Ethan Agent — AI skill for Claude Code
A lightweight, high-performance personal AI agent.
How to install Ethan Agent
This entry records only its repository, not the path inside it, so there is no
exact command to give. Open llm011/ethan-agent and copy the folder into
~/.claude/skills/, or the file into ~/.claude/agents/.
What Ethan Agent does
A lightweight, high-performance personal AI agent. Fast async core, pluggable tools, and open integration with external agent ecosystems (Claude Code, Codex, MCP). Simple to configure, easy to extend.
Alternatives in AI
- Deepreasoning — A high-performance LLM inference API and Chat UI that integrates DeepSeek R1's CoT reasoning traces with Anthr 5.4k ★
- Vllm Mlx — High-performance OpenAI and Anthropic compatible LLM inference server for Apple Silicon 1.5k ★
- Easy LLM CLI — An open-source AI agent that is compatible with multiple LLM models 1.3k ★
README
Ethan Agent
[中文文档](./README_CN.md)
A lightweight, extensible personal AI agent built in Python. Designed to run persistently on your own hardware with memory that grows over time, scheduled tasks, and a pluggable tool/skill system.
Ethan combines ideas from [OpenClaw](https://github.com/openclaw/openclaw) (structured agent loop, layered memory), [Hermes Agent](https://github.com/NousResearch/hermes-agent) (self-improving skills, memory consolidation), and [nanobot](https://github.com/HKUDS/nanobot) (minimal core, readable codebase).
Features
**Memory system**
- Structured long-term memory (
memory.db, the single source of truth for user facts): short sessions (<3 turns) extract immediately, then incrementally every 3 turns — each candidate carries an exact quote from a user message — and is deterministically admitted — explicit → active immediately, observed → promoted only after ≥2 independent sessions. 64 typed dimensions across 7 categories (personal info / preference / activity / decision / relationship / methodology / companion), with TTL expiry, supersede chains, and redaction-on-forget - Semantic recall & dedup: hybrid FTS5 + BGE vector retrieval (RRF-fused) feeds a single
prompt block; at admission, embedding near-neighbors are paired and merged/superseded by deterministic rules ("住在深圳" ≈ "家在深圳南山" never stored twice) - Memory decay & reinforcement: fully deterministic tier rules (zero LLM) — identity/preference/companion memories are exempt from decay; project scopes idle for 21 days are archived (dormant, restorable at any time); tentative decisions ("先试试") sink on a 3-day ranking half-life; evidence repeated across independent sessions promotes confidence up a ladder (2→0.8, 3→0.9, 5→0.95). Value is voted by future behavior: recurrence reinforces, long silence archives
- Dimension registry: the extraction prompt's dimension guide and the validation whitelist are both generated from one declarative registry
Related Skills
Ataru
High-performance AI memory retrieval for local agent history — a Rust search core (SDK / API / JSON CLI) plus
Postline
Your AI coding agent, in your pocket — a lightweight, extensible mobile front-end for Claude Code / Codex. Dri
Laya Fast Router
A lightweight decision routing model designed to replace slow, expensive LLMs for simple classification and co
Late CLI
High-performance AI agent for long-horizon tasks and local models. Built on empirical research. 200k+ tokens o
Karpathy LLM Wiki Stack
A comprehensive, build-ready reference for constructing a high-performance personal knowledge system using Obs
Kerux
A high-performance Rust implementation orchestration loop for LLM-driven tool execution.
Related Agents
Async Code
Use Claude Code or CodeX CLI to perform multiple tasks in parallel with a Codex-style UI, functioning as a per
Plugins
Agent Plugin System - manages the pluggable AI agent architecture (Claude, Cursor, Gemini). Use proactively wh
Dnp TDD Developer Easy
⚡ Fast TDD for routine .NET tasks: clear requirements, low-risk changes, well-defined scope. Writes both tests