Optimizes CI pipelines for monorepos by detecting affected packages/apps and running only necessary builds and tests. Includes Turborepo/Nx strategies, caching, and parallel execution. Use for "monorepo CI", "affected detection", "incremental builds", or "workspace optimization".
Optimizes Nginx configurations for performance, security, caching, and load balancing with modern best practices. Use when users request "Nginx setup", "reverse proxy", "load balancer", "web server config", or "Nginx optimization".
Creates ephemeral preview deployments for each pull request with automatic deployment, unique URLs, and cleanup on PR close. Use for "preview deployments", "PR environments", "ephemeral environments", or "review apps".
Enforces minimum quality thresholds in CI including code coverage, linting, type checking, and security scanning. Provides required checks, PR rules, and automated enforcement. Use for "quality gates", "CI checks", "code quality", or "PR requirements".
Automates releases and package publishing with changesets or semantic-release. Handles versioning, changelog generation, git tags, and release notes. Use for "release automation", "semantic versioning", "package publishing", or "changelog generation".
Creates safe rollback procedures for deployments with automated workflows, rollback runbooks, version management, and incident response. Use for "rollback automation", "deployment recovery", "incident response", or "production rollback".
Validates environment variables in CI, prevents secret leaks, enforces masking, and provides fail-fast validation with clear documentation. Use for "secrets management", "env var validation", "credential security", or "secret masking".
Creates reusable Terraform modules with proper structure, variables, outputs, and state management for infrastructure as code. Use when users request "Terraform setup", "infrastructure as code", "IaC module", "cloud provisioning", or "Terraform module".
Creates comprehensive disaster recovery procedures with automated backup scripts, restore procedures, validation checks, and role assignments. Use for "database backup", "disaster recovery", "data restore", or "DR planning".
Detects data integrity issues including orphaned records, broken foreign key relationships, constraint violations, and provides automated fix migrations. Use for "data integrity", "orphaned records", "broken relationships", or "data quality".
Plans and implements data retention policies with archival strategies, compliance requirements, automated cleanup jobs, and cold storage migration. Use for "data retention", "data archival", "GDPR compliance", or "storage optimization".
Generates deterministic seed data for development and testing with factory functions, realistic fixtures, and database reset scripts. Use for "data seeding", "test fixtures", "database seeding", or "mock data generation".
Orchestrates multi-agent AI systems with task delegation, agent communication, shared memory, and workflow coordination. Use when users request "multi-agent system", "agent orchestration", "AI agents", "agent coordination", or "autonomous agents".
Reduces LLM costs and improves response times through caching, model selection, batching, and prompt optimization. Provides cost breakdowns, latency hotspots, and configuration recommendations. Use for "cost reduction", "performance optimization", "latency improvement", or "efficiency".
Converts documents into clean, chunked datasets suitable for embeddings and vector search. Produces chunked JSONL files with metadata, deduplication logic, and quality checks. Use when preparing "training data", "vector datasets", "document processing", or "embedding data".
Builds document embedding pipelines with text chunking, embedding generation, indexing, and retrieval optimization. Use when users request "embedding pipeline", "document indexing", "text chunking", "RAG preprocessing", or "semantic indexing".
Builds repeatable evaluation systems with golden datasets, scoring rubrics, pass/fail thresholds, and regression reports. Use for "LLM evaluation", "testing AI systems", "quality assurance", or "model benchmarking".
Builds LLM applications with LangChain including chains, agents, memory, tools, and RAG pipelines. Use when users request "LangChain setup", "LLM chain", "AI workflow", "conversational AI", or "RAG pipeline".
Diagnoses LLM output failures including hallucinations, constraint violations, format errors, and reasoning issues. Provides root cause classification, prompt fixes, tool improvements, and new test cases. Use for "debugging AI", "fixing prompts", "quality issues", or "output errors".
Builds Model Context Protocol (MCP) servers for Claude with tools, resources, and prompts. Use when users request "create MCP server", "build Claude tool", "MCP integration", or "custom Claude tools".
Compares old vs new prompts across test cases with diff summaries, stability metrics, breakage analysis, and fix suggestions. Use for "prompt testing", "A/B testing prompts", "prompt versioning", or "quality regression".
Creates reusable prompt templates with strict output contracts, style rules, few-shot examples, and do/don't guidelines. Provides system/user prompt files, variable placeholders, output formatting instructions, and quality criteria. Use when building "prompt templates", "LLM prompts", "AI system prompts", or "prompt…