dlawskillz

Orchestrate multi-stage pipelines for ssmd workflows. Pre-defined pipelines chain skills and agents in sequence — deploy, feature, hotfix, and dq-investigate. Use when user says "ssmdorch", "orchestrate", "pipeline", or named pipelines like "ssmdorch deploy", "ssmdorch feature", "ssmdorch hotfix", "ssmdorch dq".

Multi-agent orchestration for ssmd market data system tasks. Extends waldstorm with domain-specific experts for secmaster, data feeds, trading APIs, and data quality. Use when working on connectors, exchanges, NATS pipelines, market metadata, or user says "ssmdstorm", "market data task", "exchange work".

Multi-agent orchestration that analyzes tasks through specialized expert panels (security, performance, architecture, etc.), synthesizes prioritized actions, then plans and executes. Use when facing complex tasks requiring multiple perspectives, architectural decisions, new features needing security/performance/quality review, or user says "waldstorm", "expert review", "analyze this task".

This skill MUST be used before writing any implementation code — feature work, bug fixes, pipeline stages, data processing, API handlers, K8s manifests, or integration code. Enforces fail-loud patterns, input/output validation, connection verification, and pre-commit gates. Triggered automatically on any code writing task. Also use when user says "defensive", "fail-fast", "validate", "check failures", "harden".

Catalog of all ssmd health metrics — sources, query methods, labels, healthy/unhealthy thresholds. Covers data pipeline Prometheus metrics, HTTP endpoints, infrastructure components, DQ scores, and composite health scoring. Use when checking environment health, interpreting metrics, setting alert thresholds, or building health dashboards.

Procedures for running ssmd health checks and interpreting results. Covers quick triage, data pipeline health, infrastructure checks (NATS, Postgres, Redis), connector/archiver deep dives via port-forward, and Cloud Monitoring queries. Use when checking environment health, investigating degradation, or verifying health after deployments.

Catalog of ssmd DQ checks — what each measures, pass/fail criteria, common failure modes and fixes, fanout rules, and accountability SLOs. Use when investigating DQ failures, understanding check behavior, or adding new checks.

How to run ssmd DQ checks locally and in-cluster, interpret scores, trigger email reports, and verify results. Use when running data quality checks, re-sending DQ emails, or verifying pipeline health after deployments or backfills.

Deploy ssmd components to GKE prod. Handles git tagging, GitHub Actions image builds, manifest updates, and Flux reconciliation. Use when deploying connector, archiver, parquet-gen, DQ, data-ts, CLI, operator, worker, or other ssmd images after code changes.

Analyze code for simplification opportunities. Use when user says "simplify", "reduce complexity", "clean up code", "remove duplication", "too complicated", or wants to reduce technical debt.