Not the parent, but:
You define roles for different agents like this:
modelRoles:
task: fireworks/kimi-k3-fast:high
plan: fireworks/kimi-k3-fast:max
slow: fireworks/kimi-k3-fast:max
smol: fireworks/deepseek-v4-flash-0731:low
tiny: fireworks/gpt-oss-20b
vision: fireworks/qwen3.7-plus:high
designer: fireworks/qwen3.7-plus:high
advisor: openai-codex/gpt-5.6-sol:high
main_worker: fireworks/kimi-k3-fast:high
fast_worker: fireworks/deepseek-v4-flash-0731:low
vision_worker: fireworks/qwen3.7-plus:high
research_worker: fireworks/glm-5.2:medium
code_worker: fireworks/kimi-k2.7-code-fast:high
review_worker: anthropic/claude-fable-5:high
security_review_worker: fireworks/kimi-k3-fast:max
minimal_worker: fireworks/gpt-oss-20b
default: fireworks/kimi-k3-fast
task:
agentModelOverrides:
task: "@main_worker"
sonic: "@fast_worker"
scout: "@fast_worker"
designer: "@vision_worker"
librarian: "@research_worker"
reviewer: "@review_worker"
security-reviewer: "@security_review_worker"
Then you first say /plan and use some big model like K3. Finally the harness shows you a markdown you approve, and in approval you switch to a smaller model and reset the context. The smaller model gets the full plan and starts working on it. When done, you say /review and it spawns N review agents and returns the change suggestions. And you iterate on that.