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Generated from docs/home.md at df1dbe1. Edit the repository file, not the wiki.

Scrum Around and Find Out

A GitHub Project defined as code, an Action that applies it and keeps it current, and a playbook for running a small team of AI agents (Claude, Codex, Copilot) under one human maintainer, with the lessons that shaped it.

Read in this order

  • Why: the problem, and the idea that the board is the one place work is visible.
  • Roles and Routing: who does what, and which agent a task goes to (routing is generated from agents.yaml).
  • Personas: the four roles (implementer, reviewer, adversarial reviewer, transcriber) and six packs defined in the Department of Internal Arguments, how SAFO relates to them, and how to install and update them.
  • Agent profiles: how to brief each agent, with every claim tied to a pointer at a measurement (the loader, the evidence check and the rendering into examples/harness/ are built).
  • Usage, routing and outcomes: measure what each agent has left, get a recommendation, and keep a log of how it went.
  • safo hooks: how Claude Code is made to hold the lead to agents.yaml, and what the guard cannot prove.
  • Handoff: how work moves from a card to a merged pull request without losing the thread.
  • The review loop: the implement, review, fix and adversarial cycle, with what the build showed.
  • Local LLM: what a local model is good and bad at, and the guard that keeps it from evicting a resident model.
  • Limits: reading each tool's real usage and deciding when to switch.
  • Board and the board.yaml reference: the project as code.
  • agents-status: one read-only view of what every agent is doing.
  • Lessons: what went wrong, the evidence, and the rule the code enforces now.
  • Measurements: what the first month measured, dated and aggregated, and what is not measured yet.
  • Adoption: create an App, write a board.yaml, run it.
  • Privacy check: what the public files are scanned for, and how to add your own private terms safely.

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