ivanshamaev/de-agent-skills

aiops-autonomous-incident-response

When your agent uses it

AIOps autonomous incident response agent — LLM-driven diagnosis loop (Claude tool-use agent with kubectl/SQL/Prometheus tools), alert-to-action pipeline (PagerDuty webhook → agent trigger), automated RCA generation (failure taxonomy + log correlation), self-healing action executor with approval gate, incident severity classification, runbook automation (structured YAML runbooks executed by agent), escalation logic, incident timeline auto-generation, Slack integration for human-in-the-loop approvals

What it loads into context

Token counts are estimates. Scripts run separately; they are not counted as reference context.

No excerpt is shown for this license. Read the source on GitHub.

View the complete source on GitHub

aiops-capacity-planning-agent

When your agent uses it

AIOps capacity planning agent — predictive resource forecasting (Prophet/linear regression on Prometheus metrics), Kubernetes HPA/VPA right-sizing recommendations, node capacity headroom calculator, Kafka partition and broker capacity model, Spark executor sizing from job history, data lake storage growth forecast (S3/GCS), cluster autoscaler simulation, automatic HPA threshold tuning, cost-per-job attribution, capacity planning report generator

What it loads into context

Token counts are estimates. Scripts run separately; they are not counted as reference context.

No excerpt is shown for this license. Read the source on GitHub.

View the complete source on GitHub

aiops-infrastructure-anomaly-detection

When your agent uses it

AIOps infrastructure anomaly detection — statistical baseline (z-score/IQR/seasonal decomposition), Prometheus anomaly rules (predict_linear/stddev_over_time/MAD), ML-based detection (Isolation Forest/Prophet/LSTM autoencoder on metrics), metric correlation clustering, automated alert threshold tuning from historical data, Kubernetes resource anomaly detection, data pipeline anomaly signals (row count z-score/freshness drift/throughput drop), Python sklearn/Prophet integration, Grafana anomaly panel

What it loads into context

Token counts are estimates. Scripts run separately; they are not counted as reference context.

No excerpt is shown for this license. Read the source on GitHub.

View the complete source on GitHub

aiops-observability-copilot

When your agent uses it

AIOps observability copilot — natural language to PromQL/LogQL translation, alert explanation in plain English (what fired/why/impact), Grafana dashboard auto-generation from service topology, anomaly narrative generation from metric patterns, on-call context enrichment (related alerts/recent deploys/runbook links), log pattern clustering for noise reduction, SLO status explanation, automated weekly observability health digest

What it loads into context

Token counts are estimates. Scripts run separately; they are not counted as reference context.

No excerpt is shown for this license. Read the source on GitHub.

View the complete source on GitHub

aiops-platform-optimization-agent

When your agent uses it

AIOps continuous platform optimization agent — autonomous optimization loop (observe→analyze→recommend→apply), Kubernetes resource rightsizing (VPA recommendation reader + apply), Kafka consumer lag auto-scale, Spark job configuration tuning from history, idle resource detection (unused deployments/PVCs/topics), compaction and VACUUM scheduling, auto-ANALYZE stale statistics, cost savings attribution, optimization audit trail, human approval gate for high-risk changes

What it loads into context

Token counts are estimates. Scripts run separately; they are not counted as reference context.

No excerpt is shown for this license. Read the source on GitHub.

View the complete source on GitHub

aiops-query-cost-analyzer

When your agent uses it

AIOps autonomous query cost analyzer — Trino system.runtime.query_history cost SQL (CPU time/peak memory/bytes scanned), ClickHouse system.query_log top expensive queries, Spark UI cost attribution by user/job/DAG, BigQuery INFORMATION_SCHEMA.JOBS cost analysis, LLM-driven query rewrite recommendations (missing partition filters/broadcast hints/aggregation pushdown), cost anomaly detection (user over daily budget), automated query tagging, chargeback report by team/project

What it loads into context

Token counts are estimates. Scripts run separately; they are not counted as reference context.

No excerpt is shown for this license. Read the source on GitHub.

View the complete source on GitHub

dataops-airflow-cost-optimizer

When your agent uses it

Airflow cost optimization — KubernetesPodOperator right-sizing (request vs actual CPU/memory), spot node tolerations for batch tasks, task consolidation (reduce pod-per-task overhead), pool-based concurrency control, idle worker cleanup, log retention policy (S3 lifecycle), metadata DB right-sizing, CeleryExecutor worker autoscaling (KEDA Kafka/queue depth), DAG run frequency analysis (oversceduled DAGs), cloud cost attribution per DAG

What it loads into context

Token counts are estimates. Scripts run separately; they are not counted as reference context.

No excerpt is shown for this license. Read the source on GitHub.

View the complete source on GitHub

dataops-airflow-ha-review

When your agent uses it

Airflow high availability review — multi-scheduler setup (HA schedulers with PostgreSQL row-level locking), CeleryExecutor worker pool sizing, KubernetesExecutor pod limits, metadata DB HA (PostgreSQL HA with PgBouncer connection pooling), DAG sync strategy (git-sync sidecar/S3/GitDagBundle), log storage (S3/GCS), webserver multi-replica, triggerer HA, rolling upgrades without downtime, Celery Flower monitoring, heartbeat alerts

What it loads into context

Token counts are estimates. Scripts run separately; they are not counted as reference context.

