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Found 59 Skills
PokeClaw (PocketClaw) — on-device Android AI phone agent using Gemma 4 via LiteRT-LM with tool calling, accessibility automation, and optional cloud models.
A complete workshop curriculum for building an agentic application using the Gemini Interactions API. Guides the user from basic API calls to a full production coding agent.
Provides tool and function calling patterns with LangChain4j. Handles defining tools, function calls, and LLM agent integration. Use when building agentic applications that interact with tools.
Use when building durable AI agents or agentic workflows with Inngest and AgentKit, including model calls, tool calls, multi-agent networks, human approval, realtime progress, provider rate limits, crash-safe execution, and Agent Evals handoff. Covers AgentKit, `step.ai`, `step.run`, `step.waitForEvent`, native realtime, and when to use lower-level Inngest primitives instead of an in-memory agent loop. Use `inngest-agent-evals` with this skill when the user wants scoring, sessions, experiments, deferred scorers, or outcome-based evaluation for the agent.
Provider-agnostic, type-safe AI SDK for streaming, tool calling, structured output, and multimodal content.
LangGraph-based agent framework for consistent tool calling with automatic tool loops. Use when you need reliable multi-step task execution with OpenAI-compatible providers (Z.AI/GLM-5, OpenRouter, Groq, DeepSeek, Ollama).
Design and integration guidance for adding a reusable AI Agent chat interface to an existing web application. Use when adding an embedded AI assistant, chat view, multimodal input, speech-to-text, session history, long-task execution UI, Agent activity states, provider/model settings, or Tool / Function Calling support. The Agent is a supporting interface for the existing application rather than the application's primary UI.
Analyse agent execution to find wasted tool calls, wrong turns, and blind alleys. Optimise agents to reach their goal in the fewest turns, tokens, and least time. Recommend harness/model changes — never apply without user approval.
Quickly build Chainlit AI chat demos for product demos, proof-of-concept, and stakeholder presentations. Trigger words: chainlit, build demo, chat demo, conversation demo
Write, review, or integrate Apple's on-device FoundationModels framework (iOS 26.0+, macOS 26.0+). Use when building generative AI features, structured data extraction, tool calling, or streaming text generation natively on Apple Silicon devices.
Call use_skill as your FIRST and ONLY action when the user asks to DELETE, REMOVE, or GET RID OF an existing run configuration for Mule applications. Use this ONLY for deleting/removing configurations, NOT for creating or editing. Trigger phrases include "delete config", "remove config", "get rid of config", "delete all configs", "remove all my run configs", "clean up configs". When you call use_skill, it must be the only tool call in that response.