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@ratna3 ratna3 commented Feb 17, 2026

🃏 The Joker — Agentic Terminal v1.1.1

Pull Request: RK-Dev-Betamain

Full-stack build of The Joker Agentic Terminal — an autonomous, AI-powered terminal that understands natural language, scrapes the web, generates complete projects, performs OSINT reconnaissance, and deploys applications.


📊 PR Stats

Metric Value
Commits 29
Files Changed 103
Lines Added 55,255+
Lines Removed 528
Test Suites 22
Tests Passing 980
Test Coverage 80%+
Version 1.1.1

🎯 What This PR Achieves

This PR delivers the complete implementation of The Joker Agentic Terminal across 20 development phases, taking the project from initial setup to a fully-featured, tested, Dockerized AI agent with 29 registered tools.


🏗️ Development Phases

Phase 1–4: Foundation

  • Project Setup — TypeScript + Node.js boilerplate, tsconfig.json, ESLint, Prettier
  • LLM Integration — LM Studio API client (src/llm/client.ts), prompt templates, response parsing
  • Web Scraping Engine — Puppeteer-based browser automation with stealth mode, anti-detection, and data extraction
  • Agent System — Core autonomous agent loop with planner, executor, and session memory

Phase 5: Tool System & Execution

  • Tool registry with category support (SEARCH, SCRAPE, PROCESS, FILE, CODE)
  • Parameter validation and error handling
  • Dependency resolution and chaining

Phase 6: Terminal Interface & UX

  • Enhanced CLI system with chalk-powered display
  • Command handler architecture
  • Real-time progress tracking with ora spinners

Phase 7: Autonomous Agent Loop

  • JokerAgent with Think → Plan → Act → Observe cycle
  • Self-correction and iterative refinement
  • Goal detection, action planning, and synthesis

Phase 8: Data Processing & Output Formatting

  • 5 data processing tools: transform, clean, extract_patterns, convert, summarize
  • Rich terminal output with markdown and code block rendering

Phase 9: Error Handling & Resilience

  • Custom error types and centralized handler
  • Retry logic with exponential backoff
  • Circuit breaker pattern for external service calls

Phase 10: Testing Infrastructure

  • Jest configuration with 80%+ coverage
  • Mock system for browser and LLM dependencies
  • 191 → 980 tests across all phases

Phase 11: Code Generation Engine

  • LLM-powered code generation with template system
  • Framework templates: React, Next.js, Vue, Express
  • Component, page, and style generation

Phase 12: Project Scaffolding System

  • Full project scaffolding from natural language
  • npm install automation and directory structure creation
  • Integration with code generation engine

Phase 14: File System Indexer

  • AST-like parser for TypeScript/JavaScript files
  • File watcher with chokidar for real-time change detection
  • Dependency graph construction

Phase 15: Code Understanding & Context

  • Static analysis with code complexity scoring
  • Import/export resolution and symbol tracking

Phase 16: Multi-File Operations

  • Batch file creation and manipulation
  • Import management and automated refactoring (721 tests)

Phase 17: Progress Tracking System

  • Auto-generated progress.md reports
  • Task tracking with file change and build monitoring (784 tests)

Phase 18: Build & Development Workflow

  • Build manager, dev server orchestration
  • Error parsing and auto-fix pipeline (836 tests)

Phase 19: Testing & Quality Assurance

  • Comprehensive test generator (test-generator.ts)
  • Integration workflow tests
  • Full regression suite

Phase 20: Deployment Automation

  • Deployer module for Docker, Kubernetes, and CI/CD
  • Packager for production bundling

🌟 Headline Features

🎨 Vibe Coding Mode — Natural Language → Running App

Describe an app in plain English and The Joker builds it end-to-end:

🃏 joker > vibe Build me a portfolio website with dark mode and a contact form
  • LLM-powered prompt analysis → structured project spec
  • Automatic framework detection (React, Next.js, Vue, Express)
  • Full code generation for components, pages, and styles
  • Automated npm install + dev server launch + browser open
  • Live session refinement via HMR

Key files: src/agents/vibe-coder.ts, src/project/dev-server.ts


🔍 Hack Mode (Recon) — Automated OSINT

One-command passive domain reconnaissance:

🃏 joker > recon example.com
  • DNS records (A, AAAA, MX, TXT, NS, CNAME, SOA)
  • WHOIS lookup (registrar, dates, nameservers)
  • SSL/TLS certificate analysis
  • HTTP security header inspection
  • Tech stack detection (25+ signatures: React, Next.js, Vue, WordPress, Cloudflare, Vercel, AWS…)
  • Email and social link extraction
  • Full-page screenshot capture
  • Security score (0–100) and markdown report saved to ./reports/

Key file: src/tools/recon.ts


🖥️ TUI Dashboard — Real-Time Agent Visualization

Full-screen interactive terminal dashboard built with blessed:

  • Split-pane UI: Agent Thinking (left) + Tool Execution (right)
  • Live stats bar: state, elapsed time, message count, step progress, active model
  • Interactive input pane with key bindings (Tab, q, c, i, Esc)

Key file: src/cli/dashboard.ts


🧠 AirLLM Integration — 70B Models on 4GB RAM

Run 70B-parameter LLMs on commodity hardware via layer-wise inference:

  • Python sidecar server (airllm_server.py) wrapping models via OpenAI-compatible API
  • TypeScript bridge (src/llm/airllm-bridge.ts) with health checks and process management
  • LLM client factory (src/llm/factory.ts) for seamless backend switching
  • Backend selection prompt at startup (LM Studio vs AirLLM)
  • Configuration via .env: model, port, compression (none/4bit/8bit), max length

🐳 Docker Support

Production-ready containerization:

  • Multi-stage Dockerfile with Puppeteer + Chromium support
  • docker-compose.yml with volume mounts, host networking, and AirLLM sidecar port
  • .dockerignore for optimized builds
  • host.docker.internal for LM Studio communication from container

🔧 29 Registered Tools

Category Tools
Search web_search
Scrape scrape_page, extract_links, take_screenshot
Process transform, clean, extract_patterns, convert, summarize
File read_file, write_file, append_file, delete_file, list_dir, copy_file, move_file, file_exists, create_dir
Code generate_code, modify_code, scaffold_project, analyze_code
Recon recon (DNS, WHOIS, SSL, headers, tech stack, emails, socials, screenshot)
Vibe vibe (NL → running app pipeline)

📁 Architecture

theJoker/
├── src/
│   ├── index.ts                 # Entry point & CLI command registration
│   ├── agents/                  # Agent loop, planner, executor, memory, vibe-coder
│   ├── cli/                     # Terminal, dashboard, commands, display, progress, formatter
│   ├── llm/                     # LM Studio client, AirLLM bridge, factory, prompts, parser
│   ├── scraper/                 # Puppeteer browser, navigator, extractor, stealth
│   ├── tools/                   # Registry + search, scrape, recon, code, file, process tools
│   ├── project/                 # Scaffolder, builder, deployer, dev-server, packager
│   ├── coding/                  # Generator, analyzer, indexer, parser, templates, test-gen
│   ├── filesystem/              # Multi-file ops, tracker, watcher, operations
│   ├── errors/                  # Handler, retry, circuit-breaker
│   ├── utils/                   # Logger, config, cache, cleaner, links, validators
│   └── types/                   # TypeScript types and error types
├── tests/
│   ├── unit/                    # 22 test suites (980 tests)
│   └── integration/             # Workflow integration tests
├── airllm_server.py             # AirLLM Python sidecar
├── Dockerfile                   # Multi-stage Docker build
├── docker-compose.yml           # Compose with volumes & networking
├── DOCUMENTATION.md             # Full API reference (1,305 lines)
├── CONTRIBUTING.md              # Contribution guidelines (544 lines)
├── SECURITY.md                  # Security policy (288 lines)
└── LICENSE.md                   # TJCL v1.0 license