No excerpt is shown for this license. Read the source on GitHub.

View the complete source on GitHub

dataops-airflow-observability

When your agent uses it

Airflow observability — StatsD/OpenTelemetry metrics (scheduler_heartbeat/task_duration/pool_open_slots/dag_processing_total_parse_time), Prometheus scraping, Grafana dashboards (DAG success rate/task duration/slot utilization), structured task logging (JSON formatter), OpenTelemetry traces for task spans, DAG SLA miss alerts, anomaly detection on task duration, Airflow audit log, DagBag parse error monitoring, dead letter queue for failed tasks

What it loads into context

Token counts are estimates. Scripts run separately; they are not counted as reference context.

No excerpt is shown for this license. Read the source on GitHub.

View the complete source on GitHub

dataops-airflow-production-readiness

When your agent uses it

Airflow production readiness — idempotent tasks (UPSERT/partition overwrite), no top-level code at DAG parse time (Variable.get inside tasks), KubernetesExecutor configuration, connection/variable management (no hardcoded secrets), SLA callbacks, retry with exponential backoff, pool management, max_active_runs, dag_concurrency, celery vs kubernetes executor trade-offs, metadata DB maintenance (airflow db clean), health check endpoints, structured logging

What it loads into context

Token counts are estimates. Scripts run separately; they are not counted as reference context.

No excerpt is shown for this license. Read the source on GitHub.

View the complete source on GitHub

dataops-blue-green-deployment

When your agent uses it

Blue/green deployment for data platforms — Kubernetes blue/green with service selector swap, Argo Rollouts blue-green strategy, database schema migration compatibility (backward-compatible DDL), dbt blue/green schema swap (swap_schema macro), Airflow DAG versioning (dag_id with version suffix), traffic cutover and rollback procedure, smoke tests before cutover, Canary vs blue/green decision guide

What it loads into context

Token counts are estimates. Scripts run separately; they are not counted as reference context.

No excerpt is shown for this license. Read the source on GitHub.

View the complete source on GitHub

dataops-cicd-pipeline-review

When your agent uses it

DataOps CI/CD pipeline review — pipeline stages for data projects (lint/test/build/scan/deploy), trunk-based vs GitFlow branching, environment promotion (dev→staging→prod), artifact versioning (Docker image tags/dbt manifest), deployment gating (DQ checks/smoke tests/manual approval), rollback strategy, pipeline observability (DORA metrics), reusable workflow patterns, monorepo vs polyrepo CI strategy

What it loads into context

Token counts are estimates. Scripts run separately; they are not counted as reference context.

No excerpt is shown for this license. Read the source on GitHub.

View the complete source on GitHub

dataops-disaster-recovery-review

When your agent uses it

Disaster recovery review for data platforms — RTO/RPO definitions, DR strategy selection (cold/warm/hot standby), Airflow metadata DB backup and restore (pg_dump/WAL), Kafka topic replication (MirrorMaker2), data lake replication (S3 CRR/GCS Transfer), Kubernetes cluster backup (Velero), runbook for DR failover, DR testing (game day exercises), backup validation, cross-region Terraform, recovery time measurement

What it loads into context

Token counts are estimates. Scripts run separately; they are not counted as reference context.

No excerpt is shown for this license. Read the source on GitHub.

View the complete source on GitHub

dataops-github-actions-optimizer

When your agent uses it

GitHub Actions optimization for DataOps — path filters to skip unchanged components, concurrency groups (cancel-in-progress), job parallelization, caching strategies (pip/npm/Maven/Docker layers), self-hosted runners for heavy workloads, matrix strategy for multi-environment tests, reusable workflows to reduce duplication, OIDC for cloud credentials (no static keys), artifact retention, workflow timing analysis

What it loads into context

Token counts are estimates. Scripts run separately; they are not counted as reference context.

No excerpt is shown for this license. Read the source on GitHub.

View the complete source on GitHub

dataops-jenkins-modernization

When your agent uses it

Jenkins modernization for DataOps — migration from Freestyle to Declarative Pipeline, Jenkinsfile best practices, shared libraries (vars/src structure), parallel stages, Kubernetes agent pods (docker-in-docker vs kaniko), credential management (withCredentials/Jenkins Credential Store), pipeline-as-code with Multibranch Pipeline, Blue Ocean UI, migration path to GitHub Actions, JCasC (Jenkins Configuration as Code)

What it loads into context

Token counts are estimates. Scripts run separately; they are not counted as reference context.

No excerpt is shown for this license. Read the source on GitHub.

View the complete source on GitHub

dataops-postmortem-generator

When your agent uses it

DataOps blameless postmortem generation — severity matrix (SEV1-4), postmortem Markdown template with timeline/impact/root cause/action items, 3 filled-in examples (Kafka rebalance/dbt incremental data loss/ClickHouse schema mutation), CAPA framework (Corrective/Action/Preventive/Action), impact quantification SQL, stakeholder communication templates, 60-min facilitation guide, postmortem review checklist, Git-based postmortem repository management

What it loads into context

Token counts are estimates. Scripts run separately; they are not counted as reference context.

No excerpt is shown for this license. Read the source on GitHub.

