demo-2-1-features
Demo skill showing all Claude Code 2.1 features. Use when asked to "demo 2.1" or "show new skill features".
Demo skill showing all Claude Code 2.1 features. Use when asked to "demo 2.1" or "show new skill features".
Tools for creating and managing Claude Code Skills. Use when users need to create new skills, validate skill structure, or package skills for distribution. Triggers include creating custom workflows, encapsulating domain knowledge, building document generation templates, or integrating specific tools and APIs.
Fetches additional perspectives from OpenAI Codex and Google Gemini for architecture, review, and debugging. Transparently displays all LLM calls.
Comprehensive toolset for creating, converting, validating, and packaging Skilzy-compliant AI agent skills. This skill should be used when users want to initialize a new skill, convert a Claude skill archive to the Skilzy format, validate an existing skill's structure and compliance, or package a skill for distribution to the Skilzy registry.
Manage multi-session AI agent workflows using klondike CLI. Use when working on klondike-managed projects (those with .klondike/ directory), when starting/ending coding sessions, tracking features through lifecycle, or maintaining coherence across context window resets. Triggers on session management, feature tracking, progress handoffs, and verification workflows.
Rails service object patterns and business logic organization. Automatically invoked when working with service objects, extracting business logic, implementing command/query patterns, or organizing app/services. Triggers on "service object", "service", "business logic", "workflow", "orchestration", "command pattern", "query object", "form object", "interactor", "result object".
Local Microsoft Agent Framework documentation reference. Use when asked about Microsoft Agent Framework, building AI agents in .NET or Python, MCP servers/clients, durable agents, agent tools, Teams/WebChat adapters, or agent-to-agent communication.
Build production agentic applications on OCI using Oracle Agent Development Kit with multi-agent orchestration, function tools, and enterprise patterns
Code Query with AI-enhanced deterministic analysis via SplitMix ternary classification
Bootstrap AI Developer Workflows (ADWs) infrastructure in any codebase. Use when user wants to: "set up ADWs", "bootstrap agentic workflows", "add AI developer workflows", "enable programmatic agent execution", "initialize ADW infrastructure", or "set up programmatic Claude Code". This enables programmatic agent orchestration via subprocess/SDK, reusable workflow templates, multi-phase workflows, and structured observability for agent executions.
Help users discover Contextune capabilities and understand how to use natural language commands. Use when users ask about Contextune features, available commands, how to use the plugin, or what they can do. Activate for questions like "what can Contextune do?", "how do I use this?", "show me examples", "what commands are available?"
Semantic code search with VectorCode using embeddings for finding code by meaning, not just keywords. Use when searching for code patterns, similar implementations, concept-based search, or when keyword search fails. Automatically available via MCP.
Help users customize devcontainers by adding packages, extensions, features, and settings. Use when users ask about adding tools, languages, or configuring their development environment. Focus on practical devcontainer customization, not BitBot internals.
Gmail inbox management via ANIMA condensation. Transforms messages into GF(3)-typed Interactions, routes to triadic queues, detects saturation for inbox-zero-as-condensed-state. Use for email triage, workflow automation, or applying ANIMA principles to Gmail.
Run the same prompt with Claude, OpenAI, and Gemini in parallel, then return back exact replies you got back without modifying the results one bit.
Generate answers to questions with structured output using AI search and synthesis. Use when you need factual answers with citations from web sources, or when you want to extract specific structured information in response to a query.
LangChain JS/TS framework for building LLM-powered applications - models, chains, tools, and RAG patterns.