Problem
The current OMOC swarm and dispatch delegation architecture is fragile and heavily relies on oh-my-opencode's hardcoded fallback chains. When an agent's primary model and limited fallbacks fail, the plugin defaults to xai/grok or anthropic/claude-haiku-4-5, leading to unwanted model usage and task failures. The user explicitly stated: "wir haben dispatch funktionen gebaut für omoc swarm usw aber das wurde gut gedacht und extrem, aber ultra schlecht umgesetzt! mach das von grundauf neu!"
Goal
Redesign the agent dispatch and delegation architecture from the ground up.
Steps
- Exhaustive Config Overrides: Update
oh-my-openagent.json with 4-5 fallback models per agent to guarantee we never hit the plugin's hardcoded layer. (Completed)
- Skill Redesign: Refactor
omoc-plan-swarm and check-plan-done to use robust, deterministic delegation.
- Dispatch Logic: Implement explicit model/provider validation before delegation.
- Live Verification: Ensure delegates always route to approved models (GPT-5.4, Antigravity Claude/Gemini, GLM-5.1, Qwen).
Subtasks
Problem
The current OMOC swarm and dispatch delegation architecture is fragile and heavily relies on
oh-my-opencode's hardcoded fallback chains. When an agent's primary model and limited fallbacks fail, the plugin defaults toxai/grokoranthropic/claude-haiku-4-5, leading to unwanted model usage and task failures. The user explicitly stated: "wir haben dispatch funktionen gebaut für omoc swarm usw aber das wurde gut gedacht und extrem, aber ultra schlecht umgesetzt! mach das von grundauf neu!"Goal
Redesign the agent dispatch and delegation architecture from the ground up.
Steps
oh-my-openagent.jsonwith 4-5 fallback models per agent to guarantee we never hit the plugin's hardcoded layer. (Completed)omoc-plan-swarmandcheck-plan-doneto use robust, deterministic delegation.Subtasks
oh-my-openagent.jsoncall_omo_agentusage in swarm skills