                                                                                  │
│ 826 checks · 9 gate layers                 │                                                                                               │
│                                            │ What's new                                                                                    │
│                                            │ v0.42.2 — WASM guard + automated publish pipeline                                            │
╰────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────╯

Yana AI is a personal agent operating system for AI coding tools — runtime safety hooks, memory tiers, 162 specialist agents, 1,983 skills, and a Rust runtime that intercepts dangerous AI actions before they execute.

Works with Claude Code, Cursor, Windsurf, Antigravity, Kiro, OpenCode, Zed, Gemini, GitHub Copilot, Aider, and more.

New in v0.42.2: yana-rt now runs in the browser — WebAssembly build via wasm-bindgen ships destructive-command guard to browser extensions, VS Code, and Node.js (npm install yana-rt). Publish pipeline fully automated — npm, PyPI, and crates.io all publish on tag push. Agent count reconciled to 162. Rule 70 added: context-faithfulness law enforcing provided data over training data.

→ Full documentation & demo

→ VISION.md · ARCHITECTURE.md · ROADMAP.md

What are the 162 agents? They are not 162 AI models running at the same time — they're predefined specialist roles (security, frontend, backend, testing, learning, daily assistant…) used for routing and task organization. In normal usage, only the agent required for the current task is activated; most requests use a single model and a single agent route. Generated from repository metrics Last updated: 2026-06-21

🤝 An invitation — try it yourself

Don't take this README's word for any of it. Install the engine, then ask your AI assistant to do something it shouldn't — and watch the gates catch it first:

npm install yana-ai && npx yana-ai-install   # wire the hooks (60 seconds)
yana-ai doctor .                                   # verify everything is wired

Then try: ask your agent to git push --force, pipe a script from the internet into bash, or read a .env file — every attempt is intercepted, explained, and logged. That moment is the whole pitch.

Built by one 17-year-old in Vietnam — which means real-world feedback is the most valuable thing you can give this project. If something blocks too much, too little, or confuses you: open an issue. Every report makes the gates sharper.

Installation

Requirements

• Node.js 18+ (for npm package)
• Git
• Any AI coding tool: Claude Code, Cursor, Windsurf, Aider, etc.

Method 1 — npm (recommended, 60 seconds)

npm install -g yana-ai          # install CLI globally
npx yana-ai-install             # wire hooks into current project
yana-ai doctor                  # verify everything is working

Method 2 — clone from source

git clone https://github.com/yanacuti1121/yana-ai.git
cd yana-ai
npm install
bash install.sh                 # copies hooks + config into your project
yana-ai doctor                  # verify

Method 3 — GitHub App (no CLI needed)

Install via npm and wire into your project in 60 seconds — see Method 1 above.

Verify

yana-ai doctor        # checks hook wiring, config integrity, gate health
yana-ai --version     # confirms version

After install, try asking your AI agent to run git push --force, pipe a remote script to bash, or access a .env file — every attempt is intercepted, explained, and logged.

Yana AI at a Glance

┌──────────────────────────────────────────────────────────────────┐
│                     Yana AI v0.42.2                        │
│      "The orchestration layer between humans and AI —            │
│        routing, safety, and context for every domain."           │
│                                                                  │
│        Built by Vũ Văn Tâm · 17 · Vietnam                       │
└──────────────────────────────────────────────────────────────────┘

graph TB
    %% ── Mission ──────────────────────────────────────────────────────────
    subgraph MISSION["🎯 Mission — AI coding agent safety layer"]
        direction LR
        AGENT["Agent wants\nto run a command"]
        GATE["9-layer gate\nintercepts every call"]
        OUT["Execute ✅\nor BLOCK + log 🚫"]
        AGENT --> GATE --> OUT
    end