View the complete source on GitHub

dataops-release-readiness-review

When your agent uses it

Release readiness review for data platforms — pre-release checklist (schema migrations tested, backward compatibility, rollback plan), runbook completeness, monitoring and alerting configured, on-call handoff, load/soak testing results, data reconciliation between versions, feature flag strategy, go/no-go criteria, post-release validation (15-min/1-hour/24-hour checkpoints), communication templates

What it loads into context

Token counts are estimates. Scripts run separately; they are not counted as reference context.

No excerpt is shown for this license. Read the source on GitHub.

View the complete source on GitHub

dataops-root-cause-analysis

When your agent uses it

Root cause analysis for DataOps incidents — 5-Why analysis for pipeline failures, failure taxonomy (infrastructure/data/logic/dependency/config/concurrency), Airflow diagnosis (task state SQL/scheduler heartbeat/DagBag errors), Spark diagnosis (OOM/skew/FetchFailed/serialization), Kafka consumer lag spike RCA, data quality anomaly investigation (volume/freshness/distribution shift), log correlation across components, timeline reconstruction, impact quantification SQL

What it loads into context

Token counts are estimates. Scripts run separately; they are not counted as reference context.

No excerpt is shown for this license. Read the source on GitHub.

View the complete source on GitHub

dataops-self-healing-platform

When your agent uses it

Self-healing data platform — auto-restart failed Airflow DAGs (idempotency required), Kafka consumer group auto-resume after partition rebalance, circuit breaker for flapping pipelines, automatic partition backfill on gap detection, auto-scale Kubernetes resources on OOM detection, stale statistics auto-ANALYZE, DQ gate auto-quarantine pattern, dead letter queue reprocessing, watchdog agents for heartbeat monitoring, self-healing Airflow sensor (RoutineLoadLagSensor pattern)

What it loads into context

Token counts are estimates. Scripts run separately; they are not counted as reference context.

No excerpt is shown for this license. Read the source on GitHub.

View the complete source on GitHub

dataops-sla-monitoring

When your agent uses it

Data platform SLA monitoring — freshness SLAs (data available by X:XX), completeness SLAs (row count variance < N%), latency SLAs (pipeline completes within N minutes), SLA breach detection (Prometheus/Soda/SQL), SLA burn rate alerting, SLA reporting dashboards, SLA miss root cause linking, cascading SLA dependencies (upstream delay propagation), SLA definition process, error budget tracking, consumer notification on SLA breach

What it loads into context

Token counts are estimates. Scripts run separately; they are not counted as reference context.

No excerpt is shown for this license. Read the source on GitHub.

View the complete source on GitHub

dataops-workflow-orchestration-review

When your agent uses it

Workflow orchestration comparison and review — Airflow vs Prefect vs Dagster vs Temporal (architecture, execution model, dependency management, observability), when to choose each, migration patterns from Airflow to Prefect/Dagster, orchestrator evaluation scorecard, event-driven vs schedule-based triggering, Software-Defined Assets (Dagster) vs task-based (Airflow), hybrid orchestration patterns

What it loads into context

Token counts are estimates. Scripts run separately; they are not counted as reference context.

No excerpt is shown for this license. Read the source on GitHub.

View the complete source on GitHub

infra-alert-fatigue-reduction

When your agent uses it

Alert fatigue reduction — SLO-based alerting (burn rate vs threshold), multi-window burn rate alerts (short/long window), AlertManager inhibition and silencing, alert deduplication (group_by), routing by severity (PagerDuty for critical / Slack for warning), alert ownership labels, runbook links in annotations, alert review process (weekly noise audit), flapping detection (for/pending period tuning), absent() vs rate() alerting patterns, ticket-based escalation for warning-level noise

What it loads into context

Token counts are estimates. Scripts run separately; they are not counted as reference context.

No excerpt is shown for this license. Read the source on GitHub.

View the complete source on GitHub

infra-aws-data-platform-review

When your agent uses it

AWS data platform review — S3 data lake (lifecycle/replication/encryption/access points), EMR vs Glue ETL trade-offs, MSK Kafka configuration, RDS/Aurora for metadata, Redshift vs Athena for analytics, MWAA (managed Airflow), EKS for containerized pipelines, IAM roles (IRSA for EKS/EMREC2 instance profiles), Lake Formation row/column security, AWS Glue catalog, VPC data platform networking, cost optimization (S3 Intelligent-Tiering/Spot instances)

What it loads into context

Token counts are estimates. Scripts run separately; they are not counted as reference context.

No excerpt is shown for this license. Read the source on GitHub.

View the complete source on GitHub

infra-azure-data-platform-review

When your agent uses it

Azure data platform review — ADLS Gen2 (hierarchical namespace/RBAC/lifecycle), Azure Synapse vs Databricks vs HDInsight trade-offs, Event Hubs (Kafka protocol compatible), ADF vs Azure Databricks for ETL, Azure Managed Airflow, AKS with Workload Identity (AAD Pod Identity), Key Vault for secrets, Azure Monitor/Log Analytics, Purview for data catalog/lineage, Private Endpoints for data services, cost management (reserved instances/spot VMs)

What it loads into context

Token counts are estimates. Scripts run separately; they are not counted as reference context.

No excerpt is shown for this license. Read the source on GitHub.

