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Achievement: Starstruckx2Achievement: Pull Sharkx3Achievement: Pair Extraordinairex4Achievement: Quickdraw

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qrak/README.md

qrak

I build small, verifiable systems — mostly Python, mostly around LLMs.

Semantic Signal — an LLM trading agent that shows its work

On every closed candle it renders the price action into a 1920×1080 chart, sends the image with 79 Numba-compiled indicators, the news context and its own closed-trade memory to a multimodal model, then passes the answer through deterministic risk gates before booking a paper trade. The prompt, the retrieved memory, the verdict and the losses are public.

Code · Live dashboard · Ledger · How one cycle works

Around it

  • ti_numba — 79 technical indicators in Numba JIT, the ones the bot calls every cycle.
  • candledownloader — OHLCV downloader with gap detection across exchanges.
  • telegram-commandcode — MCP server that lets a coding agent send Telegram messages and files.

Paper trading only. No fund management, no signal selling, and no performance claim that the public ledger cannot reproduce.

Pinned Loading

  1. LLM_trader LLM_trader Public

    An LLM trading agent that shows its work: the chart, the prompt, the memory it retrieved, and every loss. Paper trading, public ledger.

    Python 141 48

  2. DiscordCryptoAnalyzer DiscordCryptoAnalyzer Public

    DiscordCryptoAnalyzer

    Python 8 1

  3. ti_numba ti_numba Public

    High-performance technical indicators using Numba JIT compilation.

    Python 5 3

  4. candledownloader candledownloader Public

    Python application for downloading and validating OHLCV cryptocurrency data from multiple exchanges with smart filtering and gap detection capabilities

    Python 8

  5. ai-research-articles ai-research-articles Public

    A collection of AI research articles

    HTML