'assist' 검색 결과

Manage AI assistant configurations and peer-to-peer mesh network connections in the NV oOS Pro Toolkit. Covers assistant creation, model configuration, provider setup, peer discovery, mesh networking, cross-assistant communication, and detecting from a coding-agent session (Zed) which NV oOS assistants / MCP servers are enabled. Use when creating or editing AI assistants, configuring model providers, setting up peer connections, managing mesh network topology, debugging assistant behavior, or answering "is agent X available" / "what tools does this MCP have".

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Review Home Assistant migration behavior for input validation, configuration preservation, and output that does not overwrite existing files. Check storage schema versions, keep secrets out of diagnostics, and identify incomplete automation or integration behavior.

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• