Seed: Minimal, self-modifying agent harness

What the seed is

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.

First run and local runner

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.

Models and providers

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
• OpenRouter (one OpenRouter key unlocks hundreds of models)

Design notes

Why it's shaped this way - McCarthy's metacircular eval, homoiconicity, the prior art, and the risks we consciously accepted: docs/DESIGN.md.