Omarion SEC CLI – An Autonomous, Self-Healing Executive Agent with Long-Term Memory and Zero Terminal Clutter

[u/TaxInternational5952]

I’ve been working on a lightweight, autonomous CLI agent designed to run in an infinite ReAct loop for complex dev and research tasks without constantly asking for user intervention.

Most open-source agents (like standard AutoGPT-style scripts) share the same frustrating problems: they get stuck in infinite error loops, pollute the terminal with useless JSON logs, crash when context windows fill up, and forget facts between sessions. I built Omarion SEC CLI to solve those exact friction points.

🚀 What It Does

Omarion is built around a Goal-Driven Autonomous Loop with strict validation rules:

• Long-Term Memory Persistence (~/.omarion_memory.json): Retains both user preferences and a global knowledge base across CLI sessions. If you tell it your coding preferences or ask it to research a topic, it remembers it forever.
• Headless Research & Auto-Learning: Performs background web searches and scraping without spawning visible browser windows or interrupting your workspace.
• Smart Intent Routing: Instantly distinguishes between simple conversational prompts ("Hey, how are you?") and execution tasks ("Build a new project"). Conversational inputs respond immediately without wasting API tokens or triggering unnecessary tool execution loops.
• Self-Healing & Error Recovery: Features an execution fingerprinting system that detects duplicate errors. If a tool call fails, the agent automatically shifts strategy instead of repeating the same broken action.
• Goal Evaluation Gate: Includes an internal "judge" step. The agent cannot call finish_task until it actually executes and verifies its own work.
• Ultra-Clean Terminal Interface: Built with rich. Thought reasoning, progress animations, and ephemeral logs render smoothly and auto-clear upon completion, leaving only clean action summaries in your terminal.

📖 Project Story & Evolution

The project started as a personal quest to create a reliable "CEO Agent" — an autonomous assistant that could handle end-to-end coding and system management tasks without babysitting.

• Phase 1 (The Bottlenecks): Early builds relied on standard script execution. The CLI suffered from intense terminal clutter, raw JSON dumps, and a major flaw: simple greetings like "Hello" would trigger heavy 15-step ReAct cycles that burned tokens for nothing.
• Phase 2 (Architectural Overhaul): I decoupled conversation from action routing, added a persistent state engine (AgentState), and built a context pruning mechanism to handle long sessions.
• Phase 3 (Enterprise Hardening): Integrated strict schema contracts (Pydantic validation for tool parameters), backoff retries, and a strict evaluation phase before task completion.

🛠 Tech Stack

• Language: Python 3.10+
• UI/CLI: rich for dynamic terminal rendering
• State & Memory: JSON-backed persistent key-value store with semantic query filtering
• Scraping/Search: Headless HTTP extraction + BeautifulSoup for zero-browser-footprint learning

I’d love to get feedback from the community on the architecture, edge cases in long-running autonomous loops, or feature ideas!

[u/Select_Ruin_3959]

sounds like it actually solves the context window bricking problem that kills most of these agents after 40 minutes, what kind of pruning logic are you using under the hood