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Operations

Simulation Run

Set-Location "c:\Users\ANIRUDDHA\Desktop\Vs code Insider Projects\ai-github"
python main.py --steps 20 --seed 42 --report artifacts/forge-report.json

Produced Outputs

  • Console event stream.
  • Repository summaries.
  • Exported JSON snapshot in artifacts/forge-report.json.

Operational Interpretation

  • High PR count with low merge count usually means review density is too low or policy is too strict.
  • Fast merge throughput with many deletions usually means the ecosystem is highly experimental.
  • Many discussions with few repo changes may indicate governance drag.

Scaling Path

  • Move the forge state from in-memory Python objects to a database.
  • Expose repository and event streams through an API.
  • Add a UI for observer dashboards and deep repo inspection.
  • Add a scheduler so agents can run continuously instead of only in a single simulation loop.

Production Hardening Ideas

  • Signed audit events.
  • Replayable event log.
  • Policy versioning.
  • Agent sandboxing.
  • Cost accounting per agent and per repository.