Picoclaw Ai Assistant
Deploy and configure PicoClaw, a sub‑10MB Go AI assistant on cheap ARM/RISC‑V hardware with your LLM keys and tools.
Overview
PicoClaw AI Assistant is an agent skill for the Build phase that guides ultra-lightweight Go-based personal AI deployment on low-cost ARM and RISC-V hardware.
Install
npx skills add https://github.com/aradotso/trending-skills --skill picoclaw-ai-assistantWhat is this skill?
- Single-binary deployment on x86_64, ARM64, MIPS, and RISC-V with under 10MB RAM targets
- OpenAI-compatible, Anthropic, and Volcengine provider wiring plus optional web search tools
- Precompiled release install and Makefile-based source builds with Docker option
- Onboarding flow (`picoclaw onboard`) for API keys, memory, and workspace configuration
- Designed for Raspberry Pi-class $10 boards with sub‑1s boot
- Sub-1 second boot
- Supports x86_64, ARM64, MIPS, and RISC-V
Adoption & trust: 1.3k installs on skills.sh; 31 GitHub stars; 2/3 security scanners passed (skills.sh audits).
What problem does it solve?
You want a personal LLM assistant on cheap edge hardware but do not have a repeatable install, provider, and tooling setup for a sub‑10MB binary.
Who is it for?
Indie builders shipping a local or edge-hosted assistant on Raspberry Pi–class boards with OpenAI-compatible or Anthropic APIs.
Skip if: Teams needing managed cloud agent platforms, heavy multi-tenant backends, or Windows/macOS desktop-only assistants without Linux targets.
When should I use this skill?
User asks to set up, configure, deploy, build from source, dockerize PicoClaw, or wire LLM providers and web search on device.
What do I get? / Deliverables
You get a configured PicoClaw binary with chosen providers, optional search tools, and memory/workspace settings ready to run on your device.
- Running PicoClaw binary
- Configured provider and tool settings
- Optional Docker deployment
Recommended Skills
Journey fit
Canonical shelf is Build because the skill centers on assembling, configuring, and shipping a runnable personal agent binary—not ongoing production ops. Agent-tooling fits setup of lightweight assistant runtimes, providers, tools, and workspace memory on edge devices.
How it compares
Use for bare-metal edge agent packaging instead of ad-hoc curl scripts against chat APIs.
Common Questions / FAQ
Who is picoclaw-ai-assistant for?
Solo and indie builders using Claude Code, Cursor, or similar agents to stand up PicoClaw on Linux ARM/x86 edge devices with minimal RAM.
When should I use picoclaw-ai-assistant?
During Build when you need to set up PicoClaw on a device, configure API keys, add providers, enable web search, or containerize with Docker on Pi-class hardware.
Is picoclaw-ai-assistant safe to install?
Review the Security Audits panel on this Prism page and treat API keys and network-enabled tools as sensitive; verify release binaries and repo sources before deploying.
SKILL.md
READMESKILL.md - Picoclaw Ai Assistant
# PicoClaw AI Assistant > Skill by [ara.so](https://ara.so) — Daily 2026 Skills collection. PicoClaw is an ultra-lightweight personal AI assistant written in Go. It runs on $10 hardware with under 10MB RAM and boots in under 1 second. It supports multiple LLM providers (OpenAI-compatible, Anthropic, Volcengine), optional web search tools, and deploys as a single self-contained binary on x86_64, ARM64, MIPS, and RISC-V Linux devices. --- ## Installation ### Precompiled Binary Download from the [releases page](https://github.com/sipeed/picoclaw/releases): ```bash # Linux ARM64 (Raspberry Pi, LicheeRV-Nano, etc.) wget https://github.com/sipeed/picoclaw/releases/download/v0.1.1/picoclaw-linux-arm64 chmod +x picoclaw-linux-arm64 ./picoclaw-linux-arm64 onboard ``` ### Build from Source ```bash git clone https://github.com/sipeed/picoclaw.git cd picoclaw # Install dependencies make deps # Build for current platform make build # Build for all platforms make build-all # Raspberry Pi Zero 2 W — 32-bit make build-linux-arm # → build/picoclaw-linux-arm # Raspberry Pi Zero 2 W — 64-bit make build-linux-arm64 # → build/picoclaw-linux-arm64 # Build both Pi Zero variants make build-pi-zero # Build and install to system PATH make install ``` ### Docker Compose ```bash git clone https://github.com/sipeed/picoclaw.git cd picoclaw # First run — generates docker/data/config.json then exits docker compose -f docker/docker-compose.yml --profile gateway up # Edit config vim docker/data/config.json # Start in background docker compose -f docker/docker-compose.yml --profile gateway up -d # View logs docker compose -f docker/docker-compose.yml logs -f picoclaw-gateway # Stop docker compose -f docker/docker-compose.yml --profile gateway down ``` #### Docker: Web Console (Launcher Mode) ```bash docker compose -f docker/docker-compose.yml --profile launcher up -d # Open http://localhost:18800 ``` #### Docker: One-shot Agent Mode ```bash # Single question docker compose -f docker/docker-compose.yml run --rm picoclaw-agent -m "What is 2+2?" # Interactive session docker compose -f docker/docker-compose.yml run --rm picoclaw-agent ``` #### Docker: Expose Gateway to Host If the gateway needs to be reachable from the host, set: ```bash PICOCLAW_GATEWAY_HOST=0.0.0.0 docker compose -f docker/docker-compose.yml --profile gateway up -d ``` Or set `PICOCLAW_GATEWAY_HOST=0.0.0.0` in `docker/data/config.json`. ### Termux (Android) ```bash pkg install wget proot wget https://github.com/sipeed/picoclaw/releases/download/v0.1.1/picoclaw-linux-arm64 chmod +x picoclaw-linux-arm64 termux-chroot ./picoclaw-linux-arm64 onboard ``` --- ## Quick Start ### 1. Initialize ```bash picoclaw onboard ``` This creates `~/.picoclaw/config.json` with a starter configuration. ### 2. Configure `~/.picoclaw/config.json` ```json { "agents": { "defaults": { "workspace": "~/.picoclaw/workspace", "model_name": "gpt-4o", "max_tokens": 8192, "temperature": 0.7, "max_tool_iterations": 20 } }, "model_list": [ { "model_name": "gpt-4o", "model": "openai/gpt-4o", "api_key": "$OPENAI_API_KEY", "request_timeout": 300 }, { "model_name": "claude-sonnet", "model": "anthropic/claude-sonnet-4-5", "api_key": "$ANTHROPIC_API_KEY" }, { "model_name": "ark-code", "model": "volcengine/ark-code-latest", "api