sam-4screen-desktop 2026-5-21:9:0:39
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"title": "LLM - models to consider"
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"title": "Automated Agentic Tools"
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"300 areas/350 AI/Pi Agent Extensions & Skills.md",
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"300 areas/310 Home Assistant/Home Assistant.md~",
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"300 areas/310 Home Assistant/Dog Feeder.md",
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"100 inbox/1779253896-DPHX.md~",
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"300 areas/360 Dev-Ops Network Computers/Pi Neovim Coding Harness.md",
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300 areas/350 AI/Automated Agentic Tools.md
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---
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created: 2026-05-21 08:48
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modified: 2026-05-21 08:48
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type: note
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tags:
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- ai
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- llm
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- tool
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- automation
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- agents
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- ESP32
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aliases: []
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---
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# [[Automated Agentic Tools]]
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# Autonomous AI Agents & Background Companions
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A comprehensive breakdown of persistent, autonomous 24/7 AI agents that can manage local files, research data, automate browsers, and execute background tasks.
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---
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## 🛠️ Local & Open-Source Agents
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These tools focus on running locally or on a private server (VPS), using messaging interfaces like Telegram or Discord for interaction.
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### 🦅 Hermes Agent AI
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Developed by Nous Research, this is a highly modular "Agent Operating System" designed to live persistently on local or server environments.
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* **Core Philosophy:** Minimal noise, high autonomy, and self-improving memory mechanics.
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* **Key Feature:** If it fails a task, it pauses in the background, reflectively debugs its own code, and saves a permanent custom "skill file" to its system directory so it never makes the same mistake twice.
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* **Interfaces:** Terminal CLI, official Desktop GUI app, or fully compatible with **Open WebUI** for a local, private ChatGPT-style interface.
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* **Resources:** [Hermes Agent Documentation](https://nousresearch.com) | [GitHub Repository](https://github.com)
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### 🦞 OpenClaw (Formerly MoltBot)
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The open-source pioneer of the background messaging assistant movement.
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* **Core Philosophy:** A personal gateway connecting highly powerful cloud LLMs directly to your local hardware capabilities.
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* **Key Feature:** Deep integration across 12+ messaging platforms (WhatsApp, Telegram, Signal, iMessage). It handles long, hour-long background tasks (like checking emails or crawling websites) and reports back with results.
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* **Resources:** [OpenClaw GitHub](https://github.com)
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### 🧠 MiniClaw OS
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An optimized extension built directly on top of the OpenClaw architecture.
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* **Core Philosophy:** Streamlining agent memory to prevent cognitive bloating over long conversation logs.
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* **Key Feature:** Implements an autonomous "Kanban brain" that tracks long-term goals and files away structured memories without requiring heavy local Node.js or Linux infrastructure overhead.
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---
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## 🔌 Hardware-Native Edge Agents
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These frameworks shift the agent logic completely away from PCs and servers, putting autonomous AI runtimes directly onto inexpensive microcontrollers.
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### 🦞 ESP-Claw (by Espressif)
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An official edge-AI framework built by the makers of the ESP32 chip family to replace standard embedded programming with natural language "Chat Coding".
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* **Core Philosophy:** Transforming passive IoT hardware (relays, bulbs, sensors) into thinking, event-driven edge agents for under $10.
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* **Key Feature:** Zero IDE required. You flash the runtime once via a Chromium browser web serial connection. Once connected to Wi-Fi and Telegram, you program your physical pins dynamically by texting it (e.g., *"If temperature sensor exceeds 30°C, blink the green LED and message me"*). The device writes and executes its own runtime code on the fly.
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* **Architecture:** Uses an optimized C-based engine supporting the Model Context Protocol (MCP), allowing the microchip to act as both a client or server to other devices.
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* **Resources:** [ESP-Claw Website](https://esp-claw.com/en/) | [GitHub Repository](https://github.com/espressif/esp-claw)
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---
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## ☁️ Cloud & Premium Managed Frameworks
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These platforms are designed to execute sprawling, multi-step research or tasks on isolated cloud environments rather than your personal machine.
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* **Manus:** A powerful cloud-native option that provisions a dedicated virtual machine for the AI agent. This allows it to manipulate files, run web actions, and execute heavy programming scripts completely isolated from your physical computer.
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* **KimiClaw:** Optimized for massive data reading workflows. Features an isolated cloud storage layout designed specifically to ingest, cross-reference, and summarize gigantic libraries of PDFs, docs, and notes.
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* **Perplexity Computer:** A premium, multi-model orchestrator tier. It is designed to run deep, prolonged web research tasks where you give it a broad objective and let it parse the live web for hours before delivering a comprehensive report.
