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YAMTAM

YAMTAM ENGINE

The orchestration layer between humans and AI — routing, safety, and context for every domain.

Built by Vũ Văn Tâm · 17 · Vietnam · 1,034,519 lines

English · 🇻🇳 Tiếng Việt

CI


YAMTAM ENGINE is a personal agent operating system for AI coding tools — runtime safety hooks, memory tiers, 97 specialist agents, 3,518 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.

YAMTAM gate system blocking rm -rf, pipe-to-shell, prompt injection and an unapproved production delete — live recording

New in v0.41.0: Yana task router — auto-classifies every task into simple/complex/external/learn/daily and dispatches agents. Yana AI now runs on 100% real data — encrypted key vault (AES-256-GCM), live provider stats, real L1 memory and audit-log dashboard. Mission dispatcher — wave-based parallel agent orchestration, built in Rust. Core-lock — SHA-256 integrity manifest pinning 216 core files against tampering (rule 67).

Full documentation & demo · GitHub Marketplace

VISION.md · ARCHITECTURE.md · ROADMAP.md

What are the 97 agents? They are not 97 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: 2026-06-10


🤝 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 yamtam-engine && npx yamtam-install   # wire the hooks (60 seconds)
yamtam 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.


YAMTAM at a Glance

┌──────────────────────────────────────────────────────────────────┐
│                     YAMTAM ENGINE v0.41.0                        │
│      "The orchestration layer between humans and AI —            │
│        routing, safety, and context for every domain."           │
│                                                                  │
│        Built by Vũ Văn Tâm · 17 · Vietnam · 1M+ lines            │
└──────────────────────────────────────────────────────────────────┘
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["📚 3,518 skills\nSKILL.md workflow defs\n(frontend, backend, AI, K8s, sec...)"]
        AGENTS["🤖 97 specialist agents\n(planner, security-auditor,\nhoc-tap, daily-assistant...)"]
        RULES["📜 64 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 — yamtam-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 ✅\nv0.41.0 — 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 yamtam 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 · 97 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 (yamtam-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.

YAMTAM 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

🧩 Skills 3,518 workflow skill definitions
🤖 Agents 97 specialist agents
📜 Safety rules 63 enforced rules
🪝 Hooks 46 pre/post-execution hooks
⚡ Slash commands 164
🔌 Harness adapters 15 (Claude Code, Cursor, Windsurf, Antigravity, Kiro, OpenCode, Zed, Gemini, Copilot, Aider...)
🦀 Rust subcommands 19 (scan, graph, vault, route, mission, hunt, fix, doctor...)
✅ Rule checks in CI 826
📦 Total codebase 1,034,519 lines · 5,762 files

Quick Install

Install from GitHub Marketplace — one click, official listing.

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

# Python CLI
pip install yamtam-engine

# Rust runtime (1256x faster scanner)
cargo install yamtam-rt
# Verify everything is wired
yamtam doctor .

Multi-harness support

YAMTAM 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/yamtam-scan.yml
- uses: phamlongh230-lgtm/yamtam-engine/.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:

🟠 YAMTAM Security Scan — HIGH

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

Full workflow template


Rust runtime — yamtam-rt

19 subcommands. Zero Python dependency.

yamtam scan .                        # security scan — secrets, CVEs, supply chain risks
yamtam graph .                       # knowledge graph — file deps, import resolution
yamtam vault search Q                # search 3,518 skills by keyword
yamtam hunt .                        # hunt for security patterns (OWASP, injection, SSRF)
yamtam fix .                         # auto-fix rule violations
yamtam doctor .                      # full system health check
yamtam map .                         # blast radius map — what can the agent touch?
yamtam ci                            # run all gate checks (used in CI)
yamtam route classify "fix auth bug" # classify task → simple/complex/external
yamtam mission create "add-auth"     # create parallel agent mission

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


Safety architecture

core/
├── hooks/          # 46 PreToolUse / PostToolUse / Stop hooks
├── rules/          # 64 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/         # 95 specialist agent definitions
├── skills/         # 3,518 SKILL.md files
├── config/
│   ├── core-lock.json    # SHA-256 manifest — 216 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 97 agents instantly
  • Honeypot layer — decoy files/env vars catch compromised agents

What it looks like in practice

# Agent tries: git push --force origin main
[yamtam/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/
[yamtam/network-egress] BLOCKED  SSRF target detected
  Host    : 169.254.169.254
  Gate    : L3
  Exit    : 3

# Agent tries to install unvetted package
[yamtam/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 YAMTAM 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 → YAMTAM 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 (Llama4 · Qwen3 · Gemma2) · Gemini 2.5 · OpenAI · DeepSeek · OpenRouter
  • 📊 100% real data — live provider stats, L1 memory garden, audit-log health panel; zero demo numbers
  • Skill routing built in — type naturally, YAMTAM 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 YAMTAM 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 (yamtam-rt), 97 agents, 3,518 skills, multi-harness support
  • 15 harness adapters (Claude Code, Cursor, Windsurf, Antigravity, Kiro, Zed, Gemini, Copilot, Aider…)

The 3,518 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 YAMTAM to your repo

Static badge — paste into your README:

[![Protected by YAMTAM](https://img.shields.io/badge/protected%20by-YAMTAM%20ENGINE-ff6b35?style=for-the-badge)](https://github.com/phamlongh230-lgtm/yamtam-engine)

Dynamic audit badge — shows live security score:

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

GitHub Action — scan every PR automatically:

- uses: phamlongh230-lgtm/yamtam-engine/.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.

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

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

yamtam 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 3,518-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=$(yamtam mission create "implement-auth" | awk '/id:/{print $2}')

# 2. Declare tasks with dependencies
yamtam mission task $MID "design-schema"   --agent database-expert --produces schema.sql
yamtam mission task $MID "implement-auth"  --agent backend-developer \
  --consumes schema.sql --produces src/auth.ts
yamtam 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
yamtam mission dispatch $MID --max-parallel 3
# → JSON briefs for each ready agent

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

# Cancel / retry stuck tasks
yamtam mission cancel $MID "implement-auth"
yamtam 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:

═══ YAMTAM 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

License

Apache 2.0 — free forever.


Contact

Vũ Văn Tâm · Vietnam · 17

Email phamlongh230@gmail.com
Website phamlongh230-lgtm.github.io/yamtam-engine
GitHub phamlongh230-lgtm
Yana AI yamtam-engine-production.up.railway.app

🇻🇳 Tiếng Việt

Bản dịch tiếng Việt đầy đủ của tài liệu này: README.vi.md

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