    %% ── Gate layers ──────────────────────────────────────────────────────
    subgraph GATES["🔒 9-Layer Gate System (L1 → L9)"]
        direction LR
        G1["L1\nAnti-evasion\nbase64, pipe-to-shell"]
        G2["L2\nShell sanitize\nquoting, metacharacters"]
        G3["L3\nEgress / SSRF\nprivate IPs blocked"]
        G4["L4\nSupply chain\ntyposquatting, CVEs"]
        G5["L5\nBlast radius\ndestructive scope cap"]
        G6["L6\nPermission tier\nagent authority check"]
        G7["L7\nCode signing\nECDSA-P256"]
        G8["L8\nMerkle audit\nhash-chain, tamper-proof"]
        G9["L9\nSovereign overlord\nhuman veto / freeze swarm"]
        G1 --> G2 --> G3 --> G4 --> G5 --> G6 --> G7 --> G8 --> G9
    end

    %% ── Core engine ──────────────────────────────────────────────────────
    subgraph CORE["⚙️ Core Engine"]
        direction TB
        SKILLS["📚 1,983 skills\nSKILL.md workflow defs\n(frontend, backend, AI, K8s, sec...)"]
        AGENTS["🤖 162 specialist agents\n(planner, security-auditor,\nhoc-tap, daily-assistant...)"]
        RULES["📜 65 enforced rules\n(security, git, UI, TypeScript,\nAPI security, core-lock...)"]
        HOOKS["🪝 46 hooks\nPreToolUse · PostToolUse · Stop\n(guard-destructive, truth-gate...)"]
        CMDS["⚡ 164 slash commands\n/audit · /scan · /route\n/tdd-cycle · /simplify..."]
        BUS["🚌 Agent message bus\nJSON + ECDSA sig\nreplay-protected, BFT consensus"]
        MEM["🧠 Memory tiers\nL1 permanent · L2 session\nMerkle-chained, AES-256-GCM"]
    end

    %% ── Rust runtime ─────────────────────────────────────────────────────
    subgraph RT["⚡ Rust Runtime — yana-rt"]
        direction LR
        SCAN["scan · hunt · fix\nVulnerabilities, OWASP,\nsupply chain — 1256× faster"]
        ROUTE["route · mission\nTask classifier → simple/\ncomplex/external dispatch"]
        VAULT["graph · vault · doctor\nKnowledge graph,\nskill search, health check"]
    end

    %% ── Tools ────────────────────────────────────────────────────────────
    subgraph TOOLS["🛠️ Tools — sub-projects"]
        direction LR
        YANA["yana-ai ✅\nZero-dep Node.js web UI\nAnthropic · Groq · Gemini · OpenAI\nSkill routing · SSE streaming"]
        CODEXMATE["codexmate\nOpenAI Codex integration\nVietnamese patch"]
        MOSS["moss-tts-nano\nTTS engine"]
        FINETUNE["finetune-vi\nVietnamese LLM fine-tuning"]
    end

    %% ── Harness adapters ─────────────────────────────────────────────────
    subgraph HARNESS["🔌 Harness Adapters (15)"]
        direction LR
        H1["Claude Code\nCursor · Zed"]
        H2["Gemini · Copilot\nAider · OpenCode"]
        H3["Cloudflare Workers\nGitHub Actions"]
    end

    %% ── Active branches ──────────────────────────────────────────────────
    subgraph BRANCHES["🌿 Active Branches"]
        direction LR
        BMAIN["main ✅\nv0.42.0 — stable"]
        BVDEV["v1.8.0-dev\nnext release (in progress)"]
        BCF["cloudflare/workers-autoconfig\nWorkers zero-config setup"]
        BCX["codex/fix-hello-bug-in-bn\nCodex compatibility"]
    end

    %% ── Product funnel ───────────────────────────────────────────────────
    subgraph FUNNEL["📣 Product Funnel — 'Scan first. Guard later.'"]
        direction LR
        F1["① yana-ai audit .\n30s · no learning needed\nScan any repo for AI agent risks"]
        F2["② Policy Kit\nAdopt safe configs piece by piece\n(CLAUDE.md · .mcp.json · CI gates)"]
        F3["③ Full Control Layer\nAll 9 gates · 162 agents\nMerkle log · Sovereign veto"]
        F1 --> F2 --> F3
    end

    %% ── Connections ──────────────────────────────────────────────────────
    MISSION --> GATES
    GATES --> CORE
    CORE --> RT
    CORE --> TOOLS
    CORE --> HARNESS

Reading the diagram: every AI tool call flows MISSION → GATES → CORE. The Rust runtime (yana-rt) accelerates the scanner. Sub-project tools (yana-web etc.) use the same gate system. Branches show active development fronts.

