Seed: 자기 수정이 가능한 최소한의 에이전트 하네스

seed A seed agent: the smallest starting point from which an agent can grow. There is no framework here. The entire frozen layer is seed.py — a small loop that connects a language model to exactly one tool ( exec , which runs bash) and loads its system prompt from a file the agent itself owns and may rewrite. Everything an agent normally gets from a framework — tools, memory, skills, conventions — must instead be grown by the agent, session by session, into its self/ directory. Plant one mkdir my-agent && cd my-agent uvx --from git+https://github.com/vivekhaldar/seed.git seed First run copies seed.py and run_seed.sh into this directory (never overwriting a file that already exists), germinates self/SELF.md , and commits those files together in a fresh git repo here — the loop is part of this individual's history, not only self/ . Then it drops you into a REPL. Start talking. Everything the agent wants to keep must be written into self/ — sessions are ephemeral and nothing else survives. Come back to the same agent with the local runner — no need to uvx again: ./run_seed.sh ./run_seed.sh -m gemini-2.5-pro A verbatim transcript of every session is recorded to self/sessions/*.json (updated after each turn). This is a flight recorder, not memory: the agent never loads it at boot, but you can read it — and the agent may grow tools to study its own past. One seed, many individuals: each directory you plant in grows a different agent, diverging based on what it experiences. Configuration Models and keys are handled entirely by llm (Simon Willison's library). The default model is openai-codex/gpt-5.6-sol , which uses the ChatGPT login from the Codex CLI: codex login # one-time, per machine ./run_seed.sh # uses openai-codex/gpt-5.6-sol ./run_seed.sh -m gemini-2.5-pro # or override it for one session Bundled providers: OpenAI via a Codex subscription or API key, Anthropic, Gemini, and OpenRouter (one OpenRouter key unlocks hundreds of models). Design Why it's shaped this way — McCarthy's metacircular eval, homoiconicity, the prior art, and the risks we consciously accepted: docs/DESIGN.md .