Skills for your AI
Scaffolds, versions, and registers Claude Code plugins with correct directory structure, plugin.json and marketplace.json manifests. Use when creating a new plugin, bumping a plugin version, adding commands/skills/agents/hooks/MCP servers, or registering a plu
Scaffolds and explains Claude Code plugin structure, manifest, and component organization. Use when creating a new plugin, configuring plugin.json, organizing commands/agents/skills/hooks/MCP servers, fixing intra-plugin paths, or validating kebab-case naming.
Guides GRPO/RL fine-tuning of language models with TRL for reasoning and structured tasks, covering dataset prep, reward functions, configs, training setup, and log diagnosis. Use when the user wants to prepare data for GRPO, design or test reward functions, g
Fine-tunes and aligns language models with TRL methods (SFT, DPO, PPO, GRPO, reward model training) and evaluates the results. Use when the user wants to train on instruction or preference data, run RLHF pipelines, or test an aligned model on prompts.
Generates safe, auditable PowerShell 5.1 scripts for Windows infrastructure automation across Active Directory, DNS, DHCP, and GPO using RSAT modules. Use when asked to create, review, or plan PowerShell 5.1 scripts, bulk AD user or group changes, DNS record u
Designs WinForms, WPF/Metro, and terminal UIs for PowerShell automation tools with clean separation between UI and business logic. Use when building or refactoring a PowerShell GUI or TUI, choosing a UI technology, or moving automation logic out of UI scripts.
Plans and optimizes production technology integration, covering equipment selection, compatibility and risk analysis, data migration, process automation, cost and ROI, training, implementation monitoring, stakeholder reporting, and advanced production systems.
Coordinates multi-agent workflows by detecting intent, validating payloads, dispatching agents in sequence, and returning consistent JSON. Use when a request must be checked for required fields, routed through a configured agent sequence, or answered with clar
Guides design, composition and optimization of DSPy pipelines — signatures, modules, optimizers, LM providers, RAG and agents. Use when the user asks to build or improve a DSPy program, define a signature, pick a module, configure an optimizer or LM provider,
Constrains LLM output with regex patterns, selection lists, and grammars to guarantee valid JSON, XML, or code, and builds multi-step guided workflows. Use when the user needs format-guaranteed generation, multiple-choice classification, structured JSON/XML ou
Teaches developers to extract validated structured data from LLM responses with the Instructor library, covering setup, Pydantic models, validation and retries, streaming, and extraction examples. Use when the user asks about Instructor setup, response models,
Guides users to set up guaranteed-valid structured generation with the Outlines library for local LLMs, covering Pydantic JSON, choice, regex, integer, float, and nested models. Use when a user wants valid JSON, XML, regex, or code output from a local model, n
Provides PufferLib reinforcement learning engineering guidance to train agents, build custom environments, and optimize multi-agent or distributed training. Use when the user wants PPO training, PufferEnv development, vectorization, policies, integrations, or
Designs and maintains QA team collaboration, task tracking, test management, bug resolution, reporting, and automation processes. Use when a QA manager needs task assignments, test cases, bug workflows, tool integrations, reports, stand-ups, knowledge bases, c
Plans QA testing strategy across coverage analysis, risk prioritization, environment setup, test data, automation, scheduling, reporting, and CI/CD. Use when a QA manager needs test plans, coverage gap analysis, risk matrices, test cases, automation strategy,
Use when the user asks to design a RAG pipeline, choose a chunking strategy or embedding model, pick a vector database, or evaluate retrieval quality (precision@k, recall@k, NDCG). Examples: 'design a RAG system for our docs', 'what chunk size should I use for
Manages a local Chroma vector database for creating collections, adding documents with embeddings and metadata, semantic search, retrieval, updates, and deletion. Use when the user wants to store embeddings, run semantic search or RAG retrieval, or manage Chro
Manages a Qdrant vector database for RAG and semantic search: creates collections, upserts points with payloads, runs filtered and batch searches, and retrieves collection info. Use when the user asks to set up a Qdrant collection, insert or update vectors, se
Generates local sentence-transformers embeddings for RAG, similarity, semantic search and batch encoding, and advises on model choice and vector store integration. Use when the user asks to embed texts, compare similarity, rank a corpus, batch-encode, pick a m
Hunts vector-store and embedding-layer weaknesses in RAG pipelines — persistent corpus poisoning, cross-tenant vector IDOR, source-text and metadata leakage, and retrieval hijack — with proof gates. Use when testing an authorized RAG application's retrieval la
Drafts and maintains concise repo-specific instruction files for coding agents, covering initial drafts, updates after agent mistakes, and nested-file advice. Use when creating an agent instruction file for a repository, correcting one after a repo-specific mi
Analyzes e-commerce return and refund data, customer feedback and processes to produce reports, policy guides, templates, training scenarios and automation plans. Use when reviewing return reasons, refund pain points, chatbots, self-service portals, RMA/return
Review Playwright tests for quality. Use when user says "review tests", "check test quality", "audit tests", "improve tests", "test code review", or "playwright best practices check".
Builds, configures, and tests Model Context Protocol servers in Ruby using the official SDK and Rails integration. Use when setting up an MCP server, defining tools, resources, prompts, schemas, annotations, custom JSON-RPC methods, error handling, structured