The problem

AI coding agents make mistakes. They rm -rf the wrong directory. They push force to main. They hallucinate test results. They commit secrets. By the time you notice, the damage is done.

Yana AI sits between the agent and your system — every tool call passes through a 9-layer safety gate before execution.

How it works

Agent wants to run a command
         ↓
[L1] Anti-evasion scan       — blocks base64 decode+exec, pipe-to-shell
[L2] Shell sanitization      — quotes all variables, strips metacharacters
[L3] Egress check            — blocks SSRF, private IP ranges, metadata endpoints
[L4] Supply chain gate       — vets every package install (typosquatting, CVEs)
[L5] Blast radius check      — caps destructive scope
[L6] Permission tier check   — verifies agent authority level
[L7] Signature verification  — ECDSA-P256 on generated code
[L8] Merkle audit log        — append-only, tamper-detected hash chain
[L9] Sovereign overlord gate — human veto, freeze swarm, full rollback
         ↓
Execute (or block + log)

Numbers

Quick Install

→ npm install — npm install -g yana-ai

# Claude Code plugin — npx yana-ai-install wires the hooks
# (required: npm v12+ no longer runs postinstall scripts by default)
npm install yana-ai && npx yana-ai-install

# Python CLI
pip install yana-ai

# Rust runtime (1256x faster scanner)
cargo install yana-rt

# Verify everything is wired
yana-ai doctor .

Multi-harness support

Yana AI adapts to whichever tool you use:

bash core/scripts/switch-engine.sh cursor    # .cursorrules + 7 .cursor/rules/*.mdc
bash core/scripts/switch-engine.sh opencode  # OPENCODE.md
bash core/scripts/switch-engine.sh zed       # .zed/settings.json
bash core/scripts/switch-engine.sh gemini    # GEMINI.md
bash core/scripts/switch-engine.sh copilot   # .github/copilot-instructions.md
bash core/scripts/switch-engine.sh status    # check all 12 adapters

GitHub Action

Scan any repo's AI agent configuration on every PR — secrets, permissions, hook injection, MCP vulnerabilities.

# .github/workflows/yana-ai-scan.yml
- uses: yanacuti1121/yana-ai/.github/actions/scan@main
  with:
    fail-on: 'high'       # fail CI on HIGH or CRITICAL findings
    diff-only: 'true'     # scan only changed files on PRs
    comment-on-pr: 'true' # post findings summary as PR comment

Posts a comment on every PR:

🟠 Yana AI Security Scan — HIGH

| Metric  | Value  |
|---------|--------|
| Risk    | HIGH   |
| Score   | 58/100 |
| Findings| 3      |

→ Full workflow template

Rust runtime — yana-rt

23 subcommands. Zero Python dependency.

yana-ai scan .                        # security scan — secrets, CVEs, supply chain risks
yana-ai graph .                       # knowledge graph — file deps, import resolution
yana-ai vault search Q                # search 1,983 skills by keyword
yana-ai hunt .                        # hunt for security patterns (OWASP, injection, SSRF)
yana-ai fix .                         # auto-fix rule violations
yana-ai doctor .                      # full system health check
yana-ai map .                         # blast radius map — what can the agent touch?
yana-ai ci                            # run all gate checks (used in CI)
yana-ai route classify "fix auth bug" # classify task → simple/complex/external
yana-ai mission create "add-auth"     # create parallel agent mission

Benchmark: yana-ai scan on a 10k-file repo: 1256x faster than the Python equivalent.