View the complete source on GitHub

infra-compliance-readiness

When your agent uses it

Compliance readiness for data platforms — SOC2 Type II controls mapping (CC6/CC7/CC8), GDPR data processing requirements (PII inventory/right-to-erasure/data residency), PCI-DSS data platform scope reduction, CIS Benchmarks (Kubernetes/AWS/GCP), audit log completeness (Vault/Kubernetes/cloud trail), data retention and deletion policies, encryption at rest/transit evidence, access review processes, compliance-as-code (OPA policies), vulnerability management (CVE SLA)

What it loads into context

Token counts are estimates. Scripts run separately; they are not counted as reference context.

No excerpt is shown for this license. Read the source on GitHub.

View the complete source on GitHub

infra-docker-best-practices

When your agent uses it

Docker best practices — multi-stage builds (builder/runtime separation), layer cache optimization (dependency install before source copy), minimal base images (distroless/alpine/slim), security hardening (non-root USER, read-only FS, no SUID binaries), .dockerignore patterns, BuildKit secrets for private registries, image vulnerability scanning (Trivy), COPY vs ADD, CMD vs ENTRYPOINT patterns, data engineering Dockerfiles (dbt/Spark/Python ETL)

What it loads into context

Token counts are estimates. Scripts run separately; they are not counted as reference context.

No excerpt is shown for this license. Read the source on GitHub.

View the complete source on GitHub

infra-gcp-data-platform-review

When your agent uses it

GCP data platform review — BigQuery (dataset IAM/column-level security/partitioned tables/clustering/reservations), GCS data lake (uniform bucket-level access/lifecycle/CMEK), Dataproc vs Dataflow vs Spark on GKE, Pub/Sub streaming, Cloud Composer (managed Airflow), Workload Identity for GKE, VPC Service Controls, Data Catalog, Dataplex for data governance, BigQuery cost optimization (slot reservations vs on-demand), Cloud Logging/Monitoring

What it loads into context

Token counts are estimates. Scripts run separately; they are not counted as reference context.

No excerpt is shown for this license. Read the source on GitHub.

View the complete source on GitHub

infra-gitops-deployment-review

When your agent uses it

GitOps deployment review — ArgoCD Application/AppProject CRDs, app-of-apps pattern, sync policies (automated+self-heal+prune), drift detection and remediation, FluxCD HelmRelease/Kustomization, git repository structure for GitOps (app code vs config repo separation), image update automation, progressive delivery (Argo Rollouts canary/blue-green), GitOps for data platform components (Airflow/Kafka/Spark)

What it loads into context

Token counts are estimates. Scripts run separately; they are not counted as reference context.

No excerpt is shown for this license. Read the source on GitHub.

View the complete source on GitHub

infra-grafana-dashboard-review

When your agent uses it

Grafana dashboard review — panel types (timeseries/stat/gauge/table/heatmap), variable templating (datasource/label_values/query), dashboard linking and drilldown, data platform dashboards (pipeline overview/DAG health/Kafka throughput/Spark performance), alerting from panels, annotation markers for deployments, dashboard-as-code (Grafonnet/Terraform grafana provider), performance optimization (query caching/recording rules), dark/light theme standards

What it loads into context

Token counts are estimates. Scripts run separately; they are not counted as reference context.

No excerpt is shown for this license. Read the source on GitHub.

View the complete source on GitHub

infra-kafka-cost-optimizer

When your agent uses it

Kafka cost optimization — tiered storage (S3/GCS remote log offload, local.retention.ms vs retention.ms), topic retention right-sizing (per-topic audit SQL), log compaction economics, partition count right-sizing (over-partitioned cluster detection), consumer group idle cleanup, broker instance right-sizing (disk vs compute), Redpanda vs Confluent Cloud cost comparison, MirrorMaker2 cross-region cost, compression savings calculator

What it loads into context

Token counts are estimates. Scripts run separately; they are not counted as reference context.

No excerpt is shown for this license. Read the source on GitHub.

View the complete source on GitHub

infra-kafka-platform-review

When your agent uses it

Kafka production platform review — broker configuration (replication factor/min.insync.replicas/rack awareness/KRaft mode), topic design (partition count formula/compaction/retention), consumer group management (lag monitoring/rebalance tuning/cooperative sticky), producer tuning (acks/idempotence/compression/batching), security (SASL_SSL/ACLs/mTLS), JMX metrics to Prometheus (kafka-exporter/JMX exporter), alert rules (under-replicated partitions/ISR shrink/consumer lag/disk), capacity planning, Strimzi Kubernetes operator

What it loads into context

Token counts are estimates. Scripts run separately; they are not counted as reference context.

No excerpt is shown for this license. Read the source on GitHub.

View the complete source on GitHub

infra-kubernetes-autoscaling-review

When your agent uses it

Kubernetes autoscaling review — HPA (CPU/memory/custom/external metrics), stabilizationWindowSeconds anti-flapping, VPA vs HPA decision, Cluster Autoscaler tuning (scale-down delay/utilization threshold), KEDA event-driven autoscaling (Kafka lag/queue depth), spot node optimization, pod disruption budgets, scaling behavior policies (Percent/Pods/Max/Min selectPolicy)

What it loads into context

Token counts are estimates. Scripts run separately; they are not counted as reference context.

No excerpt is shown for this license. Read the source on GitHub.