🧪 Test Coverage

Test Suite Tests File
Agent Executor 120+ tests/unit/agents/executor.test.ts
Agent Memory 80+ tests/unit/agents/memory.test.ts
LLM Parser 80+ tests/unit/llm/parser.test.ts
AirLLM Bridge 15 tests/unit/llm/airllm-bridge.test.ts
Code Analyzer 100+ tests/unit/coding/analyzer.test.ts
Code Generator 40+ tests/unit/coding/generator.test.ts
Code Indexer 60+ tests/unit/coding/indexer.test.ts
Code Parser 80+ tests/unit/coding/parser.test.ts
Templates 60+ tests/unit/coding/templates.test.ts
Test Generator 100+ tests/unit/coding/test-generator.test.ts
Circuit Breaker 70+ tests/unit/errors/circuit-breaker.test.ts
Error Handling 60+ tests/unit/errors/errors.test.ts
Retry Logic 60+ tests/unit/errors/retry.test.ts
Multi-File Ops 60+ tests/unit/filesystem/multi-file.test.ts
File Tracker 100+ tests/unit/filesystem/tracker.test.ts
File Watcher 50+ tests/unit/filesystem/watcher.test.ts
Project Builder 80+ tests/unit/project/builder.test.ts
Deployer 70+ tests/unit/project/deployer.test.ts
Packager 80+ tests/unit/project/packager.test.ts
Scaffolder 80+ tests/unit/project/scaffolder.test.ts
Cache Utils 60+ tests/unit/utils/cache.test.ts
Cleaner Utils 50+ tests/unit/utils/cleaner.test.ts
Total 980 22 suites, 80%+ coverage

📝 Documentation Added

Document Lines Description
README.md 764 Full project overview with architecture, usage, Docker, AirLLM, and API docs
DOCUMENTATION.md 1,305 Complete API reference, all 29 tools, configuration, and examples
CONTRIBUTING.md 544 Contribution guidelines, coding standards, and PR process
SECURITY.md 288 Security policy and vulnerability reporting
LICENSE.md 128 The Joker Contribution License (TJCL) v1.0

⚙️ Configuration

.env.example

LM_STUDIO_BASE_URL=http://localhost:1234
LM_STUDIO_MODEL=qwen2.5-coder-14b-instruct-uncensored
LM_STUDIO_API_KEY=not-needed
AGENT_MAX_ITERATIONS=10
AGENT_TIMEOUT_MS=60000
AGENT_VERBOSE=true
SCRAPER_HEADLESS=true
SCRAPER_TIMEOUT_MS=30000
LOG_LEVEL=info
AIRLLM_MODEL=garage-bAInd/Platypus2-70B-instruct
AIRLLM_PORT=8899

🔗 Dependencies Added

Package Purpose
blessed / blessed-contrib TUI Dashboard framework
dns2 DNS lookups for Recon mode
ssl-checker SSL/TLS certificate analysis
whois-json WHOIS lookups
detect-port Port availability for dev servers
tree-kill Process tree cleanup
chokidar File system watching
inquirer Interactive prompts (backend selection)
open Browser launch for vibe coding
ora Terminal spinners
uuid Unique identifiers

🚀 How to Run

# Install
npm install

# Configure
cp .env.example .env
# Edit .env with your LM Studio endpoint

# Build & Run
npm run build
npm start

# Or with Docker
docker build -t thejoker .
docker run -it --rm --env-file .env thejoker

Author: Ratna Kirti
Branch: RK-Dev-Beta
Version: 1.1.1

- Added all 29 tools registration in executor (File, Code, Process tools)
- Refactored prompts into centralized prompts.ts module
- Enhanced code generation with markdown result formatting
- Fixed coding module type conflicts by selective exports
- Improved agent synthesis to properly display generated code
- Added comprehensive IMPLEMENTATION_COMPLETE.md documentation
- Created sample my-app project demonstrating project scaffolding
- Updated LM Studio configuration (reverted to localhost for flexibility)

Key improvements:
* File Tools (9): read, write, append, delete, list, copy, move, exists, create_dir
* Code Tools (4): generate, modify, scaffold, analyze
* Process Tools (5): transform, clean, extract_patterns, convert, summarize
* Enhanced display with markdown code block support
* Better project creation with ProjectScaffolder integration

