sharpdeveye

Use when the user wants a quality review, interaction audit, or to test the workflow against realistic scenarios.

Use when the workflow lacks error handling, has been failing in production, or needs retry logic, fallback strategies, and circuit breakers.

Analyze command history to identify which skills work, which fail, and where to improve.

Use when the workflow needs to self-correct, improve over time, or establish feedback loops and evaluation cycles.

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 the user wants to push past conventional workflow limits with advanced performance techniques like parallel orchestration, streaming pipelines, or adaptive routing.

Use when porting a workflow to a different AI provider, deployment environment, model tier, or organizational context.

Use when the workflow needs multi-step processing with sequential, parallel, or conditional tool compositions and proper data flow.

Use when starting a new project, adding a new agent to an existing system, or setting up workflow infrastructure from scratch.

Use when the user wants to create templates, extract reusable patterns, document solutions, or build a pattern library from working workflows.

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 workflow components are inconsistent, naming conventions vary, or a new team member's work needs alignment to project standards.

Use when a single agent demonstrably cannot handle the task and multi-agent coordination is justified.

Use when the workflow feels too complex, has accumulated cruft, or has redundant steps and overlapping tools that need consolidation.

Use when the workflow works but needs polish, or as the final step in a diagnose → fix → refine cycle before shipping.

Use when the user wants to tailor a workflow for a specific industry, domain, or vertical with specialized expertise, terminology, and guardrails.

MCP server for Maestro — exposes 25 workflow skills as tools, prompts, and resources for any MCP-compatible AI client

Use when starting a new project with Maestro or when no .maestro.md context file exists yet. Run once per project.

Use when the user wants to find problems, audit workflow quality, or get a comprehensive health check on their AI workflow.

Use when the workflow is too slow, too expensive, or both and needs latency, cost, or token usage optimization.

Use when the workflow feels over-engineered, has premature optimizations, unnecessary abstraction layers, or complexity beyond actual requirements.

Quick summary of the last session — commands run, files changed, and what to do next.