saas-ai-skills

Review or design an API contract: REST, GraphQL, gRPC, events, webhooks, streaming, or OpenAPI/AsyncAPI. Use when the primary deliverable is an interface contract, compatibility assessment, or API-specific security/resilience guidance. Do not use for whole-system architecture planning, generic code review, database modeling, or implementation debugging.

Plan the future architecture of a new or materially changing system before implementation. Use for greenfield products, planned platform changes, and technical blueprints spanning components, data, APIs, deployment, and delivery trade-offs. Do not use to audit an existing repository, review a PR, or diagnose an incident.

Audit the current architecture of an existing repository or deployed system: boundaries, dependency direction, module responsibilities, coupling, testability, and incremental modernization. Use for Clean/Hexagonal/DDD/layering health checks. Do not use for greenfield architecture design or a narrow code/PR review.

Build an evidence-based mental model of an unfamiliar existing repository: structure, ownership, flows, entry points, and change locations. Use for onboarding, tracing, and discovery before another task. Do not use to prescribe a design, issue findings, implement changes, or diagnose a specific failure.

Review a specific implementation, change set, PR, function, or service for broad correctness and production-readiness findings. Use when code-quality is the primary concern. Do not use when security, performance, architecture, dependencies, or tests are the exclusive requested discipline.

Design, review, or evolve a database schema and its data-integrity, tenancy, migration, indexing, and operational model. Use when the primary deliverable is a datastore or schema decision. Do not use for general system planning, query debugging, or generic dependency/security review.

Investigate and safely fix an active, observable software failure, error, regression, or unexpected behavior using reproduction and evidence. Use for the proximate technical cause and remediation. Do not use for a systemic incident postmortem or general performance tuning without a failure.

Analyze package, lockfile, import/module, build, runtime-service, and third-party dependency relationships, risks, upgrades, and supply-chain health. Use when dependencies themselves are the primary object. Do not use for a broad security audit or whole-architecture review.

Select or assess the smallest justified software design pattern for a concrete design problem. Use for pattern choice, pattern misuse, and trade-off guidance. Do not use to refactor code, audit architecture, or perform broad code review.

Measure, diagnose, and improve a performance or capacity objective?latency, throughput, CPU, memory, scalability, or cost?without regressing correctness. Use when performance is the primary requested outcome. Do not use for generic code cleanup or an unmeasured incident postmortem.

Plan and execute behavior-preserving structural changes to existing code: simplify, decompose, modernize, and reduce technical debt with tests and safe steps. Use when implementation change is requested. Do not use for a review-only finding report, new features, or bug fixes that change behavior.

Produce a systemic, evidence-based incident RCA/postmortem after a failure: timeline, causal chain, contributing conditions, corrective actions, and prevention. Use when recurrence prevention and organizational learning are primary. Do not use as a generic live debugger.

Conduct a security-led audit of code, systems, APIs, infrastructure, dependencies, and AI workflows with threat modeling and exploitability-backed remediation. Use when security risk is the primary concern. Do not use for a generic code review, database design, or non-security debugging.

Review existing code or modules specifically through practical SOLID design risks: responsibility, extensibility, substitutability, interface capability, and dependency inversion. Use for SOLID-focused diagnosis. Do not use for broad architecture review or implementation refactoring.

Generate or plan deterministic automated tests for existing behavior, regressions, APIs, UI, integrations, and edge cases. Use when tests are the primary deliverable. Do not use to debug the defect, review the implementation, or redesign the system.