Getting started

Your first successful cap-evolve run, in two minutes, with no API key.

Prerequisites
Python 3.10+ and git. That's it.

1. Clone and enter

git clone https://github.com/skillberry-ai/cap-evolve.git
cd cap-evolve

2. Create a clean environment and install the core

python3 -m venv .venv && source .venv/bin/activate
pip install ./core          # package: cap-evolve-core · CLI: cap-evolve · zero runtime deps
cap-evolve version          # verify

If your default pip index requires auth, append --index-url https://pypi.org/simple.

3. Run the zero-API toy example

toy_calc is a deterministic stand-in agent that only answers correctly when its system prompt contains a [CALC] marker. The mock optimizer adds the marker, so the score provably rises — no model is called.

bash examples/toy_calc/run.sh

Expected output — the seed prompt scores 0.0 on val; the optimized prompt is gate-accepted and scores 1.0 on the sealed test split:

baseline_val 0.0  ->  test_reward 1.0   (gate-accepted, test sealed) + dashboard.html

This is exactly what core/tests/test_e2e_slice.py asserts. The script prints a working directory; open the dashboard.html it writes in any browser to see the run (KPIs, per-iteration diffs, the tasks × iterations heatmap).

4. Where to next

You want to…Go to
Understand what cap-evolve optimizes and how Architecture
Set up a real optimizer/runner (credentials, dashboard) INSTALL.md
Optimize your own agent + benchmark Optimize your own agent
See real benchmark results Results
Something failed TROUBLESHOOTING.md