Safety architecture

core/
├── hooks/          # 46 PreToolUse / PostToolUse / Stop hooks
├── rules/          # 65 enforced rules (security, correctness, UI, git)
├── scripts/        # safe-run.sh, verify-core-lock.sh, secure-logger.sh
├── gates/          # truth_gate.md, action_gate.md
├── agents/         # 162 specialist agent definitions
├── skills/         # 1,983 SKILL.md files
├── config/
│   ├── core-lock.json    # SHA-256 manifest — 220 core files pinned
│   └── skills-lock.json  # skill content hashes
└── memory/
    ├── L1_atomic/  # permanent facts — persist across sessions
    └── L2_session/ # session state — auto-expires

Key properties:

• Merkle audit chain — every action logged, tamper-detected
• Core-lock integrity — SHA-256 manifest detects drift, deletion, and rule injection in core/
• BFT consensus — 3-of-N vote required for core infrastructure writes
• Sovereign overlord — human can freeze all 162 agents instantly
• Honeypot layer — decoy files/env vars catch compromised agents

What it looks like in practice

# Agent tries: git push --force origin main
[yana-ai/02-terminal-validator] BLOCKED — force push prohibited
  Command : git push --force origin main
  Gate    : L1
  Fix     : Run gate checks first, then push without --force

# Agent tries: curl http://169.254.169.254/latest/meta-data/
[yana-ai/network-egress] BLOCKED — SSRF target detected
  Host    : 169.254.169.254
  Gate    : L3
  Exit    : 3

# Agent tries to install unvetted package
[yana-ai/dependency-vetting] BLOCKED — unvetted package install
  Package : req-uests@2.28.0
  Reason  : typosquatting (similar to 'requests')
  Gate    : L4

Yana AI

Live →

Yana is the first interface built on Yana AI core — a web UI that lets anyone chat with AI, switch providers, and use skill routing without knowing anything about the infrastructure underneath.

User → Yana AI → Yana AI Core (Router · Safety · Context) → Model

• Zero signup — bring your own API key
• 🔐 Encrypted key vault — keys stored AES-256-GCM, master key non-extractable (WebCrypto + IndexedDB), never plaintext
• Multi-provider: Anthropic · Groq · Gemini · OpenAI · DeepSeek · OpenRouter · 9Router · Ollama

Provider setup — bring your own key, keys encrypted locally (never sent to Yana AI):

• 📊 100% real data — live provider stats, L1 memory garden, audit-log health panel; zero demo numbers
• Skill routing built in — type naturally, Yana AI dispatches the right agent
• Non-coding use cases: learning (Socratic learning assistant), daily work (summarize / plan / draft)
• SSE streaming, mobile-friendly · Electron desktop shell (tools/yana-desktop)

If Yana AI is the power grid, Yana is the first building plugged into it.

Built by one person

One person. No team. No funding.

• Hook architecture, safety gates, Python CLI
• Rust runtime (yana-rt), 162 agents, 1,983 skills, multi-harness support
• 15 harness adapters (Claude Code, Cursor, Windsurf, Antigravity, Kiro, Zed, Gemini, Copilot, Aider…)

The 1,983 skills cover: frontend, backend, AI/LLM, security, Kubernetes, WebAssembly, DevOps, databases, testing, and more. Two new agent personas cover non-coding use cases: learning (hoc-tap) and daily productivity (daily-assistant).

Add Yana AI to your repo

Static badge — paste into your README:

[![Protected by Yana AI](https://img.shields.io/badge/protected%20by-Yana AI%20ENGINE-ff6b35?style=for-the-badge)](https://github.com/yanacuti1121/yana-ai)

Dynamic audit badge — shows live security score:

yana-ai badge .           # prints badge markdown with current score
yana-ai badge . --json    # machine-readable output

GitHub Action — scan every PR automatically:

- uses: yanacuti1121/yana-ai/.github/actions/scan@main
  with:
    fail-on: 'high'

→ Full workflow template

Yana task router

Every task is classified before execution — no more guessing whether to handle it inline or dispatch an agent.

