alert to execution workflow builder
by nowrich
Generates production-ready alert pipelines with deduplication, routing, and failure handling.
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Works with the AI tools you already use
See it in action
You say
Generate a pipeline for failed payment events in the checkout service. Needs high priority for 3+ failures, Redis deduplication, and a fallback to PagerDuty if the primary queue fails.
Your agent does
pipeline: name: payment_failure_workflow signal: condition: "event.type == 'payment_failed' AND event.attempts >= 3" cooldown_period: 5m deduplication: strategy: fingerprint cache: redis failure_handling: retry: {max_attempts: 5} fallback_routes: [{target: pager_service}]
What you get
About this skill
The problem
Building reliable alert pipelines manually often leads to noisy notification storms, inconsistent schemas, and silent failures when brokers go down. Developers waste time debugging duplicated alerts or tracing missing signals across fragmented logging systems.
What it does
- Generates precise signal condition specifications with cooldown periods and time-bounded windows.
- Constructs strict JSON schemas for alert payloads to ensure downstream compatibility and data integrity.
- Defines deterministic deduplication policies using fingerprinting to prevent alert fatigue.
- Maps complex broker routing tables based on severity, including delivery semantics and headers.
- Architects failure handling strategies featuring exponential backoff, dead-letter queues, and fallback channels.
Frameworks & tools
Supports YAML/JSON manifests compatible with Redis for deduplication, RabbitMQ/Kafka for brokers, and PagerDuty/Slack for escalations.
Why this beats prompting it yourself
General prompts often miss critical operational safeguards like jittered retries or structured logging across every stage. This skill enforces a standardized architecture that guarantees no critical alert is silently dropped while keeping logs machine-readable for audits.
Use cases
- Designing a critical order-failure pipeline with multi-stage escalations.
- Creating a deduplicated monitoring system for high-volume event streams.
- Standardizing alert schemas across multiple microservices and teams.
- Building resilient DLQ and fallback routing for mission-critical infrastructure.
Known limitations
Requires a pre-validated alert source and target specification. Does not perform actual deployment or direct API calls to cloud providers.
How to install
Drop the file into your AI Agent. Works with Claude, Cursor, ChatGPT, and 20+ more.
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