accelerate
FreeUse when the workflow is too slow, too expensive, or both and needs latency, cost, or token usage optimization.
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Use when the workflow lacks error handling, has been failing in production, or needs retry logic, fallback strategies, and circuit breakers.
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Run score Not tested
See how to installReview the instructions the agent will receive before you install.
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. Consult the guardrails-safety reference in the agent-workflow skill for defense-in-depth patterns and error boundary design.
Make the workflow resilient. Every external call will fail eventually — model APIs, tools, databases, third-party services. Fortify ensures the workflow handles failure gracefully.
Layer 1: Input Validation
Layer 2: Retry with Backoff For transient failures (network errors, rate limits, timeouts):
Retry strategy:
max_retries: 3
initial_delay: 1s
backoff_multiplier: 2
max_delay: 30s
retryable_errors: [429, 500, 502, 503, 504, TIMEOUT, CONNECTION_ERROR]
non_retryable_errors: [400, 401, 403, 404]
Layer 3: Fallback Responses When retries are exhausted:
Layer 4: Circuit Breakers When a service is consistently failing:
Circuit breaker:
failure_threshold: 5 consecutive failures
state: CLOSED → OPEN (after threshold) → HALF_OPEN (after cooldown)
cooldown: 60 seconds
half_open_max_requests: 1
Layer 5: Timeout Controls Every external call needs a timeout:
For each component, verify:
After fortification, run /evaluate to verify error handling works under realistic failure scenarios.
NEVER:
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Use when the workflow is too slow, too expensive, or both and needs latency, cost, or token usage optimization.
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Use when porting a workflow to a different AI provider, deployment environment, model tier, or organizational context.
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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.
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Use when the workflow works but needs to handle more complex cases or produce higher-quality output through better tools, context, prompts, or models.
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Use when workflow components are inconsistent, naming conventions vary, or a new team member's work needs alignment to project standards.
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Capture a session summary — what was done, what decisions were made, and what to do next.
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