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zclaw - Field Guide

zclaw docs

chapter 0

The 888 KiB Assistant

zclaw is an ESP32-resident AI agent written in C. It runs as a practical assistant over Telegram or host relay, with scheduling, GPIO control, memory, and a tight firmware budget.

Enjoy with zclaw

  • "Remind me in 20 minutes."
  • "Water the plants every day at 8:15."
  • "Set GPIO 5 high."
  • "Remember that my office sensor is on GPIO 4."

You send plain language, zclaw maps to tool calls, firmware executes on silicon.

You: In 20 minutes, check the garage sensor
Agent: Created schedule #7: once in 20 min -> check the garage sensor
Tested targets: ESP32-C3, ESP32-S3, and ESP32-C6. Other ESP32 variants should work fine.

What "888 KiB" Means

The 888 KiB target is an all-in firmware cap, not just zclaw application logic. It includes app code plus ESP-IDF/FreeRTOS runtime, Wi-Fi/networking, TLS/crypto, and cert bundle overhead.

Current default esp32s3 build (grouped loadable image bytes from idf.py -B build size-components; rows sum to total image size):

LayerSizeShare
zclaw app logic (libmain.a)35,742 bytes (~34.9 KiB)~4.1%
Wi-Fi + networking stack397,356 bytes (~388.0 KiB)~45.7%
TLS/crypto stack112,922 bytes (~110.3 KiB)~13.0%
Cert bundle + app metadata99,722 bytes (~97.4 KiB)~11.5%
Other ESP-IDF/runtime/drivers/libc224,096 bytes (~218.8 KiB)~25.8%

Total image size from this build is 869,838 bytes; padded zclaw.bin is 869,952 bytes (~849.6 KiB), under the 888 KiB cap.

Read This Manual In Order

Chapter 1 · Getting Started Bootstrap install, flash, provision, and first successful boot. Chapter 2 · Tool Surface Current built-in tools and scheduling behavior, including one-shot jobs. Chapter 3 · Runtime Anatomy Task model, queues, LLM path, and practical constraints. Chapter 4 · Security & Ops Safety defaults, flash encryption, and production handling guidance. Chapter 5 · Build Your Own Tool Design, create, validate, and maintain custom natural-language tools. Chapter 6 · Local Dev & Hacking Practical local iteration loops, provisioning profiles, and debug workflows. Chapter 7 · Use Cases Useful and playful ideas that are only practical when the assistant lives on your device. Chapter 8 · Changelog Release notes and a timeline of what changed across versions.

Project Character

  • Language/runtime: C + ESP-IDF + FreeRTOS.
  • LLM backends: Anthropic, OpenAI, OpenRouter, Ollama (custom endpoint).
  • Interface: Telegram and optional host web relay.
  • Philosophy: ship useful automation under strict resource bounds.