View the complete source on GitHub

infra-kubernetes-cluster-health

When your agent uses it

Kubernetes cluster health assessment — node status and pressure conditions (disk/memory/PID), pod failure diagnosis (CrashLoopBackOff/OOMKilled/Pending/Evicted), control plane health (API server/etcd/scheduler/controller-manager), resource quota utilization, scheduling failures (taints/affinity/insufficient resources), kubectl diagnostic commands, node eviction policies, kubelet troubleshooting

What it loads into context

Token counts are estimates. Scripts run separately; they are not counted as reference context.

No excerpt is shown for this license. Read the source on GitHub.

View the complete source on GitHub

infra-kubernetes-cost-optimizer

When your agent uses it

Kubernetes cost optimization — idle workload detection (zero-replica deployments, always-pending jobs), overprovisioning analysis (request vs actual CPU/memory), namespace-level cost attribution, node bin-packing via requests tuning, spot instance strategy, LimitRange defaults, right-sizing with VPA recommendations, Goldilocks tool, resource efficiency metrics, namespace resource quotas for chargeback

What it loads into context

Token counts are estimates. Scripts run separately; they are not counted as reference context.

No excerpt is shown for this license. Read the source on GitHub.

View the complete source on GitHub

infra-kubernetes-security-audit

When your agent uses it

Kubernetes security audit — RBAC review (ClusterRoleBindings/RoleBindings/ServiceAccount permissions), Pod Security Standards (privileged/hostPID/hostNetwork/runAsRoot), NetworkPolicy enforcement, Secret management (encryption at rest, external-secrets), image vulnerability scanning (Trivy/Grype), admission controllers (OPA Gatekeeper/Kyverno), audit logging, CIS Kubernetes Benchmark, supply chain security (SBOM/image signing)

What it loads into context

Token counts are estimates. Scripts run separately; they are not counted as reference context.

No excerpt is shown for this license. Read the source on GitHub.

View the complete source on GitHub

infra-kubernetes-storage-review

When your agent uses it

Kubernetes storage review — PVC lifecycle (provisioning/binding/reclaim), StorageClass selection (SSD/HDD/NVMe), dynamic vs static provisioning, StatefulSet volume management, volume performance tuning (ReadWriteMany vs ReadWriteOnce), CSI drivers (AWS EBS/GCP PD/Ceph/Longhorn), PVC resize, snapshot and backup, storage class access modes, orphaned PVs detection, shared storage patterns (NFS/CephFS)

What it loads into context

Token counts are estimates. Scripts run separately; they are not counted as reference context.

No excerpt is shown for this license. Read the source on GitHub.

View the complete source on GitHub

infra-multi-cloud-governance

When your agent uses it

Multi-cloud governance — cloud-agnostic data platform patterns, federated identity (OIDC/SAML between AWS/GCP/Azure), Terraform multi-cloud modules, cross-cloud data replication (S3↔GCS/Azure), unified cost management (FinOps Foundation framework), cloud-agnostic observability (OpenTelemetry), policy enforcement (OPA Gatekeeper across clouds), disaster recovery cross-cloud, vendor lock-in avoidance (open formats Iceberg/Parquet), centralized secrets management (HashiCorp Vault)

What it loads into context

Token counts are estimates. Scripts run separately; they are not counted as reference context.

No excerpt is shown for this license. Read the source on GitHub.

View the complete source on GitHub

infra-network-security-review

When your agent uses it

Network security review for data platforms — Kubernetes NetworkPolicy (default-deny + allow patterns), VPC/subnet design (private subnets for all data services), security group rules audit (0.0.0.0/0 detection), TLS everywhere (Kafka mTLS/Trino HTTPS/DB SSL), service mesh (Istio mTLS), DNS security (private hosted zones), egress filtering (no unrestricted outbound), VPC peering vs PrivateLink, network flow logs analysis, firewall rules review

What it loads into context

Token counts are estimates. Scripts run separately; they are not counted as reference context.

No excerpt is shown for this license. Read the source on GitHub.

View the complete source on GitHub

infra-observability-stack-review

When your agent uses it

Observability stack review — three pillars (metrics/logs/traces), Prometheus+Grafana+Loki+Tempo (LGTM stack), OpenTelemetry Collector as universal agent, cardinality management, log aggregation patterns (Fluent Bit→Loki), distributed tracing (Jaeger/Tempo), alerting pipeline (Alertmanager routing), SLO definition and error budget tracking, data platform observability (pipeline freshness/throughput/error rate), observability as code (Grafana provisioning)

What it loads into context

Token counts are estimates. Scripts run separately; they are not counted as reference context.

No excerpt is shown for this license. Read the source on GitHub.

View the complete source on GitHub

infra-opentelemetry-instrumentation

When your agent uses it

OpenTelemetry instrumentation for data platforms — Python auto-instrumentation (opentelemetry-bootstrap), manual span creation for ETL tasks, trace context propagation across Airflow→Spark→dbt, OTLP exporter configuration, W3C TraceContext headers in Kafka messages, resource attributes (service.name/environment/version), Baggage for partition metadata propagation, Collector pipeline (tail sampling), correlation between traces/logs/metrics, Grafana Tempo integration

What it loads into context

Token counts are estimates. Scripts run separately; they are not counted as reference context.

No excerpt is shown for this license. Read the source on GitHub.