yana-ai route classify "implement JWT refresh token"
# → { "route": "complex", "gate": "harness", "confidence": 0.36,
#     "suggested_agents": ["security-engineer", "backend-developer"] }

yana-ai route classify "xem git log 10 commit"
# → { "route": "simple", "gate": "auto", "confidence": 0.43 }

yana-ai route classify "deploy to production"
# → { "route": "external", "gate": "confirm", "confidence": 0.30 }

Five routes:

• simple → Yana handles directly (read-only, no agents needed)
• skill → matched against 1,983-entry index, dispatches exact skill agent
• learn → routes to hoc-tap — Socratic learning assistant (triggers on "learn", "explain", "why" — English and Vietnamese)
• daily → routes to daily-assistant — summarize / plan / draft (triggers on "summarize", "write an email", "make a plan" — English and Vietnamese)
• complex → dispatch specialist agent(s) with scoped brief
• external → stop, confirm with human before proceeding

Domain-aware agent selection: auth tasks → security-engineer, database → database-expert, UI → frontend-developer + ui-ux-designer.

Mission dispatcher

Wave-based parallel orchestration with dependency resolution — built in Rust, zero Python.

# 1. Create mission
MID=$(yana-ai mission create "implement-auth" | awk '/id:/{print $2}')

# 2. Declare tasks with dependencies
yana-ai mission task $MID "design-schema"   --agent database-expert --produces schema.sql
yana-ai mission task $MID "implement-auth"  --agent backend-developer \
  --consumes schema.sql --produces src/auth.ts
yana-ai mission task $MID "write-tests"     --agent test-engineer \
  --consumes src/auth.ts --produces tests/auth.test.ts

# 3. Dispatch wave 1 — only tasks whose dependencies are satisfied
yana-ai mission dispatch $MID --max-parallel 3
# → JSON briefs for each ready agent

# 4. Mark complete, dispatch next wave
yana-ai mission done $MID "design-schema" --evidence schema.sql
yana-ai mission dispatch $MID  # → wave 2 unlocked

# Cancel / retry stuck tasks
yana-ai mission cancel $MID "implement-auth"
yana-ai mission retry  $MID "write-tests"

Tasks marked Running on dispatch — re-running dispatch never double-dispatches the same task.

Multi-agent launcher

Launch multiple agents in parallel with hard limits and a kill switch:

# Launch 3 agents, at most 3 running in parallel
bash core/scripts/multi-agent-launch.sh start \
  --agents "scanner,auditor,qa-team" \
  --concurrency 3

# Real-time status
bash core/scripts/multi-agent-launch.sh status

# Stop one specific agent
bash core/scripts/multi-agent-launch.sh kill scanner

# Kill switch — stop everything immediately
bash core/scripts/multi-agent-launch.sh kill all

# Tail an agent's log
bash core/scripts/multi-agent-launch.sh log auditor

Or drive it from a task-list file:

# tasks.txt — one line per task: agent_name:task description
echo "scanner:scan the whole repo
auditor:check the hooks
qa-team:run the test suite" > tasks.txt

bash core/scripts/multi-agent-launch.sh start --tasks-file tasks.txt --concurrency 4

Sample output:

═══ Yana AI Multi-Agent Launcher ═══
  Agents     : 3
  Concurrency: 3 (max running in parallel)
  Kill switch: bash multi-agent-launch.sh kill all

[LAUNCH] scanner → scan the whole repo    PID 12341
[LAUNCH] auditor → check the hooks        PID 12342
[LAUNCH] qa-team → run the test suite     PID 12343

[OK] Launched 3/3 agents

162 specialist roles defined in repo config 1,983 skill definitions discovered by repository scan 10,331 files, measured on 2026-06-21

Contact

Vũ Văn Tâm · Vietnam · 17

🇻🇳 Tiếng Việt · 🇰🇷 한국어 · 🇨🇳 中文

Full translations of this document: README.vi.md (Tiếng Việt) · README.ko.md (한국어) · README.zh.md (中文)