Data pipeline architecture — ingestion, orchestration, quality, lineage, SLAs. Use when the user asks to 'design data pipelines', 'architect ingestion', 'set up orchestration', 'plan data lake', 'design lakehouse', or mentions Airflow, Dagster, CDC, data lineage, or pipeline SLAs. [EXPLICIT]

Router de extensiones Claude Code para decidir y componer command/skill, scope, context fork y controles de invocacion. Deriva la autoria a claude-command-authoring o claude-skill-authoring y permisos a tool-permission-policy; no cubre Claude Platform.

Cloud-native design -- containers, service mesh, serverless, multi-cloud, FinOps. Use when the user asks to 'design cloud-native architecture', 'containerize the application', 'evaluate service mesh', 'plan serverless migration', 'implement multi-cloud strategy', 'optimize cloud costs', or mentions Kubernetes, Istio, Docker, Helm, Terraform, FinOps, or 12-factor. [EXPLICIT]

Cloud migration planning -- 7R assessment, workload classification, wave planning, cutover. Use when the user asks to 'plan cloud migration', 'assess workloads for migration', 'design landing zone', 'create migration waves', 'plan cutover strategy', or mentions 7R, rehost, replatform, refactor, lift-and-shift, or migration factory. [EXPLICIT]

This skill should be used when the user asks to 'author a Claude Code skill', 'write a SKILL.md', 'design skill frontmatter', 'choose allowed-tools or context fork for a skill', 'convert a command into a skill', or 'make a skill pass validation'. Teaching companion for SKILL.md authoring; defers heavy repair/hardening work to toolkit-hardener and packaging to plugin-builder.

Inventory and route Claude Code, Cowork, and Claude Platform capabilities, including Messages API runtime, server/client tools, Files/PDF, context/cache/compaction, skills, commands, agents, hooks, MCP, SDK, plugins, and output. Cowork claims still require a Cowork-session probe.

This skill should be used when the user asks to 'create a slash command', 'author a Claude Code command', 'decide command vs skill', 'choose project vs user scope', 'version custom commands for my team', or 'design command frontmatter'. Covers commands/*.md authoring and the command-vs-skill decision; unifies the custom-commands kata with the extension decision tree.

This skill should be used when the user asks to build, audit, or harden a Claude Platform Messages API client-side tool execution loop, handle tool_use and tool_result messages, correlate tool_use_id values, stream partial tool JSON, enforce strict:true schemas, handle stop_reason values, or design retry/error behavior for Anthropic Messages API tools. Do not use it for Claude Code headless CLI or Agent SDK automation, prompt-cache design, MCP server design, tool catalog descriptions, or individual tool implementations.

Use this skill to design, audit, or validate Claude Platform server-tool plans for server-tools, web search, web fetch, code execution, advisor, tool search, or the mechanical server-side portion of programmatic tool calling. It owns server_tool_use/result correlation, pause_turn continuation, versioned definitions, caller/container rules, domain controls, and source-supported privacy, retention, and cost controls. It does not own the application agent loop; route loop ordering and budgets to claude-api-tool-runtime and katas-deterministic-agent-loop.

This skill should be used when the user asks to design, audit, or harden Claude Platform Files API upload/reference/lifecycle flows or PDF document requests using file_id, URL, or base64 document sources. Use it for file metadata, deletion, conditional downloadability, PDF request limits, MIME-to-content-block contracts, and source/platform compatibility. Do not use it for text-editor operations, fetching web pages, generic object storage, document authoring, or arbitrary binary processing.

Use this skill when the user asks to design, audit, or harden Claude Platform Messages API context budgets, token counting, prompt caching, cache diagnostics, context editing, server-side compaction, context-window overflow policy, or mid-conversation system-message modes around a fixed effort setting. Do not use it for tool dispatch correlation, durable memory systems, generic context-writing advice, executor implementation, or Bash ownership.

This skill should be used when the user asks to implement, audit, or harden application-side handlers for Anthropic-defined Claude API client tools: memory, bash, text editor, or computer use; including sandboxing, path containment, command/action allowlists, session state, idempotency, tool_result construction, and execution evidence. Do not use it for Claude Code permissions, Anthropic server tools, MCP, Claude Code headless CLI, Agent SDK automation, or the generic Messages API tool loop.

CI/CD and release engineering: pipeline architecture, multi-environment strategy, deployment rollback (blue-green/canary), code-quality gates, dependency governance, git-hook automation. [EXPLICIT] Trigger: 'ci/cd', 'pipeline', 'rollback', 'canary', 'blue-green', 'release', 'quality gate', 'staging'.

This skill should be used when the user asks to design, configure, audit, or choose Claude Code channels, MCP channel servers, --channels startup flags, external push events, channel plugins, permission relay, or channel-vs-schedule/hook/headless decisions.

BI solution design — semantic layers, dashboard patterns, self-service analytics, KPI frameworks. Use when the user asks to 'design BI architecture', 'build a KPI framework', 'set up self-service analytics', 'design dashboard hierarchy', 'create a semantic layer', or mentions metric trees, drill-down patterns, or reporting strategy. [EXPLICIT]

Guides implementation of AI/GenAI architectures on AWS — Bedrock setup, SageMaker pipelines, OpenSearch vector stores, API Gateway configuration, security hardening, cost controls, and deployment automation. This skill should be used when the user asks to 'implement AI on AWS', 'set up Bedrock', 'deploy SageMaker pipeline', 'configure OpenSearch for RAG', 'implement AWS AI security', 'set up AWS AI monitoring', or mentions AWS AI deployment, Bedrock Knowledge Base setup, SageMaker endpoint deployment, AWS GenAI implementation, or AWS AI CI/CD pipeline. [EXPLICIT]

Designs AWS cloud architectures for AI and GenAI workloads applying the Well-Architected Framework GenAI Lens (6 pillars: GENOPS, GENSEC, GENREL, GENPERF, GENCOST, GENSUS), AWS service selection matrices, RAG/Agent/Fine-Tuning patterns, cost optimization strategies, and enterprise reference architectures. Activated when designing, evaluating, or migrating AI systems on AWS. [EXPLICIT]

Audits AWS AI/GenAI architectures against the Well-Architected GenAI Lens — operational excellence, security, reliability, performance, cost optimization, and sustainability. This skill should be used when the user asks to 'audit AWS AI architecture', 'review Bedrock configuration', 'assess SageMaker security', 'optimize AWS AI costs', 'evaluate AWS GenAI compliance', 'review AWS Well-Architected for AI', or mentions AWS AI audit, Bedrock audit, SageMaker review, AWS GenAI security assessment, or AWS AI cost optimization review. [EXPLICIT]

Cross-cutting reliability patterns for PubNub apps. Covers reconnect with exponential backoff + jitter, idempotent publish with client-generated message IDs, dedup-on-merge for live + history streams, queue-and-retry for offline writes, and schema versioning of message envelopes. Use during design reviews, when planning offline support, or during incident response when network or delivery reliability is the concern.

Logging, testing, cost hygiene, incident triage, and usage metrics for PubNub apps. Covers the correlation fields every send/receive must log, the test pyramid for real-time apps, payload + fan-out cost hygiene, the incident triage runbook, and PubNub usage metrics for billing reconciliation. Use during code reviews, when planning monitoring, when triaging incidents, or when investigating PubNub cost overruns.