loom-dead-code-check
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prometheus
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64background-jobs
Background job processing patterns including job queues, scheduled jobs, worker pools, and retry strategies. Use when implementing async processing, job queues, workers, task queues, async tasks, delayed jobs, recurring jobs, scheduled tasks, ETL pipelines, data processing, ML training jobs, Celery, Bull, Sidekiq, Resque, cron jobs, retry logic, dead letter queues, DLQ, at-least-once delivery, exactly-once delivery, job monitoring, or worker management.
39testing
Comprehensive test implementation across all domains including unit, integration, e2e, security, infrastructure, data pipelines, and ML models. Covers TDD/BDD workflows, test architecture, flaky test debugging, and coverage analysis.
34karpenter
Kubernetes node autoscaling and cost optimization with Karpenter. Use when implementing node provisioning, spot instance management, cluster right-sizing, node consolidation, or reducing compute costs. Covers NodePool configuration, EC2NodeClass setup, disruption budgets, spot/on-demand mix strategies, multi-architecture support, and capacity-type selection.
31auth
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29dead-code-check
Generates dead code detection configurations for loom plan verification. Provides language-specific commands, fail patterns, and ignore patterns for Rust, TypeScript, Python, Go, and JavaScript. Use when adding code quality checks to acceptance criteria or truths fields in loom plans. Dead code detection catches incomplete wiring by identifying code that exists but is never called.
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