View the complete source on GitHub

infra-prometheus-optimization

When your agent uses it

Prometheus optimization — recording rules (level:metric:operations naming), cardinality explosion diagnosis (tsdb status API), scrape interval tuning, remote write configuration (batch size/queue capacity), Thanos/Mimir for long-term retention, federation vs remote write, AlertManager routing trees (inhibition/silencing), absent() alerts for missing series, relabeling to drop expensive labels, TSDB compaction, ServiceMonitor vs PodMonitor patterns

What it loads into context

Token counts are estimates. Scripts run separately; they are not counted as reference context.

No excerpt is shown for this license. Read the source on GitHub.

View the complete source on GitHub

infra-rbac-audit

When your agent uses it

RBAC audit for data platforms — Kubernetes RBAC (ClusterRole/Role/Binding audit), AWS IAM permission boundary and policy review (AWS IAM Access Analyzer), GCP IAM audit (principle of least privilege/owner role detection), database RBAC (PostgreSQL/Trino/ClickHouse role hierarchies), Airflow RBAC (role-based menu/DAG access), dbt permissions (warehouse roles), service account proliferation detection, wildcard permission detection, privilege escalation paths

What it loads into context

Token counts are estimates. Scripts run separately; they are not counted as reference context.

No excerpt is shown for this license. Read the source on GitHub.

View the complete source on GitHub

infra-secrets-management-review

When your agent uses it

Secrets management review — HashiCorp Vault (KV v2/dynamic credentials/lease renewal/audit log), External Secrets Operator (Vault/AWS SSM/GCP Secret Manager → K8s secrets), secret rotation strategies (database dynamic credentials/TLS cert-manager), detecting secrets in code (gitleaks/truffleHog/Semgrep), Airflow connections from Vault backend, dbt profiles without hardcoded credentials, CI/CD secrets (GitHub OIDC/GitLab CI variables), no plaintext secrets in logs/configs

What it loads into context

Token counts are estimates. Scripts run separately; they are not counted as reference context.

No excerpt is shown for this license. Read the source on GitHub.

View the complete source on GitHub

infra-streaming-reliability-review

When your agent uses it

Streaming pipeline reliability — exactly-once semantics (idempotent producer/transactional API/read_committed/Kafka Streams EOS), at-least-once patterns with idempotent consumers, dead letter queue (DLQ) design with Kafka Connect SMT/custom error handler, poison message handling, reprocessing strategy, watermarks and late data handling, checkpoint/savepoint for Flink/Spark Streaming, consumer group rebalance storm prevention, end-to-end latency SLO monitoring, streaming reliability checklist

What it loads into context

Token counts are estimates. Scripts run separately; they are not counted as reference context.

No excerpt is shown for this license. Read the source on GitHub.

View the complete source on GitHub

infra-terraform-cost-estimator

When your agent uses it

Terraform cost estimation — Infracost breakdown and diff commands (monthly cost per resource), PR cost comments (before/after change delta), budget thresholds (block PRs over cost limit), usage files for variable quantities (S3 GB/requests), AWS pricing data sources, cost tagging strategy, OpenTofu/Terraform cost attribution, FinOps tagging policy enforcement, multi-environment cost comparison (dev vs prod)

What it loads into context

Token counts are estimates. Scripts run separately; they are not counted as reference context.

No excerpt is shown for this license. Read the source on GitHub.

View the complete source on GitHub

infra-terraform-review

When your agent uses it

Terraform code review — module structure (main/variables/outputs/modules layout), variable validation blocks, type constraints, sensitive variables, locals vs variables, resource naming conventions, provider version pinning, data sources vs resources, module composition patterns, state management (remote backend S3/GCS), workspace strategy, dependency management (depends_on vs implicit), terraform fmt/validate/tflint checks, DRY with Terragrunt

What it loads into context

Token counts are estimates. Scripts run separately; they are not counted as reference context.

No excerpt is shown for this license. Read the source on GitHub.

View the complete source on GitHub

infra-terraform-security-scan

When your agent uses it

Terraform security scanning — tfsec static analysis (AWS/GCP/Azure misconfigurations), Checkov IaC policy checks (750+ rules, CIS benchmarks), tflint security rules, KICS scanner, S3 encryption/public access/versioning checks, IAM least-privilege patterns, security group rule review (0.0.0.0/0), KMS key rotation, VPC flow logs, CloudTrail enabled, pre-commit hooks, SARIF output for GitHub Security tab, policy-as-code with OPA/Sentinel

What it loads into context

Token counts are estimates. Scripts run separately; they are not counted as reference context.

No excerpt is shown for this license. Read the source on GitHub.

View the complete source on GitHub

platform-engineering-agentic-control-plane

When your agent uses it

Agentic control plane for data platform — MCP (Model Context Protocol) server exposing platform tools to AI agents (FastMCP/Python SDK), natural language platform operations (trigger DAG/create topic/run dbt/query Trino via LLM), Claude-based platform assistant with tool use, multi-agent platform governance (audit agent/cost agent/reliability agent), MCP server deployment (Docker/Kubernetes), tool authorization and audit logging, agentic workflow patterns (plan-execute-verify), platform chat interface

What it loads into context

Token counts are estimates. Scripts run separately; they are not counted as reference context.

No excerpt is shown for this license. Read the source on GitHub.

