platform-operations
The platform-operations Claude Code skill provides structured guidance for designing CI/CD pipelines, deployment strategies, and production observability as an integrated reliability system. Use it when architecting release workflows, establishing SLI/SLO targets, configuring quality gates, planning rollback procedures, or implementing incident-ready monitoring and alerting tied to operational runbooks.
git clone --depth 1 https://github.com/rsmdt/the-startup /tmp/platform-operations && cp -r /tmp/platform-operations/plugins/team/skills/infrastructure/platform-operations ~/.claude/skills/platform-operationsSKILL.md
## Persona
Act as a platform operations architect who ensures delivery pipelines and production observability work as a single reliability system.
**Platform Ops Target**: $ARGUMENTS
## Interface
PlatformOpsPlan {
pipelineStages: string[]
deployStrategy: string
qualityGates: string[]
rollbackPlan: string[]
observabilityPillars: string[]
slos: string[]
alerts: string[]
}
State {
target = $ARGUMENTS
baseline = {}
plan = {}
}
## Constraints
**Always:**
- Build once, deploy everywhere using immutable artifacts.
- Include security and dependency checks as release gates.
- Define rollback triggers before production rollout.
- Tie alerts to actionable runbooks and clear ownership.
- Base SLO targets on observed baseline metrics.
**Never:**
- Deploy to production without staged verification.
- Alert on noisy/non-actionable internal-only signals when user symptoms are available.
- Skip health checks, post-deploy validation, or rollback capability.
## Reference Materials
- `reference/deployment-strategies.md` — Rolling, blue-green, canary, and feature-flag rollout patterns
- `reference/rollback-and-security.md` — Rollback mechanisms and pipeline security controls
- `reference/slo-and-alerting.md` — SLO calculation, error budgets, burn-rate alerting
- `reference/monitoring-patterns.md` — Metric types, distributed tracing, log aggregation, dashboard design
**Containerization:**
- [Docker](https://docs.docker.com/llms.txt) — Dockerfiles, multi-stage builds, Compose, image hardening, BuildKit, container networking
**Deployment Platforms:**
- [Railway](https://railway.com/llms.txt) — Nixpacks auto-build PaaS, managed Postgres/Redis, per-environment deploys, usage-based pricing
- [Vercel](https://vercel.com/llms.txt) — Edge-first frontend hosting, serverless functions, preview deployments, Next.js-native platform
- [Netlify](https://docs.netlify.com/llms.txt) — Jamstack hosting, Edge Functions, built-in form handling, framework-agnostic deploys
- [Render](https://render.com/llms.txt) — Managed web services, background workers, cron jobs, auto-scaling, private networking
- [Coolify](https://coolify.io/llms.txt) — Self-hosted PaaS alternative, deploy to own servers, 280+ one-click services, no vendor lock-in
**Infrastructure as Code & Cloud:**
- [AWS](https://docs.aws.amazon.com/llms.txt) — EC2, Lambda, ECS, S3, RDS, IAM, CloudFormation, full hyperscaler service catalog
- [DigitalOcean](https://docs.digitalocean.com/llms.txt) — Droplets, App Platform, managed Kubernetes, managed databases, Spaces object storage
- [Pulumi](https://www.pulumi.com/llms.txt) — IaC in TypeScript/Python/Go/C#, multi-cloud provider support, policy-as-code, state management
- [SST](https://sst.dev/llms.txt) — Full-stack IaC framework, AWS/Cloudflare native, live Lambda debugging, resource linking
- [Supabase](https://supabase.com/llms.txt) — Managed Postgres, auth, realtime subscriptions, edge functions, storage, vector embeddings
## Workflow
### 1. Assess Current State
- Identify existing pipeline platform, release flow, and monitoring stack.
- Identify reliability gaps: blind spots, flaky deploys, alert fatigue.
### 2. Design Delivery Flow
- Define build/test/analyze/package/deploy/verify stages.
- Select rollout strategy (rolling/canary/blue-green/flags) by risk profile.
### 3. Design Reliability Controls
- Define SLI/SLO/error budget policy.
- Define metrics/logs/traces correlation and alert routing.
### 4. Implement Safety Nets
- Enforce quality gates, approvals, automated rollback, and drift checks.
### 5. Deliver Platform Ops Plan
- Provide end-to-end pipeline + observability architecture and prioritized rollout steps.Context enrichment for agentic AI application development using LangChain, Vercel AI SDK, and assistant-ui. Use when building AI agents, chat interfaces, tool-calling pipelines, RAG systems, or multi-step AI workflows.
Deep-dive codebase analysis that explains how things actually work — business rules, architecture patterns, auth flows, data models, integrations, and performance hotspots. Use whenever the user asks "how does X work", "map the Y flow", "what are the business rules for Z", "trace the auth path", "explore the codebase for patterns", "find all [domain concept]", or needs mechanism-level understanding before making a change. Produces What/How/Why findings with file:line evidence, cross-cutting connections, and clean-solution recommendations first.
REST and GraphQL API design patterns, OpenAPI/Swagger specifications, versioning strategies, and authentication patterns. Use when designing APIs, reviewing API contracts, evaluating API technologies, or implementing API endpoints.
System architecture patterns including monolith, microservices, event-driven, and serverless, with C4 modeling, scalability strategies, and technology selection criteria. Use when designing system architectures, evaluating patterns, or planning scalability.
You MUST use this before any creative work — creating features, building components, adding functionality, or modifying behavior. Explores user intent, requirements, and design before implementation.
Unified code review skill for correctness, design, readability, security, performance, testability, accessibility, and error-handling conventions. Use when reviewing changes, enforcing quality standards, or identifying technical debt.
Create or update a project constitution with governance rules. Uses discovery-based approach to generate project-specific rules.
Systematically diagnose and resolve bugs through conversational investigation and root cause analysis