engineering/skills/backend/SKILL.md
Use for backend engineering work such as APIs, services, data models, persistence, queues, caching, auth, background jobs, and server-side debugging or refactors.
npx skillsauth add alvarovillalbaa/agent-suite backendInstall this skill globally with one command. Works with Claude Code, Cursor, and Windsurf.
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This skill owns server-side implementation depth. Use it together with ../agentic-development/SKILL.md: agentic-development handles repo orientation, planning, and execution model; this skill handles APIs, services, schemas, persistence, and operational backend detail.
../agentic-development/SKILL.md for repo orientation, proof planning, and execution-mode selection.../frontend/SKILL.md.Business logic lives in services, not in controllers, views, or models. Follow this routing:
| Layer | Owns | |-------|------| | Controllers / Views | Request parsing, auth check, delegating to a service, serializing the response. No business logic. | | Serializers / Validators | Input shape validation and output shape mapping. Route the result to a service for processing — serializers do not compute. | | Services | The business logic: computations, orchestration, side effects, third-party calls, conditional branching. Keep services small and single-purpose. | | Models | Persistence shape, relationships, and simple data invariants. Keep models clean — no business logic, no external service calls. |
A smell that logic is in the wrong layer: a controller or serializer that branches on business state, or a model that calls an external API.
Read backend-development.md for service-layer, data-model, API, async, and architecture heuristics.
Read api-design-patterns.md when designing or refactoring REST or GraphQL APIs.
Read rest-design-rules.md for detailed REST semantics, URL design, response conventions, caching headers, and rate-limit headers.
Read api-antipatterns.md when auditing or reviewing an existing API surface.
Read database-design-reference.md when designing a schema from scratch or evaluating normalization/denormalization.
Read normalization-guide.md for deep normalization and denormalization trade-off work.
Read database-optimization.md when queries are slow or database performance needs improvement.
Read index-strategy-patterns.md for index selection, query-pattern matching, and over-indexing avoidance.
Read database-selection-decision-tree.md when choosing a database technology or migration path.
Read backend-security-node.md when touching authentication, authorization, input handling, or HTTP response security in Node/Express systems.
scripts/api_linter.py for REST/OpenAPI linting.scripts/api_scorecard.py for API quality grading.scripts/breaking_change_detector.py for API diffing and breaking-change classification.scripts/api_scaffolder.py for route/type/middleware scaffolding from OpenAPI or schemas.scripts/api_load_tester.py for endpoint latency and throughput measurement.scripts/database_migration_tool.py for schema analysis and migration help.scripts/schema_analyzer.py for normalization, constraints, and ERD analysis.scripts/index_optimizer.py for index recommendations.scripts/migration_generator.py for schema diffs and zero-downtime migration planning.../agentic-development/SKILL.md.../frontend/SKILL.md when the task also changes browser-facing behavior or UI integration.../frontend/SKILL.md for routes, components, interaction behavior, design systems, accessibility, and browser performance.../agentic-development/SKILL.md when the work needs repo-wide planning, architecture explanation, execution-mode selection, or coordinated frontend/backend delivery.quality-assurance for passive security audits, threat modeling, test strategy, and CI triage.development
Use for frontend engineering work such as components, routes, state management, accessibility, performance, design-system integration, and browser-facing debugging or refactors.
development
This skill should be used when the user asks to write, update, review, scaffold, move, remove, or continuously improve documentation for code, folders, services, repos, workflows, architectural decisions, or operational processes. Trigger for inline docs, `README.md`, `ARCHITECTURE.md`, `TESTS.md`, `SETUP.md`, `RUNBOOK.md`, `CHANGELOG.md`, `SECURITY.md`, `OVERVIEW.md`, `FAQ.md`, `DECISIONS.md`, `DEPENDENCIES.md`, `AGENTS.md`, `PLAN.md`, `SPEC.md`, `SOUL.md`, `PRINCIPLES.md`, `DESIGN.md`, `logs/`, `lessons/`, `items/`, `fixes/`, `audits/`, `raw/`, `plans/`, `specs/`, `sources/`, `lib/`, `references/`, `cookbook/`, `knowledge/`, `runbooks/`, `research/`, `official-documentation/`, `context/`, MDX docs, JSDoc/TSDoc, docstrings, ADRs, post-mortems, migration guides, documentation cleanups, and documentation-impact reviews.
tools
Cross-cloud CLI-first cloud operations for AWS, Azure, and GCP. Use when the assistant needs to identify which cloud provider or multi-cloud estate a repo uses, deploy new resources or services, wire automatic deployments, inventory and optimize infrastructure, or diagnose and repair cloud failures entirely from the terminal, with explicit approval gates for high-cost, destructive, identity-sensitive, or hard-to-reverse changes. Covers AWS Amplify full-stack projects, serverless workloads (Lambda, API Gateway, Step Functions, SAM, CDK), and the full AWS database portfolio (RDS, Aurora, Aurora DSQL, DynamoDB, ElastiCache), as well as deep Azure references for diagnostics, storage, compute, compliance, identity, Foundry, and cross-cloud migrations.
tools
Use for AI and agent engineering work: system prompt design, tool call architecture, context engineering, memory and learning systems, multi-agent coordination, evals and regression gates, fine-tuning pipelines, RAG, vector stores (TurboPuffer/Pinecone/Azure), agent governance and safety, run steering, skill packages, prompt engineering patterns, constrained generation, ML pipelines, data engineering, and production AI infrastructure.