sharpdeveye/maestro

accelerate

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

Langue du texte source : anglais

adapt-workflow

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

Langue du texte source : anglais

agent-workflow

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.

Langue du texte source : anglais

amplify

Use when the workflow works but needs to handle more complex cases or produce higher-quality output through better tools, context, prompts, or models.

Langue du texte source : anglais

calibrate

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

Langue du texte source : anglais

capture

Capture a session summary — what was done, what decisions were made, and what to do next.

Langue du texte source : anglais

chain

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

Langue du texte source : anglais

compose

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

Langue du texte source : anglais

diagnose

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

Langue du texte source : anglais

enrich

Use when the agent needs access to information beyond its training data — knowledge sources, RAG pipelines, or grounding data.

Langue du texte source : anglais

evaluate

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

Langue du texte source : anglais

extract-pattern

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

Langue du texte source : anglais

fortify

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

Langue du texte source : anglais

guard

Use when deploying to production, handling sensitive data, or the workflow needs safety constraints, input validation, and security boundaries.

Langue du texte source : anglais

iterate

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

Langue du texte source : anglais

onboard-agent

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

Langue du texte source : anglais

recap

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

Langue du texte source : anglais

refine

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

Langue du texte source : anglais

reflect

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

Langue du texte source : anglais

specialize

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

Langue du texte source : anglais

streamline

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

Langue du texte source : anglais

teach-maestro

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

Langue du texte source : anglais

temper

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

Langue du texte source : anglais

turbocharge

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

Langue du texte source : anglais

zero-defect

Use when you need maximum precision on a critical task — production deployments, security-sensitive code, financial calculations, or any work where mistakes are unacceptable.

Langue du texte source : anglais