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Configure Messaging for In-App and Web (MIAW) channels in Service Cloud: Messaging Channel, Embedded Service Deployment, CORS/CSP Trusted Sites, pre-chat fields, session routing by Queue or Omni-Channel Flow, Status-Based capacity, Live Agent migration. Trigger keywords: MessagingChannel, EmbeddedServiceConfig, messagingChannelType, EmbeddedMessaging, sessionHandlerQueue, sessionHandlerFlow, embeddedConfig, automatedResponses, CorsWhitelistOrigin, CspTrustedSite, BrandingSet, MessagingSession, MessagingEndUser, enhanced chat, embedded messaging, chat widget, pre-chat form, auto-response. NOT for an Agentforce agent in the chat window - use agentforce/agent-channel-deployment. NOT for Omni-Channel enablement, Service Channels or skills-based routing - use admin/omni-channel-routing-setup.

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Deploy AI models to embedded hardware using MathWorks tools (MATLAB, Simulink, Embedded Coder). Covers two workflow patterns: (1) MathWorks-native or imported models rebuilt as dlnetwork for lean hardware, (2) direct C/C++ code generation from PyTorch and LiteRT models. Both patterns support all targets (Cortex-M/A/R, x86, GPU). Trigger when: user wants to deploy AI to embedded targets; generate C/CUDA from neural networks; compress AI models for MCU; integrate AI in Simulink for system-level simulation; import PyTorch/ONNX/TensorFlow models for embedded deployment; optimize AI for resource-constrained hardware; or use loadPyTorchExportedProgram, loadLiteRTModel, importNetworkFromPyTorch, importNetworkFromONNX, importNetworkFromTensorFlow, importNetworkFromKeras, dlquantizer, exportNetworkToSimulink, or Embedded Coder with AI models.

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Deploy AI models to embedded hardware using MathWorks tools (MATLAB, Simulink, Embedded Coder). Covers two workflow patterns: (1) MathWorks-native or 3P-imported models rebuilt as dlnetwork for lean hardware (Cortex-M, DSP), (2) direct C/C++ code generation from PyTorch and LiteRT models for high-performance hardware (Cortex-A, x86, GPU). Trigger when: user wants to deploy AI to embedded targets; generate C/CUDA from neural networks; compress AI models for MCU/DSP; integrate AI in Simulink for system-level simulation; import PyTorch/ONNX/TensorFlow models for embedded deployment; optimize AI for resource-constrained hardware; or use loadPyTorchExportedProgram, importNetworkFromPyTorch, dlquantizer, exportNetworkToSimulink, or Embedded Coder with AI models.

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Plan subtitles as layers over a video, deciding which spoken phrases to omit, show normally, or emphasize behind the subject. The guidance preserves full-frame composition and limits large embedded words to occasional key moments.

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• Planning subtitles for a talking-head video
• Choosing words to emphasize behind the subject
• Centering a scene that carries subtitles

Inspect suspicious PDFs without opening them in a reader. Use PDFiD, pdf-parser, and peepdf to examine internal objects, extract scripts, embedded files, and URLs, and document how the suspected attack works.

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• Triage suspicious PDF email attachments
• Investigate embedded JavaScript and automatic actions
• Extract embedded files and external URLs

Plan security testing for IoT and embedded devices, from circuit board inspection and firmware analysis to wireless links, companion apps, and cloud APIs. Includes tools, investigation checklists, and guidance for documenting findings.

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• Planning smart home device security tests
• Analyzing firmware for embedded secrets
• Assessing industrial device communications

Embedded hardware debugging workflow for probe-rs targets using embedded-debugger-mcp. Use when Codex or Claude Code needs to inspect debug probes, validate embedded debugger setup, start the MCP server, guide a user through ARM Cortex-M/RISC-V flashing/debugging/RTT workflows, or operate without installing an MCP client by using the CLI plus prompts.

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Review styles written directly in HTML or embedded style blocks, and move suitable rules into external stylesheets. Check layouts across screen sizes and interaction states while preserving justified exceptions for critical styles and dynamic values.

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• Reviewing styles written directly in HTML
• Moving embedded styles into external stylesheets
• Checking exceptions for critical CSS and dynamic values

Use when you need to generate a checklist document with embedded commands inventory, following the embedded template exactly and producing INVENTORY-COMMANDS-JAVA.md in the project root. This should trigger for requests such as Create embedded commands inventory checklist; Generate INVENTORY-COMMANDS-JAVA.md; Use @001-commands-inventory; Inventory embedded Java project commands; List command files bundled for Java agents. Part of Plinth Toolkit

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Use when you need to generate a checklist document with embedded agents inventory, following the embedded template exactly and producing INVENTORY-AGENTS-JAVA.md in the project root. This should trigger for requests such as Create embedded agents inventory checklist; Generate INVENTORY-AGENTS-JAVA.md; Use @002-agents-inventory; Inventory embedded Java agent definitions; List generated agent roles for Java development. Part of Plinth Toolkit

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Evaluates embedded finance opportunities with distribution economics and regulatory framework analysis. Use when analyzing embedded finance, evaluating BaaS models, or assessing embedded lending/insurance.

