beadboard/skills/beadboard-driver/agents/openai.yaml

interface:
  display_name: "Beadboard Driver"
  short_description: "BeadBoard control-plane workflow for agents in external repos"
  default_prompt: "Use BeadBoard Driver v4 to run evidence-backed bd workflow in the target repo while the user orchestrates via BeadBoard UI; do not mutate project scope, use coordination events/inbox acks, and publish verification-backed closeout notes."
feat(skills): formalize agent coordination via beadboard-driver We moved from ad-hoc task claims to a strictly defined 'Skill' system. Triumphs: - Implemented the 'beadboard-driver' skill, which encodes our project-specific coordination protocols (claim, reservation, handoff). - This ensures that any AI operative (or human supervisor) can participate in the project lifecycle using a unified CLI-driven state machine. - Decoupled high-level mission logic from low-level file mutations, allowing for easier agent skill composition in the future. Raw Honest Moment: Initially, we were just 'winging it' with manual status updates. Formalizing this into a skill was a necessary step to ensure our collaboration is repeatable and resilient to agent context swaps. 2026-02-14 00:23:41 -08:00			`interface:`
			`display_name: "Beadboard Driver"`
checkpoint: pre-split branch cleanup 2026-03-03 16:43:42 -08:00			`short_description: "BeadBoard control-plane workflow for agents in external repos"`
			`default_prompt: "Use BeadBoard Driver v4 to run evidence-backed bd workflow in the target repo while the user orchestrates via BeadBoard UI; do not mutate project scope, use coordination events/inbox acks, and publish verification-backed closeout notes."`