Claude Skills by yonatangross

Text embeddings for semantic search and similarity. Use when converting text to vectors, choosing embedding models, implementing chunking strategies, or building document similarity features.

RFC 9457 Problem Details for standardized HTTP API error responses. Use when implementing problem details format, structured API errors, error registries, or migrating from RFC 7807.

Error pattern analysis and troubleshooting for Claude Code sessions. Use when handling errors, fixing failures, troubleshooting issues.

Event sourcing patterns for storing state as a sequence of events. Use when implementing event-driven architectures, CQRS, audit trails, or building systems requiring full history reconstruction.

Collects and verifies evidence before marking tasks complete. Use when completing tasks, code reviews, or deployments to prove work with test results, build outputs, coverage metrics, and exit codes.

Deep codebase exploration with parallel agents. Use when exploring a repo or discovering architecture.

FastAPI advanced patterns including lifespan, dependencies, middleware, and Pydantic settings. Use when configuring FastAPI lifespan events, creating dependency injection, building Starlette middleware, or managing async Python services with uvicorn.

Manages OrchestKit feedback system. Use when providing feedback or viewing usage analytics.

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.

Fixes GitHub issues with parallel analysis. Use when fixing bugs or resolving issues.

Keyboard focus management patterns for accessibility. Covers focus traps, roving tabindex, focus restore, skip links, and FocusScope components for WCAG-compliant interactive widgets. Use when implementing focus traps or keyboard navigation.

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.

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.

Recovery from git mistakes. Use when you need to undo commits, recover branches, or fix history.

Complete git workflow patterns including GitHub Flow branching, atomic commits with interactive staging, and recovery operations using reflog. Essential patterns for clean history. Use when defining branching strategy or recovering git history.

GitHub CLI operations for issues, PRs, milestones, and Projects v2. Covers gh commands, REST API patterns, and automation scripts. Use when managing GitHub issues, PRs, milestones, or Projects with gh.

Use when creating or improving golden datasets for AI evaluation. Defines quality criteria, curation workflows, and multi-agent analysis patterns for test data.

Use when backing up, restoring, or validating golden datasets. Prevents data loss and ensures test data integrity for AI/ML evaluation systems.

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

gRPC with Python using grpcio and protobuf for high-performance microservice communication. Use when implementing service-to-service APIs, streaming data, or building polyglot microservices requiring strong typing.

OrchestKit skill directory. Use when you want to see available skills or need help.

Best practices for HeyGen - AI avatar video creation API. Use when creating AI avatar videos, generating talking head videos, or integrating HeyGen with Remotion.

High-performance LLM inference with vLLM, quantization (AWQ, GPTQ, FP8), speculative decoding, and edge deployment. Use when optimizing inference latency, throughput, or memory.