This completes the full agentic capabilities for The Joker terminal.
- New ReconPipeline with DNS, WHOIS, HTTP headers, SSL/TLS analysis
- Tech stack detection (25+ signatures: React, Next.js, Vue, WordPress, etc.)
- Email extraction, social link discovery, and screenshot capture
- Security score calculator (0-100) based on headers, SSL, DNS records
- Markdown report generator saved to ./reports/
- CLI command: recon <domain> (aliases: scan, osint, investigate)
- New dependencies: dns2, whois-json, ssl-checker
- New JokerDashboard class with 4-region layout (header, thought pane, tool pane, stats)
- Real-time agent state visualization with color-coded states and icons
- All 7 agent events wired: state:change, thought, plan:created, step:complete, correction, goal:achieved, goal:failed
- Stats bar with live uptime, message count, step progress, model info
- Keyboard shortcuts: Tab (cycle panes), q (quit), c (clear), i/Enter (input)
- CLI command: tui (aliases: dashboard, ui) toggles dashboard mode
- New dependencies: blessed, blessed-contrib, @types/blessed
- New VibeCodingPipeline orchestrator (src/agents/vibe-coder.ts)
  Prompt analysis  scaffold  code gen  install deps  dev server  browser
- New DevServerManager (src/project/dev-server.ts)
  Port detection (detect-port), process spawn, readiness polling, browser open (open), tree-kill cleanup
- New SYSTEM_PROMPT_VIBE_CODING + createVibeCodingPrompt() in src/llm/prompts.ts
- CLI commands: vibe (aliases: build, create-app), vibe-stop
- Iterative refinement: live session allows follow-up vibe prompts for HMR updates
- New dependencies: open, tree-kill, detect-port, @types/detect-port
…atures

- Vibe Coding Mode: natural language to running app pipeline (vibe command)
- Hack Mode: automated domain reconnaissance & OSINT (recon command)
- TUI Dashboard: real-time split-pane terminal UI (tui command)
- Updated help menu with all new commands and examples
- Updated README with What's New section, architecture, and directory structure
- Added PR description markdown
- Add AirLLM integration: Python sidecar server (airllm_server.py) wrapping
  70B models via OpenAI-compatible API, TypeScript bridge (airllm-bridge.ts),
  LLM client factory for backend switching
- Add backend selection prompt at startup (LM Studio vs AirLLM)
- Fix command dispatch: REPL now routes through CommandRegistry for all
  registered commands (airllm, vibe, recon, tui, etc.)
- Make banner dynamic: displays actual version, model name, and backend
- Make help dynamic: pulls all commands from CommandRegistry by category
- Add Docker support: multi-stage Dockerfile, docker-compose.yml, .dockerignore
- Version bump to v1.1.1
- Update README with Docker section, v1.1.1 release notes, AirLLM citation
- Add 15 unit tests for AirLLMBridge (980 total tests passing)

AirLLM citation: Li, G. (2023). AirLLM: scaling large language models
on low-end commodity computers. https://github.com/lyogavin/airllm/
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Pull request overview

This PR introduces significant new capabilities to The Joker terminal, transforming it from a basic agentic terminal into a full-featured development assistant with OSINT capabilities, project scaffolding, and support for 70B-parameter models on constrained hardware.

Changes:

  • AirLLM Integration: Python sidecar server enabling 70B models on 4GB RAM via layer-wise inference
  • Vibe Coding Pipeline: Natural language to running application (scaffold → generate → install → serve)
  • Recon Tool: Automated OSINT reconnaissance (DNS, WHOIS, SSL, tech stack detection, security scoring)
  • TUI Dashboard: Real-time split-pane visualization of agent thinking and tool execution using blessed
  • Docker Support: Production-ready containerization with multi-stage builds
  • Enhanced CLI: Dynamic backend selection, improved command dispatch, and 29 registered tools

Reviewed changes

Copilot reviewed 31 out of 31 changed files in this pull request and generated 9 comments.

Show a summary per file
File Description
airllm_server.py Python FastAPI server wrapping AirLLM for OpenAI-compatible inference
src/llm/airllm-bridge.ts TypeScript bridge managing Python sidecar lifecycle
src/llm/factory.ts LLM client factory for backend switching
src/agents/vibe-coder.ts End-to-end pipeline: prompt → running app with dev server
src/tools/recon.ts Domain reconnaissance with DNS, WHOIS, SSL, tech stack detection
src/project/dev-server.ts Dev server manager with port detection and process orchestration
src/cli/dashboard.ts Blessed-based TUI with split-pane layout and real-time updates
src/index.ts Command registration for vibe, recon, tui, airllm commands
src/utils/config.ts Added AirLLM configuration with default changed to localhost
package.json Added blessed, dns2, ssl-checker, tree-kill, detect-port, open dependencies
Dockerfile Multi-stage build with Chromium and Python support
docker-compose.yml Compose configuration with volume mounts and networking
requirements-airllm.txt Python dependencies for AirLLM sidecar

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model: str = ""
messages: List[ChatMessage]
temperature: float = 0.7
max_tokens: int = 256
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The max_tokens parameter is user-controllable and could lead to resource exhaustion. The ChatCompletionRequest model allows arbitrary max_tokens values without validation. Consider adding a maximum limit (e.g., max_tokens: int = Field(default=256, le=2048)) to prevent users from requesting excessively large token counts that could consume all available resources.