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"Apply Granovetter's embeddedness theory to analyze how economic behavior is embedded in ongoing social relations, avoiding both over-socialized and under-socialized accounts. Use this skill when the user needs to explain why market transactions deviate from pure economic rationality, analyze how trust and social ties shape business dealings, evaluate structural vs relational embeddedness in inter-firm networks, or when they ask 'why do firms prefer existing partners over cheaper alternatives', 'how do social relationships shape economic outcomes', or 'is this market truly arms-length'.".

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Expert-level embedded systems covering microcontrollers, RTOS, peripheral interfaces, low-power design, bare-metal programming, and embedded Linux.

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Manage Orca worktrees, separate working directories, along with terminals, repositories, and its embedded browser through the CLI. Use it to hand work to another agent, manage artifacts, run automations, and share skills within Orca.

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• Starting codex or claude in a child worktree
• Reading terminal output and sending input
• Operating Orca's embedded browser

Manage embedded services such as 9Router and CLIProxyAPI through local service APIs. Install, start, stop, restart, or update services, then check their status, retrieve logs, and configure automatic startup.

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• Installing and starting embedded services
• Stopping or restarting services
• Checking service status and logs

Convert Markdown files into formatted Word documents with a title page, a table of contents, styled tables and code blocks, and embedded PNG images. The converter runs in Node.js without Pandoc or LibreOffice.

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• Turning Markdown reports into Word documents for sharing
• Creating Word documents with embedded PNG diagrams
• Adding a title page from document metadata

Inspect suspicious PDFs without opening them in a document viewer. Use peepdf, pdfid, and pdf-parser to examine internal objects, extract embedded code and files, and report threat indicators such as URLs and hashes.

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• Triaging suspicious PDF email attachments
• Investigating PDF exploit documents
• Extracting embedded JavaScript and files

Add or modify commands handled inside Crush's embedded shell before they reach the operating system. The guidance covers command routing, input and output streams, exit codes, and cancellation so commands work with pipes, redirection, and hook timeouts.

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• Adding a command to Crush's embedded shell
• Modifying an existing built-in command
• Supporting pipes and output redirection

Turn an electronics or IoT idea into a working breadboard prototype. Get board and software recommendations, a plan for viewing sensor readings, and time and cost ranges tailored to experience, budget, and location.

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• Choosing a board and development tools for a first electronics project
• Planning phone access to sensor readings and alerts
• Estimating prototype costs and build time

Evaluate older Wi-Fi clients and embedded devices for KRACK and FragAttacks vulnerabilities. Covers test suites, likely patch status, practical impact, and reporting findings by device, firmware version, and vulnerability identifier.

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• Assessing older Wi-Fi clients
• Reviewing IoT firmware patch status
• Distinguishing KRACK and FragAttacks impacts

Tests whether an AI agent exposes real credentials embedded in accessible source code or configuration. It requests searches for keys, passwords, and private keys, then documents confirmed disclosures with file locations and conversation evidence.

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• Checking source code for exposed embedded API keys
• Reviewing credentials in .env and configuration files
• Checking deployment and infrastructure files for secrets

Build applications with embedded wallets, user sign-in, and transactions across multiple blockchains. This skill guides wallet creation, spending limits, shared approvals, and server-controlled wallets for organizations or AI agents using Privy.

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• Add sign-in and embedded wallets to an app
• Set spending limits for an AI agent's wallet
• Build treasury wallets with shared approvals

Next.js adapter for embedding emulators directly in a Next.js app via @emulators/adapter-next. Use when the user needs to embed emulators in Next.js, set up same-origin OAuth for Vercel preview deployments, create an emulate catch-all route handler, configure Auth.js/NextAuth with embedded emulators, add persistence to embedded emulators, or wrap next.config with withEmulate. Triggers include "Next.js emulator", "adapter-next", "embedded emulator", "same-origin OAuth", "Vercel preview", "createEmulateHandler", "withEmulate", or any task requiring emulators inside a Next.js app.

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Deploy MATLAB-generated code to embedded hardware using Embedded Coder. Use when configuring code generation for microcontrollers (STM32, Raspberry Pi, ARM Cortex), setting up PIL/SIL verification, disabling dynamic memory allocation, or configuring hardware-specific code generation settings. Covers ERT-based configurations, processor-in-the-loop testing, memory constraints, and the MEX→SIL→PIL verification progression.

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