verdigraph-neurogenesis

Clone this repo, run one script, and within 60 seconds you're building deterministic, content-addressed brain artifacts from any agent file — Claude project export, OpenAI Assistant config, raw prompt list, or Verdigraph genome JSON. Pure Python core; zero external services required.

60-second quickstart

git clone https://github.com/viridis-security/verdigraph-neurogenesis
cd verdigraph-neurogenesis
bash quickstart.sh

That's it. The script creates a venv, installs the package editable, runs the brain builder against an example genome, and prints the deterministic brain_id + content_hash. No Cloudflare account, no Stripe key, no verdigraph.dev account needed. Everything runs locally.

If you also have an internet connection, the script will additionally hit https://verdigraph.dev/app/import with the same input bytes and confirm the hosted Worker produces the exact same brain_id — that's your proof the local build is byte-equivalent to the production reference implementation.

What it is

Verdigraph turns an agent file into an inspectable cognitive graph with a content-addressed identifier you can pin in git, cite in an audit, or paste into a code review. Three things make this useful:

1. Determinism. Identical input bytes always produce identical brain_id, content_hash, and graph structure. Run it twice, get the same answer twice. Run it in Python locally; run it in TypeScript on the Worker; same answer either way.
2. Inspectable structure. Every brain carries 9 firing invariants + 1 advisory check (I9_fitness_metric_wired) so you can prove what the agent file actually compiles to without trusting a black box.
3. Self-contained build pipeline. No external dependencies beyond the Python stdlib. No SaaS lock-in. You can audit every line of verdigraph/brain.py (≈ 660 lines) in an afternoon.

Use it

Build a brain from a Verdigraph genome

python -m verdigraph build --file examples/hypothetical_research_agent.genome.json --format verdigraph_genome --pretty

Or pipe input:

cat my_agent.json | python -m verdigraph build --stdin --format auto --summary --pretty

Build from a Claude project export

python -m verdigraph build --file my_claude_project_export.json --format claude_project_export --pretty

Build from an OpenAI Assistant config

python -m verdigraph build --file my_assistant.json --format openai_assistant --pretty

Build from a flat prompt list

echo -e "You are a helpful assistant.\nSummarize the user's request.\nPlan steps and execute." \
  | python -m verdigraph build --stdin --format prompt_list --pretty

Re-verify a saved brain artifact

python -m verdigraph build --file my_agent.json --pretty > brain.json
python -m verdigraph verify brain.json

Use it as a Python library

from verdigraph.brain import extract, verify_brain, to_dict

genome = b'{"agent_name":"my_agent","purpose":"...","initial_nodes":["planner","executor"],"fitness_metrics":["task_success_rate"]}'

brain = extract("verdigraph_genome", genome)
print(brain.brain_id)        # e.g. RMX124YY916WP0TCSEHFYX7M30
print(brain.brain_uri)       # verdigraph://brain/RMX124YY916WP0TCSEHFYX7M30
print(brain.content_hash)    # sha256 hex
print(len(brain.nodes), "nodes,", len(bra

... [View full README on GitHub](https://github.com/viridis-security/verdigraph-neurogenesis#readme)