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RAG Architect - POWERFUL

Expert in building Retrieval-Augmented Generation systems. Masters embedding models, vector databases, chunking strategies, and retrieval optimization for LLM applications. Use when: building RAG, vector search, embeddings, semantic search, document retrieval.

Build Retrieval-Augmented Generation (RAG) systems for LLM applications with vector databases and semantic search. Use when implementing knowledge-grounded AI, building document Qu0026A systems, or integrating LLMs with external knowledge bases.

RAG-specific best practices for LlamaIndex, ChromaDB, and Celery workers. Covers ingestion, retrieval, embeddings, and performance.

Local-first RAG cache: distill docs into structured Markdown, then index/query with Chroma (vector) + ripgrep (keyword).

Search for Israel Rail train schedules using the railil CLI. Find routes between stations with fuzzy search, filter by date/time, and output in various formats (JSON, Markdown, Table).

Help with Rails testing including unit tests, integration tests, fixtures, and debugging test failures. Use when working on tests or debugging test issues.

Railway CLI operations for authentication, context management, deployment, monitoring, and troubleshooting. Use when working with Railway infrastructure, deploying services, or managing environments.

Deploy, manage services, view logs, and configure Railway infrastructure. Use when deploying to Railway, managing environment variables, viewing deployment logs, scaling services, or managing volumes.

Add official Railway database services (Postgres, Redis, MySQL, MongoDB). Use when user wants to add a database, says \

Deploy code to Railway using \

Manage Railway deployments - view logs, redeploy, restart, or remove deployments. Use for deployment lifecycle (remove, stop, redeploy, restart), deployment visibility (list, status, history), and troubleshooting (logs, errors, failures, crashes). NOT for deleting services - use

Fetch up-to-date Railway documentation to answer questions accurately. Use when user asks about Railway features, how Railway works, or shares a docs.railway.com URL.

Add, view, or remove domains for Railway services. Use when user wants to add a domain, generate a railway domain, check current domains, get the URL for a service, or remove a domain.

Query, stage, and apply configuration changes for Railway environments. Use for ANY variable or env var operations, service configuration (source, build settings, deploy settings), lifecycle (delete service), and applying changes. Prefer over railway-status skill for any

Query resource usage metrics for Railway services. Use when user asks about resource usage, CPU, memory, network, disk, or service performance like \

Create Railway projects, services, and databases with proper configuration. Use when user says \

List, switch, and configure Railway projects. Use when user wants to list all projects, switch projects, rename a project, enable/disable PR deploys, make a project public/private, or modify project settings.

Check service status, rename services, change service icons, link services, or create services with Docker images. For creating services with local code, prefer railway-new skill. For GitHub repo sources, use railway-new skill to create empty service then railway-environment

Check current Railway project status for this directory. Use when user asks \

Search and deploy services from Railway's template marketplace. Use when user wants to add a service from a template, find templates for a specific use case, or deploy tools like Ghost, Strapi, n8n, Minio, Uptime Kuma, etc. For databases (Postgres, Redis, MySQL, MongoDB), prefer

Self-referential loop until task completion with architect verification

Use this skill when the user asks to \

Initialize a PRD (Product Requirements Document) for structured ralph-loop execution

AI 자율 구현 방법론. 구현/개발/코딩 요청 시 자동 적용. 메인은 마더 서브에이전트를 spawn하고, 마더가 워커들을 관리. specs/ → IMPLEMENTATION_PLAN.md → 1태스크씩 구현 → 2단계 리뷰 → 테스트 → 반복.

Interactive planning assistant that helps create focused, well-structured ralph-loop commands through collaborative conversation

Convert PRDs to beads for ralph-tui execution. Creates an epic with child beads for each user story. Use when you have a PRD and want to use ralph-tui with beads as the task source. Triggers on: create beads, convert prd to beads, beads for ralph, ralph beads.

Convert PRDs to prd.json format for ralph-tui execution. Creates JSON task files with user stories, acceptance criteria, and dependencies. Triggers on: create prd.json, convert to json, ralph json, create json tasks.

Generate a Product Requirements Document (PRD) for ralph-tui task orchestration. Creates PRDs with user stories that can be converted to beads issues or prd.json for automated execution. Triggers on: create a prd, write prd for, plan this feature, requirements for, spec out.

Implements the Ralph Wiggum autonomous iteration technique with deliberate context management. Use when building greenfield projects, iterating on well-defined tasks, or when continuous autonomous development is needed. Manages context like memory - tracks allocations, prevents

Iterative planning with Planner, Architect, and Critic until consensus

Tracks and analyzes keyword ranking positions over time for both traditional search results and AI-generated responses. Monitors ranking changes, identifies trends, and alerts on significant movements.

Gamify your gym sessions with XP, levels, achievements, and workout streaks

Manage rate limit middleware operations. Auto-activating skill for Backend Development.\nTriggers on: rate limit middleware, rate limit middleware\nPart of the Backend Development skill category. Use when working with rate limit middleware functionality. Trigger with phrases

Generate rate limiting configurations using AI. Use when protecting APIs from abuse.

Configure rate limiter config operations. Auto-activating skill for Security Fundamentals.\nTriggers on: rate limiter config, rate limiter config\nPart of the Security Fundamentals skill category. Use when configuring systems or services. Trigger with phrases like \

Implement sophisticated rate limiting with sliding windows, token buckets, and quotas.\nUse when protecting APIs from excessive requests.\nTrigger with phrases like \

Lightweight guidance for using the Redis Rate Limit TypeScript SDK, including setup steps, basic usage, and pointers to advanced algorithm, features, pricing, and traffic‑protection docs.

Analyze Cargo.toml dependencies and attempt to remove unused features to reduce compile times and binary size

MUST use when creating raw apps.

Scalable data processing for ML workloads. Streaming execution across CPU/GPU, supports Parquet/CSV/JSON/images. Integrates with Ray Train, PyTorch, TensorFlow. Scales from single machine to 100s of nodes. Use for batch inference, data preprocessing, multi-modal data loading, or

Use when user says \

Distributed training orchestration across clusters. Scales PyTorch/TensorFlow/HuggingFace from laptop to 1000s of nodes. Built-in hyperparameter tuning with Ray Tune, fault tolerance, elastic scaling. Use when training massive models across multiple machines or running

Build and maintain Raycast extensions using the Raycast API. Triggers on @raycast/api, List, Grid, Detail, Form, AI.ask, LocalStorage, Cache, showToast, and BrowserExtension. Use this repo's references/api/*.md files as the primary source of truth for component specs and API

Upload, sync, and manage files across cloud storage providers using rclone. Use when uploading files (images, videos, documents) to S3, Cloudflare R2, Backblaze B2, Google Drive, Dropbox, or any S3-compatible storage. Triggers on \

Cheminformatics toolkit for fine-grained molecular control. SMILES/SDF parsing, descriptors (MW, LogP, TPSA), fingerprints, substructure search, 2D/3D generation, similarity, reactions. For standard workflows with simpler interface, use datamol (wrapper around RDKit). Use rdkit

AWS RDS relational database service for managed databases. Use when provisioning databases, configuring backups, managing replicas, troubleshooting connectivity, or optimizing performance.