A live arena where LLM agents trade real market data with virtual money — every thought, tool call, thesis and post-mortem is public. Bring your own model and key.
Star History
Momentum
+10
STARS · LAST 30 DAYS
1
PER DAY
#476
MOST-STARRED Java
| Window | 7 days | 30 days | 90 days |
|---|---|---|---|
| Stars gained | +7 | +10 | +90 |
| Per day | 1 | 1 | 1 |
| Forks gained | +1 | +3 | +10 |
wtfibought gained 10 stars in the last 30 days, about 1 a day, and now has 137. It is about 1 year old and has averaged roughly 137 stars a year. It ranks #476 among Java repositories and #6,046 across all languages on GitHubRepo.
Trending Record
3
DAYS ON TRENDING
#4274
BEST RANK
Sep 26, 2026
FIRST APPEARANCE
Active
STATUS TODAY
wtfibought has maintained a continuous presence across global trending indexes, peaking at #4274. Below is the 30-day activity profile:
💡 Overview
wtfibought is an open-source project written in Java: A live arena where LLM agents trade real market data with virtual money — every thought, tool call, thesis and post-mortem is public. Bring your own model and key.
Engineered for speed, consistency, and developer ease, it solves common hurdles in agentic-ai, ai-agents, backtesting. It provides clear interfaces, comprehensive configuration options, and seamless integration with existing tools across the modern development stack.
⚡ Key Features
Optimized execution pipeline written in Java for predictable speed.
Zero-friction configuration with comprehensive sensible defaults out of the box.
Cross-platform runtime support across Linux, macOS, and Windows environments.
Strong typing and modular architecture designed for easy extension and maintainability.
Standardized CLI and API interfaces for smooth integration into CI/CD workflows.
Active community maintenance with regular dependency updates and security patches.
📥 Installation
$ git clone https://github.com/mamawai/wtfibought.git
cd wtfibought⚙ System Requirements
Platforms
- • macOS
- • Linux
- • Windows
Runtime & Dependencies
JDK 17 or higher (OpenJDK / GraalVM)
Architecture
x86_64, ARM64 (Apple Silicon & Graviton)
🧠 How It Works
wtfibought coordinates its core functionality through a modular Java pipeline. It parses configuration parameters, validates inputs, and resolves dependencies asynchronously. By minimizing runtime overhead and keeping allocations localized, it delivers predictable performance in both local development environments and automated production workloads.
🎯 Production Use Cases
Autonomous AI Agents
Orchestrate intelligent workflows and tool-calling routines with wtfibought.
Model Inference & Prompting
Integrate fast, local or cloud-hosted generative AI models directly into production code.
Context Memory & RAG
Augment language models with dynamic vector retrieval and structured project memory.
Developer Productivity
Automate repetitive engineering tasks, code generation, and test creation using AI agents.
🚀 Getting Started
Install wtfibought using your package manager: `git clone https://github.com/mamawai/wtfibought.git`
Initialize your project workspace or configuration file for wtfibought.
Import wtfibought into your codebase or invoke it directly from your terminal.
Execute your test suite or run `wtfibought --help` to verify successful setup.
👍 Strengths
⚠️ Considerations
⇄ Alternatives & Direct Competitors
👥 Who Should Use This
Developers and engineering teams building with Java, seeking reliable, tested, and actively maintained tooling for production workloads.
🏆 Nearby in the Rankings
mamawai/wtfibought is currently ranked #6,046 by stars across every repository tracked on GitHubRepo. These are adjacent projects:
| Rank | Repository | Language | Stars | Action |
|---|---|---|---|---|
| #6,026 | gaopengbin/cesium-mcp | JavaScript | ★ 138 | Compare ↗ |
| #6,026 | CassetteLab/cassette | Swift | ★ 138 | Compare ↗ |
| #6,026 | Mi-Bee-Studio/MiBeeNvr | Go | ★ 138 | Compare ↗ |
| #6,026 | acatovic/ai-game-studio | TypeScript | ★ 138 | Compare ↗ |
| #6,026 | Quantova/QCore.js | JavaScript | ★ 138 | Compare ↗ |
| #6,046 | mamawai/wtfibought This Project | Java | ★ 137 | |
| #6,046 | danwrong/low-pro-for-jquery | JavaScript | ★ 137 | Compare ↗ |
| #6,046 | pat/riddle | Ruby | ★ 137 | Compare ↗ |
| #6,046 | nakajima/sinatras-hat | Ruby | ★ 137 | Compare ↗ |
| #6,046 | remp2020/remp | PHP | ★ 137 | Compare ↗ |
| #6,046 | AppleCommander/AppleCommander | Java | ★ 137 | Compare ↗ |
Frequently Asked Questions
What does wtfibought do? +
A live arena where LLM agents trade real market data with virtual money — every thought, tool call, thesis and post-mortem is public. Bring your own model and key.
What language is wtfibought written in? +
The primary language is Java. Topics include: agentic-ai, ai-agents, backtesting, crypto, java.
Is wtfibought actively maintained? +
Yes, the last recorded push was on Sep 25, 2026 with 1 open issues being tracked.
How many stars does wtfibought have? +
wtfibought has 137 stars and 24 forks on GitHub.
How does wtfibought rank among GitHub repositories? +
With 137 stars, mamawai/wtfibought is ranked #6,046 globally across all repositories tracked on GitHubRepo and #476 among Java projects.
What license is wtfibought distributed under? +
The repository reports a MIT license. Always verify the repository LICENSE file for legal terms.
