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Configure safety checks for LLM applications with NeMo Guardrails. Covers attempts to bypass safety rules, input and output validation, masking personal information, and checking factual claims through programmable rules and integrations.

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• Detecting instructions that try to bypass safety rules
• Masking personal information before processing
• Adding factual checks to generated answers

Guide the design of AI product features with output validation, responses displayed as they arrive, prompt versioning, and testing. Address API costs, failures, and unsafe input when preparing language model integrations for production.

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• Reviewing AI features before production release
• Designing validation for AI-generated output
• Managing prompt versions and regression tests

Build AI applications with LangChain, including chatbots with conversation history and systems that search documents before answering. The skill provides examples for connecting models, calling tools, retrieving information, and tracing application runs.

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• Building a chatbot that uses conversation history
• Creating a question-answering system for documents
• Developing an agent that calls external tools

Connect cognee to model providers, databases, storage services, and development tools. Guides configuration of language models and embeddings, the numerical representations used for search, including the separate settings each requires.

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• Switching model providers or using Ollama locally
• Connecting cognee to Postgres or Neo4j
• Storing cognee data in S3

Adapt NanoClaw by adding messaging channels, connecting services, changing response instructions, or adjusting message routing. The skill clarifies the request, selects dedicated skills where available, applies changes, and explains how to verify them.

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• Adding Telegram or Slack as an input channel
• Connecting an external service to a specific agent group
• Changing an agent group's persona or response style

Build Zoom meeting integrations in Windows C++ applications, including custom interfaces and bots that run without a visible interface. Guidance covers authentication, audio and video data access, project setup, and troubleshooting callbacks through the Windows message loop.

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• Embedding Zoom meetings in a Windows desktop application
• Building a meeting bot without a visible interface
• Receiving meeting audio and video data

Build server-side Zoom integrations for meeting scheduling, user management, and recording downloads. This reference guides API endpoint selection, OAuth authentication, request limits, and error diagnosis, with examples for automated workflows and event notifications.

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• Automating meeting creation and updates
• Managing Zoom users in bulk
• Downloading recordings after event notifications

Guide server-side Zoom integrations using Zoom Rivet SDK in JavaScript or TypeScript. Consult patterns for authentication, incoming event notifications, typed API calls, multiple modules, and webhook processing on AWS Lambda.

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• Implementing Zoom authentication and token handling
• Building a Team Chat bot with API integration
• Combining multiple Zoom modules in one server

Integrate Zoom Contact Center chat, video, ZVA, and scheduled callbacks into native iOS apps. Follow guidance on service initialization, app lifecycle events, video rejoining, and callback handling, with references and debugging checklists.

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• Add chat or video support to a native iOS app
• Implement scheduled callbacks and callback handling
• Connect app lifecycle events to the SDK

Helps plan Zoom integrations by comparing APIs, SDKs, app types, authentication, and permissions. Guides the choice between repeatable API automation and MCP, a protocol for connecting AI agents to tools, and identifies relevant implementation skills.

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• Choose a Zoom SDK for embedding meetings
• Compare REST API automation with AI agent tooling
• Plan meeting creation, authentication, and event handling

Helps integrate Zoom Contact Center into native Android apps, including chat, video, virtual agent interactions, and scheduled callbacks. Covers SDK setup, service lifecycle management, campaign support, and handling users who rejoin a session.

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• Add chat and video support to an Android app
• Integrate virtual agents and scheduled callbacks
• Check SDK initialization and service cleanup

Build custom video session experiences in Unity using Zoom Video SDK wrapper APIs. Follow guidance on connecting SDK events to scenes and interface state, with references for session joining, lifecycle management, compatibility, and troubleshooting.

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• Integrating Zoom Video SDK into a Unity app
• Connecting video session events to Unity scenes and interface state
• Checking session joining and lifecycle patterns

Choose suitable Zoom APIs and SDKs, tools for connecting or embedding Zoom features, for a product idea. Get a recommended approach, supporting components, tradeoffs, and a concrete implementation sequence.

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• Choose how to embed Zoom meetings in a product
• Compare options for custom video features
• Plan Zoom automation and event delivery

Support Zoom meeting integration in Unreal Engine projects using C++ and Blueprint wrappers, intermediary code that calls the SDK. Consult guides for SDK mappings, initialization and meeting flows, compatibility, and troubleshooting.

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• Embedding Zoom meetings in an Unreal Engine project
• Checking how C++ or Blueprint wrappers map to the SDK
• Reviewing meeting join and start implementation patterns

Guide Zoom Virtual Agent integration into websites and mobile apps, covering embedded chat, conversation startup and cleanup, and handoff to live support. It also directs developers to platform references and knowledge-base synchronization workflows.

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• Embed a support bot on a website
• Wrap web chat in an Android or iOS app
• Implement handoff from a bot to live support

Set up and use Composio to connect AI agents with apps such as Gmail, Slack, and Notion. Selects guidance for personal accounts or product integrations, covering setup, app operations, troubleshooting, and migration.

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• Connect a personal AI agent to apps
• Integrate account connections into a product
• Diagnose failed connections or tool calls

Build a computer-control loop where Cua Driver observes and acts, while TypeSafe Jev chooses from predefined actions. Validate each choice, execute one action at a time, and verify the result before continuing.

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• Build a Jev integration for browser automation
• Create action candidates for native desktop apps
• Reject stale or unknown action choices

Create and review Mastra tests that reproduce user-visible failures through public APIs, real network requests, and actual storage. Verify that tests fail before a fix and cover the different execution paths affected by the bug.

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• Reproduce a reported bug before fixing it
• Review tests that rely heavily on mocked dependencies
• Check regression coverage across engines and adapters

Create, edit, and reorganize Mastra documentation with guidance matched to the page type. Find the relevant rules for writing, links, navigation, shared components, diagrams, and redirects when reviewing pages or changing their structure.

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• Write or revise Mastra documentation pages
• Review sidebars and page organization
• Check redirects when moving or deleting pages

Design agents for recurring internal work such as scheduled posts, data synchronization, and event responses. Define triggers, duplicate prevention, approval boundaries, required integrations, and a consistent seven-field execution record for every run.

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• Design an agent for scheduled internal notifications
• Define data synchronization between two tools
• Build a workflow that responds to incoming events

Create and customize Qwen Code extensions using templates for context, commands, skills, agents, and MCP servers that connect external tools. Validate configuration and referenced files, review executable behavior, and prepare the extension for local testing.

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• Creating a Qwen Code extension from a template
• Packaging custom commands and skills in an extension
• Adding MCP servers or other extension integrations

Test Qwen Code CLI behavior from model requests through tool execution. Reproduce bugs, check terminal interactions and MCP tool connections, and inspect API logs using real models or mock servers for controlled scenarios.

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• Reproduce reported CLI bugs and verify fixes
• Test MCP tool connections through the CLI
• Check terminal rendering and keyboard interactions

Compare repository documentation with current code, tests, and settings to find missing, incorrect, or outdated guidance. Update affected pages, prioritize problems that block readers, and check examples and navigation for consistency.

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• Find outdated setup instructions
• Document existing features that lack guidance
• Check settings and command examples against code

Turn an OpenAPI specification into starter code for an MCP server, which connects AI agents to API tools. Support Python or TypeScript implementations, validate tool definitions, and plan changes that preserve compatibility.

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• Exposing an existing REST API to an AI agent
• Creating a Python or TypeScript MCP server scaffold
• Checking tool definitions before integration tests