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platform-engineering-data-platform-api

When your agent uses it

Data platform self-service API — FastAPI REST API for platform operations (Kafka topic CRUD/Airflow DAG trigger/dbt job run/Trino query execution), OAuth2+JWT authentication with team-based RBAC, async job tracking with status polling, rate limiting per team, OpenAPI spec generation, Terraform provider for API resources, versioned API (v1/v2), audit logging of all platform operations, SDK generation (Python/TypeScript), Kubernetes deployment with HPA

What it loads into context

Token counts are estimates. Scripts run separately; they are not counted as reference context.

No excerpt is shown for this license. Read the source on GitHub.

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platform-engineering-internal-developer-platform

When your agent uses it

Internal Developer Platform (IDP) for data engineering — Backstage Software Catalog (catalog-info.yaml for pipelines/datasets/services), Software Templates (scaffold new DAG/dbt project/Kafka topic), TechDocs integration, golden path enforcement, Port.io alternative, self-service data pipeline provisioning, platform scorecard (production readiness checks), team ownership model, API gateway for platform services, paved road vs escape hatch pattern

What it loads into context

Token counts are estimates. Scripts run separately; they are not counted as reference context.

No excerpt is shown for this license. Read the source on GitHub.

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airflow-starrocks-backfill

When your agent uses it

Airflow + StarRocks backfill patterns — historical partition reprocessing, date range loops with INSERT OVERWRITE, Broker Load replay for S3 partitions, safe backfill with max_active_runs=1, partial backfill resume from checkpoint, backfill idempotency via label strategy, clearing downstream tasks before rerun, parallel partition backfill with concurrency limits

What it loads into context

Token counts are estimates. Scripts run separately; they are not counted as reference context.

No excerpt is shown for this license. Read the source on GitHub.

View the complete source on GitHub

airflow-starrocks-cdc-orchestrator

When your agent uses it

Airflow CDC orchestration for StarRocks — watermark-based incremental sync, Routine Load health check DAG, Flink job submission via REST API, offset lag alerting, dead letter queue reprocessing, multi-table incremental sync with dependency graph, schema change detection and pipeline pause/resume

What it loads into context

Token counts are estimates. Scripts run separately; they are not counted as reference context.

No excerpt is shown for this license. Read the source on GitHub.

View the complete source on GitHub

airflow-starrocks-data-quality

When your agent uses it

Airflow + StarRocks data quality gates — post-load row count validation, freshness checks (MAX(updated_at) vs expected), null explosion detection, duplicate key audit on Primary Key tables, volume anomaly detection (z-score vs 7-day avg), SODA-style SQL quality checks embedded in DAG, quarantine pattern for bad partitions

What it loads into context

Token counts are estimates. Scripts run separately; they are not counted as reference context.

No excerpt is shown for this license. Read the source on GitHub.

View the complete source on GitHub

airflow-starrocks-etl-best-practices

When your agent uses it

Airflow + StarRocks ETL best practices — idempotent DAG design (label strategy/partition overwrite), retry with backoff, SLA callbacks, dynamic partition creation, duplicate prevention with MERGE/INSERT OVERWRITE, DAG-level concurrency controls, dependency ordering, catchup safety, data lineage tagging

What it loads into context

Token counts are estimates. Scripts run separately; they are not counted as reference context.

No excerpt is shown for this license. Read the source on GitHub.

View the complete source on GitHub

airflow-starrocks-pipeline

When your agent uses it

Airflow + StarRocks pipeline orchestration — MySqlHook for DDL/DML, Broker Load trigger + poll pattern, Stream Load via HTTP operator, Routine Load job lifecycle (pause/resume/stop), sensor for load completion, ANALYZE TABLE post-load, partition-aware DAG templating, Airflow variables for StarRocks connection config, XCom label passing

What it loads into context

Token counts are estimates. Scripts run separately; they are not counted as reference context.

No excerpt is shown for this license. Read the source on GitHub.

View the complete source on GitHub

dbt-starrocks-models

When your agent uses it

dbt + StarRocks models — dbt-starrocks adapter setup (profiles.yml), all materializations (table/view/incremental/ephemeral), incremental strategies (append/insert_overwrite/unique_key merge), StarRocks-specific model config (engine/keys/partition_by/distributed_by/properties), Duplicate/Aggregate/Primary Key table DDL from dbt, partition_by with date_trunc, on_schema_change behavior

What it loads into context

Token counts are estimates. Scripts run separately; they are not counted as reference context.

No excerpt is shown for this license. Read the source on GitHub.

View the complete source on GitHub

dbt-starrocks-performance

When your agent uses it

dbt + StarRocks performance tuning — model DAG optimization (fan-in/fan-out), incremental merge window sizing, partition-aware incremental filters, avoiding full table rebuilds, query plan hints in dbt SQL (LEADING/JOIN hints), materialized view as dbt model target, concurrent model execution with threads, pre/post hooks for ANALYZE TABLE, dbt run selectors to minimize rebuilt models

What it loads into context

Token counts are estimates. Scripts run separately; they are not counted as reference context.

No excerpt is shown for this license. Read the source on GitHub.

