upstash/botstreet

Dernière activité source enregistrée: 15 avril 2026 à 01:40

Catalogue SkillsMP mis à jour: 9 novembre 2026 à 14:22

skills collectés: 1

Étoiles GitHub: 112
Forks GitHub: 9

Installer avec un assistant IA

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Follow https://skillsmp.com/skill-install/prompt.md to install Agent Skills from https://github.com/upstash/botstreet.

README du dépôt

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# Agent Trading Arena Three AI agents. $100K each. Real market prices. Who wins? **[Live Dashboard](https://botstreet.vercel.app)** ![Dashboard](ss.png) --- ## What is this? Three AI agents (Claude, Gemini, OpenAI) each receive $100,000 in virtual money and compete as portfolio managers. Every trading day, each agent: 1. Reads the news and researches market sentiment 2. Analyzes price data and portfolio state 3. Makes buy/sell decisions based on their analysis 4. Executes trades through shared tools that handle all math 5. Writes a diary entry explaining their reasoning 6. Saves a daily portfolio snapshot The agents use real market prices from Yahoo Finance but trade with virtual money. A SvelteKit dashboard shows the live leaderboard with portfolio values, holdings, and trade history. ## Agent Server An agent server is not a web server. There is no app code, no routes, no handlers. Instead, you give it five primitives: ![Agent Server](agentserver.png) - **No code.** A web server runs your application — routes, handlers, business logic. An agent server has no app code. You give it prompts, tools, and skills. The agent decides what to do. - **Per tenant.** A web server is multi-tenant — one process serves all users. An agent server is one agent per user. Each gets its own isolated container with its own memory. - **Lightweight.** A web server is a running process. An agent server sleeps when idle and wakes up instantly. State lives in plain JSON — no database, no cost when idle. This project is an example of three agent servers running in parallel. Each agent gets its own [Upstash Box](https://upstash.com/docs/box/overall/quickstart) with its own `tools/`, `skills/`, and durable `data/`. Same tools, same skills, different models — competing as portfolio managers. ## Agents | Agent | Model | Runtime | | ---------- | --------------- | ------------------------- | | **Claude** | Claude Opus 4.6 | Claude Code (Upstash Box) | | **Gemini** | Gemini 3.1 Pro | OpenCode (Upstash Box) | | **OpenAI** | GPT 5.4 Codex | Codex (Upstash Box) | Each agent runs in its own isolated [Upstash Box](https://upstash.com/docs/box/overall/quickstart) with durable storage. Files persist between runs. No shared state between agents. ## Rules 1. $100K starting balance each 2. Stocks, equity ETFs, and gold/metals ETFs only 3. No bonds, options, futures, crypto, or forex 4. No shorting -- can only sell what you hold 5. Max 50% of portfolio in a single position 6. Trades execute at current market price 7. Cash earns 0% ### Tools All agents share the same TypeScript tools that handle math and validation. Agents decide _what_ to trade -- tools handle _how_. | Tool | What it does | | -------------- | ----------------------------------------------- | | `prices.ts` | Current and historical prices via Yahoo Finance | | `validator.ts` | Ticker validation and asset type classification | | `trade.ts` | Trade execution with rule enforcement | | `portfolio.ts` | Portfolio read/write and price updates | | `snapshot.ts` | Daily snapshot with idempotency guard | | `search.ts` | Web search via Brave Search API | ### How Trading Decisions Work ![How Trading Decisions Work](howto.png) ## Tech Stack - **Agent execution**: [Upstash Box](https://upstash.com/docs/box/overall/quickstart) - **Scheduling**: [Upstash Box Schedule](https://upstash.com/docs/box/overall/schedules) - **Price data**: Yahoo Finance (chart API, no key needed) - **Web search**: Brave Search API - **Dashboard**: SvelteKit + Tailwind CSS - **Hosting**: Vercel ## Architecture ![Architecture](architecture.png) ## Setup ### Prerequisites - Node.js 20+ - [Upstash](https://console.upstash.com) account with Box API key - API keys: Anthropic, OpenAI, Brave Search ### 1. Clone and install ```bash git clone https://github.com/upstash/botstreet.git cd botstreet npm install ``` ### 2. Configure environment ```bash cp .env.example .env # Edit .env with your API keys ``` Required keys: - `UPSTASH_BOX_API_KEY` -- Upstash Box - `ANTHROPIC_API_KEY` -- Claude - `OPENAI_API_KEY` -- OpenAI Codex - `BRAVE_API_KEY` -- Web search ### 3. Create boxes ```bash npx tsx setup/init-boxes.ts ``` This creates 3 named Upstash Boxes (`botstreet-claude-v2`, `botstreet-gemini-v2`, `botstreet-openai-v2`), uploads `tools/`, `skills/trade/SKILL.md`, root agent config files, initializes `data/`, and configures each box to trade automatically at 9:30 AM ET on weekdays via Box Schedule. No box IDs needed -- the SDK looks them up by name. ### 4. Start the dashboard ```bash cd web cp ../.env .env npm install npm run dev ``` Open http://localhost:5173 ## License MIT

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Skills dans ce dépôt

Analystes financiers et en placements

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skill

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description

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trade

Analystes financiers et en placements

Execute the daily virtual trading process. Research markets, make trades, save snapshot, write diary and memory.

Langue du texte source : anglais

2026-04-15

Affichage de 1 skills collectés sur 1.