// Use when porting a workflow to a different AI provider, deployment environment, model tier, or organizational context.
| name | adapt-workflow |
| description | Use when porting a workflow to a different AI provider, deployment environment, model tier, or organizational context. |
| argument-hint | [target context] |
| category | utility |
| version | 2.0.0 |
| user-invocable | true |
Invoke /agent-workflow — it contains workflow principles, anti-patterns, and the Context Gathering Protocol. Follow the protocol before proceeding — if no workflow context exists yet, you MUST run /teach-maestro first. Additionally gather: what the workflow is being adapted to.
Adapt a working workflow for a different context.
| Dimension | Current | Target | Impact |
|---|---|---|---|
| Model provider | ? | ? | Prompt format, capabilities, pricing |
| Model tier | ? | ? | Context window, reasoning ability |
| Deployment env | ? | ? | Latency, availability, compliance |
| Team structure | ? | ? | Monitoring, escalation, ownership |
| Data sensitivity | ? | ? | Guardrails, logging, access controls |
After adaptation, run /evaluate to verify the workflow performs correctly in the target environment, then /diagnose for a full health check.
NEVER:
Use when the workflow is too slow, too expensive, or both and needs latency, cost, or token usage optimization.
Use when any Maestro command is invoked — provides foundational workflow design principles across prompt engineering, context management, tool orchestration, agent architecture, feedback loops, knowledge systems, and guardrails.
Use when the workflow works but needs to handle more complex cases or produce higher-quality output through better tools, context, prompts, or models.
Use when workflow components are inconsistent, naming conventions vary, or a new team member's work needs alignment to project standards.
Capture a session summary — what was done, what decisions were made, and what to do next.
Use when the workflow needs multi-step processing with sequential, parallel, or conditional tool compositions and proper data flow.