View the complete source on GitHub

dbt-starrocks-production-readiness

When your agent uses it

dbt + StarRocks production readiness — slim CI with state:modified+, manifest.json artifact storage and --defer for dev, dbt Cloud vs dbt Core deployment, RBAC for dbt users in StarRocks, secrets management for profiles.yml, dbt run/test exit codes in CI, breaking change detection, scheduled dbt runs via Airflow/dbt Cloud, dbt docs generation and hosting, model versioning

What it loads into context

Token counts are estimates. Scripts run separately; they are not counted as reference context.

No excerpt is shown for this license. Read the source on GitHub.

View the complete source on GitHub

dbt-starrocks-semantic-layer

When your agent uses it

dbt + StarRocks semantic layer — dbt Semantic Layer (MetricFlow) on StarRocks, metric definitions (simple/ratio/cumulative/derived), dimension definitions, saved queries, semantic model DDL, exposures for BI tool documentation, dbt-metricflow query CLI, linking metrics to StarRocks materialized views for performance, business KPI governance patterns

What it loads into context

Token counts are estimates. Scripts run separately; they are not counted as reference context.

No excerpt is shown for this license. Read the source on GitHub.

View the complete source on GitHub

dbt-starrocks-testing

When your agent uses it

dbt + StarRocks testing — generic tests (not_null/unique/accepted_values/relationships), singular tests (custom SQL assertions), source freshness tests (loaded_at_field), StarRocks-specific volume and freshness tests, dbt-expectations integration, test severity (warn vs error), store_failures for debugging failed tests, ANALYZE before test runs, partition-scoped test SQL

What it loads into context

Token counts are estimates. Scripts run separately; they are not counted as reference context.

No excerpt is shown for this license. Read the source on GitHub.

View the complete source on GitHub

starrocks-admin-backup-restore

When your agent uses it

StarRocks backup and restore — CREATE REPOSITORY (S3/HDFS/NFS), BACKUP DATABASE/TABLE, SHOW BACKUP/RESTORE status, RESTORE with partition granularity, cross-cluster restore, incremental backup strategy, snapshot lifecycle, disaster recovery RTO/RPO targets

What it loads into context

Token counts are estimates. Scripts run separately; they are not counted as reference context.

No excerpt is shown for this license. Read the source on GitHub.

View the complete source on GitHub

starrocks-admin-cluster-health

When your agent uses it

StarRocks cluster health monitoring — FE/BE/CN node status, tablet health, replica status, compaction backlog, storage imbalance, SHOW commands, system tables (information_schema/sys), alert thresholds, FE quorum checks, BE disk usage, dead replica detection, Prometheus metrics

What it loads into context

Token counts are estimates. Scripts run separately; they are not counted as reference context.

No excerpt is shown for this license. Read the source on GitHub.

View the complete source on GitHub

starrocks-admin-compaction

When your agent uses it

StarRocks compaction tuning — base compaction vs cumulative compaction, compaction score analysis, write amplification reduction, BE config parameters (compaction_threads/min_cumulative_compaction_num_singleton_deltas/max_compaction_candidate_num), SHOW PROC '/compactions', manual compaction trigger, Primary Key table compaction, rowset management

What it loads into context

Token counts are estimates. Scripts run separately; they are not counted as reference context.

No excerpt is shown for this license. Read the source on GitHub.

View the complete source on GitHub

starrocks-admin-query-monitor

When your agent uses it

StarRocks query monitoring and resource management — slow query log, SHOW PROCESSLIST, information_schema.query_history, resource groups (CREATE RESOURCE GROUP), classifiers, CPU/memory/concurrency limits, query queuing, KILL QUERY, workload isolation, Audit Loader plugin

What it loads into context

Token counts are estimates. Scripts run separately; they are not counted as reference context.

No excerpt is shown for this license. Read the source on GitHub.

View the complete source on GitHub

starrocks-admin-security

When your agent uses it

StarRocks security and RBAC — CREATE USER/ROLE, GRANT/REVOKE privileges (catalog/database/table/view/MV/function/resource group level), built-in roles (cluster_admin/db_admin/user_admin/public), LDAP/LDAP group auth, row-level security policies, column masking, SSL/TLS, audit log, privilege inheritance, security best practices

What it loads into context

Token counts are estimates. Scripts run separately; they are not counted as reference context.

No excerpt is shown for this license. Read the source on GitHub.

View the complete source on GitHub

starrocks-admin-storage-balancer

When your agent uses it

StarRocks storage balancing — tablet distribution across BEs, disk skew detection (SHOW BACKENDS disk usage), cluster_balance analysis (SHOW PROC '/cluster_balance'), balance_load_score_threshold tuning, tablet migration monitoring, BE decommission, adding new BE nodes, storage capacity forecasting, imbalance alerts

What it loads into context

Token counts are estimates. Scripts run separately; they are not counted as reference context.

No excerpt is shown for this license. Read the source on GitHub.

View the complete source on GitHub

starrocks-aggregation-optimizer

When your agent uses it

StarRocks aggregation optimization — one-phase vs two-phase aggregation, pre-aggregation pushdown to scan, Aggregate Key table automatic merge, GROUP BY on distribution key (local aggregation), COUNT DISTINCT optimization (multi-phase), HLL/BITMAP approximate aggregation, aggregation spill tuning, EXPLAIN aggregation nodes

What it loads into context

Token counts are estimates. Scripts run separately; they are not counted as reference context.

No excerpt is shown for this license. Read the source on GitHub.

View the complete source on GitHub