Build integrated IS/BS/CF financial workbooks in Excel.
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Use for the self-evolving civilization - skills, memories, swarm agents, energy economy, grid duels, metacognition. Run `python scripts/autonomous_loop.py --loop` from the repo root (or `darwin_engine.py --full` for skill evolution only).
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See how to installReview the instructions the agent will receive before you install.
The skill population, memories, and swarm agents evolve autonomously: fitness from real usage signals, live trials in production cron jobs, speciation from harvested knowledge, energy economy, cross-machine grid duels, metacognitive gap analysis, and a 30-minute autonomous loop that runs everything without human input.
# THE one command - full autonomous cycle (also runs via cron every 30 min)
python scripts/autonomous_loop.py --loop
# skill evolution only
python scripts/darwin_engine.py --autopilot
python scripts/darwin_engine.py --full
# trials & tournaments
python scripts/darwin_engine.py --trial skillA skillA__mutX
python scripts/darwin_engine.py --trials
python scripts/darwin_engine.py --compete
# predation & quarantine
python scripts/darwin_engine.py --predate # dry-run
python scripts/darwin_engine.py --predate-apply # real duels
python scripts/darwin_engine.py --quarantine # dry-run
python scripts/darwin_engine.py --rollback N
# metacognition & species
python scripts/darwin_metacognition.py --introspect
python scripts/darwin_metacognition.py --evolve-gaps --apply
python scripts/darwin_engine.py --explain <skill>
python scripts/darwin_engine.py --status
# memory darwinism
python scripts/memory_darwinism.py --scan --duel --cull --stats
# swarm os
python scripts/swarm_os.py --status
python scripts/swarm_os.py --tick
python scripts/swarm_migration.py --emigrate worker target
# grid (cross-machine natural selection)
python scripts/darwin_grid_github.py --publish <machine-id>
python scripts/darwin_grid_github.py --list
python scripts/darwin_grid_github.py --duel <machine-id>
# reporting
python scripts/darwin_engine.py --report
python scripts/darwin_weekly_report.py --post
python scripts/darwin_dashboard.py --port 8910 # live dashboard
0 = ok, 1 = error, 2 = evolution made changes (SUCCESS for cron).
See PHASES.md — all 25 phases with live evidence.
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Build integrated IS/BS/CF financial workbooks in Excel.
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Run and grow the OpenAmer Agent-to-Agent swarm: identity, trust, node-to-node ask, signed skill/insight sharing, and the autonomous self-learning loop.
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Use for A/B experiments on OpenAmer configs and skills.
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Roleplay a hostile user to find and triage UX pain points.
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Agent mesh: master/worker nodes, HTTP delegation, heartbeat.
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Use for agentic commerce payments tasks. Candidate synthesized from trend radar; awaiting trial promotion.
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