Suggested change
max_tokens: int = 256
max_tokens: int = Field(default=256, le=2048)

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// Spawn the Python process
this.sidecar = spawn(this.config.pythonPath, args, {
stdio: ['ignore', 'pipe', 'pipe'],
env: { ...process.env },
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The process spawning does not set a shell=False, which could be a security risk if user input ever reaches the args. While args are currently hardcoded from config, consider explicitly setting shell=False for defense in depth, or validate that args only contains expected values.

Suggested change
env: { ...process.env },
env: { ...process.env },
shell: false,

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Comment on lines +133 to +136
private async waitForHealth(
maxAttempts: number = 120,
intervalMs: number = 5000
): Promise<void> {
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The health check polling uses a very long timeout (120 attempts × 5000ms = 10 minutes) with no user feedback. This could lead to a confusing UX where the application appears frozen. Consider reducing the timeout or adding progress indicators via events that the caller can display.

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Comment on lines +88 to +94
const child = spawn(command, args, {
cwd: projectPath,
env,
stdio: ['pipe', 'pipe', 'pipe'],
shell: true,
detached: false,
});
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The spawn call uses shell=true which is a security risk. The command and args are controlled by options but could potentially be influenced by user input through the DevServerOptions. Use shell=false and pass command and args separately to prevent command injection attacks.

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Comment on lines +227 to +231
async recon(domain: string): Promise<ReconResult> {
const startTime = Date.now();
const cleanDomain = this.cleanDomain(domain);
log.info(`[Recon] Starting reconnaissance on: ${cleanDomain}`);

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The recon tool performs network requests and DNS lookups on user-supplied domains without validation. A malicious user could provide internal IP addresses (e.g., 127.0.0.1, 192.168.x.x, 10.x.x.x) to perform SSRF attacks against internal services. Add validation to reject private IP addresses and localhost before performing reconnaissance.

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category: 'general',
execute: async () => {
console.log(theme.muted('\nGoodbye! 🃏\n'));
process.exit(0);
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The process.exit(0) call will terminate the entire Node.js process immediately, which may not allow proper cleanup of resources (e.g., stopping the AirLLM sidecar, closing database connections, etc.). The cleanup method is called on line 781 but may not complete before exit. Consider returning an exit code instead and letting the caller handle the actual exit, or ensure cleanup completes before calling process.exit.

Suggested change
process.exit(0);

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Comment on lines +344 to +347
return new Promise<void>((resolve, reject) => {
const child = spawn('npm', ['install'], {
cwd: projectPath,
shell: true,
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The npm install spawns with shell=true which could be a command injection risk if projectPath contains malicious input. While projectPath is typically controlled by the application, consider using shell=false and ensuring the cwd path is validated or sanitized to prevent potential security issues.

Suggested change
return new Promise<void>((resolve, reject) => {
const child = spawn('npm', ['install'], {
cwd: projectPath,
shell: true,
const resolvedProjectPath = path.resolve(projectPath);
return new Promise<void>((resolve, reject) => {
const child = spawn('npm', ['install'], {
cwd: resolvedProjectPath,
shell: false,

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*/
export const llmConfig: LLMConfig = {
baseUrl: getEnv('LM_STUDIO_BASE_URL', 'http://192.168.56.1:1234'),
baseUrl: getEnv('LM_STUDIO_BASE_URL', 'http://localhost:1234'),
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The default URL for LM Studio has been changed from localhost (127.0.0.1) to a specific local network address (192.168.56.1). This change may break the application for users who haven't configured this specific network setup. This appears to be a development-specific configuration that should not be in the default. Revert to 'http://localhost:1234' as the default.

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"type": "commonjs",
"dependencies": {
"axios": "^1.13.2",
"blessed": "^0.1.81",
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The blessed types package (@types/blessed) may have compatibility issues with the blessed package version 0.1.81 being used. The blessed package hasn't been updated since 2015 and the types package is community-maintained. Consider using neo-blessed (a maintained fork) instead, or verify that the types are compatible with the ancient blessed version.

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