Claude Skills

Reranking patterns for improving search precision. Use when implementing cross-encoder reranking, LLM-based relevance scoring, or improving retrieval quality in RAG pipelines.

Agentic workflow patterns for autonomous LLM reasoning. Use when building ReAct agents, implementing reasoning loops, or creating LLMs that plan and execute multi-step tasks.

LangGraph Functional API with @entrypoint and @task decorators. Use when building workflows with the modern LangGraph pattern, enabling parallel execution, persistence, and human-in-the-loop.

LangGraph human-in-the-loop patterns. Use when implementing approval workflows, manual review gates, user feedback integration, or interactive agent supervision.

LangGraph parallel execution patterns. Use when implementing fan-out/fan-in workflows, map-reduce over tasks, or running independent agents concurrently.

LangGraph conditional routing patterns. Use when implementing dynamic routing based on state, creating branching workflows, or building retry loops with conditional edges.

LangGraph state management patterns. Use when designing workflow state schemas, using TypedDict vs Pydantic, implementing accumulating state with Annotated operators, or managing shared state across nodes.

LangGraph supervisor-worker pattern. Use when building central coordinator agents that route to specialized workers, implementing round-robin or priority-based agent dispatch.

Multi-agent coordination and synthesis patterns. Use when orchestrating multiple specialized agents, implementing fan-out/fan-in workflows, or synthesizing outputs from parallel agents.

Temporal.io workflow orchestration for durable, fault-tolerant distributed applications. Use when implementing long-running workflows, saga patterns, microservice orchestration, or systems requiring exactly-once execution guarantees.

[QUALITY] Add documents to golden dataset with validation. Use when curating test data or saving examples.

LLM fine-tuning with LoRA, QLoRA, DPO alignment, and synthetic data generation. Efficient training, preference learning, data creation. Use when customizing models for specific domains.

LLM function calling and tool use patterns. Use when enabling LLMs to call external tools, defining tool schemas, implementing tool execution loops, or getting structured output from LLMs.

Transactional outbox pattern for reliable event publishing. Use when implementing atomic writes with event delivery, ensuring exactly-once semantics, or building event-driven microservices.

React Hook Form v7 with Zod validation, React 19 useActionState, Server Actions, field arrays, and async validation. Use when building complex forms, validation flows, or server action forms.

Data visualization with Recharts 3.x including responsive charts, custom tooltips, animations, and accessibility for React applications. Use when building charts or dashboards with Recharts.

Test data management with fixtures and factories. Use when creating test data strategies, implementing data factories, managing fixtures, or seeding test databases.

Automated accessibility testing with axe-core, Playwright, and jest-axe for WCAG compliance. Use when adding or validating a11y tests, running WCAG checks, or auditing UI accessibility.

Curate and add documents to the golden dataset with multi-agent validation. Use when adding test data, creating golden datasets, saving examples.

shadcn/ui component patterns including CVA variants, OKLCH theming, cn() utility, and composition. Use when adding shadcn components, building variant systems, or customizing themes.

Use when building secure AI pipelines or hardening LLM integrations. Defense-in-depth implements 8 validation layers from edge to storage with no single point of failure.

User interviews, usability testing, surveys, card sorting, and qualitative research methods. Use when gathering user insights, validating designs, or understanding user behavior.

Automated security scanning for dependencies and code. Use when running npm audit, pip-audit, Semgrep, secret detection, or integrating security checks into CI/CD.

Use when validating golden dataset quality. Runs schema checks, duplicate detection, and coverage analysis to ensure dataset integrity for AI evaluation.