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---
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## 🔐 Crucial Security & Architecture Strategy
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Because these agents leverage heavy shell capabilities (`BashTool`, `WriteTool`), absolute isolation is required to prevent security vulnerabilities or accidental script damage to your primary computer:
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1. **Isolate the Agent:** Do not run these frameworks directly on your primary, everyday laptop or PC.
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2. **Dedicated Environment:** Install them inside an isolated Docker container, a dedicated spare machine (e.g., an old Mac Mini), or an inexpensive Linux Virtual Private Server (VPS).
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3. **Restricted Access:** Map *only* the specific folders the agent needs to see (such as an isolated `/Obsidian-Inbox/` directory) rather than giving it unrestricted access to your entire root drive.
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---
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## 🔗 How to Use This in Obsidian
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To build the **"Research Assistant Workflow"** you described, pair **Hermes Agent** or **OpenClaw** with your vault using this method:
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1. **Set Up a Watch Folder:** Create an incoming folder like `00_Inbox/Film_Research/` inside this vault.
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2. **Grant Agent Access:** Expose *only* that specific folder to your local agent's workspace configuration.
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3. **Command via Message:** Text your agent via Telegram:
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> *"Research top 5 drama films from 2025 that don't contain excessive violence. Format the response cleanly into a markdown note with frontmatter tags and save it directly to my film folder."*
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---
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## 🔗 Visual & Pipeline-Driven Agent Platforms
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These tools bridge the gap between deterministic automation platforms (like N8N) and autonomous background agents, focusing heavily on structured data pipelines and external integrations.
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### ➰ Gumloop
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A visual, node-based data piping architecture that operates exactly like a heavily upgraded, AI-first alternative to N8N.
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* **Core Philosophy:** Combining the deterministic reliability of programmatic web requests with the reasoning flexibility of LLMs.
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* **Key Feature:** You construct workflows using connected nodes to scrape modern, complex websites, pass the raw text to an LLM block for filtering/structuring, and format the output. It is highly optimized for scheduling complex background research loops.
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* **Obsidian Pipeline:** You can build a loop that scrapes film data, strips it of unwanted genres, converts the data to Markdown, and automatically pushes the `.md` file to a private GitHub repository synced directly with your local Obsidian vault.
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* **Resources:** [Gumloop Website](https://gumloop.com)
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### 🪵 Relevance AI
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An advanced environment designed to build cohesive, cooperative multi-agent teams using visual mapping.
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* **Core Philosophy:** Breaking complex goals down into distinct "jobs" managed by specialized sub-agents.
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* **Key Feature:** Rather than relying on a single conversational bot to handle everything, you build individual task units (e.g., an "Email Triager", a "Calendar Coordinator", and a "Web Scraper"). They hand files and structured inputs off to one another automatically, complete with deep trace logs for debugging failure points.
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* **Resources:** [Relevance AI Website](https://relevanceai.com)
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### 🕊️ Lindy AI
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A no-code, managed assistant platform built specifically for high-level personal, calendar, and family administration.
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* **Core Philosophy:** Creating persistent, conversational "digital employees" that integrate with your daily tech stack with zero infrastructure setup.
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* **Key Feature:** It features deep native integrations with core cloud services (Google Workspace, Microsoft 365, Slack) right out of the box, allowing you to quickly spin up reactive automation routines to manage personal scheduling and inbound communications.
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* **Resources:** [Lindy AI Website](https://lindy.ai)
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### owl alpha
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This is a multi-layer tool that as split into planner, coordinator and worker agents as its basic architecture and worth exploring.
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### qwen 3.6 plus
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| Model | Primary Agent Advantage | Availability | Best Use Case |
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| ------------------------------------ | ------------------------------------------------------- | -------------------------------------------------------------------- | ------------------------------------------- |
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| **Owl Alpha** | 3-layer native workflow (Planner, Coordinator, Workers) | [OpenRouter](https://openrouter.ai/openrouter/owl-alpha) (Free) | Lengthy context-heavy web tasks & workflows |
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| **Qwen 3.6 Plus** | Exceptionally reliable tool calling and code generation | [OpenRouter](https://openrouter.ai/qwen/qwen3.6-plus) (Free/Preview) | Building free production code agents |
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| **Kimi K2.6** | High tolerance for parallel tasks & long chains | Open-Weight / API | Multi-agent collaboration frameworks |
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| **GLM 4.5 Air** | Toggleable Native "Thinking Mode" for reasoning | OpenRouter (Free) | Hybrid text and complex API automation |
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| **NVIDIA Nemotron 3 Nano (30B A3B)** | Local, secure agents that do not rely on cloud APIs | Open-Weight | Local, secure desktop agent loops |
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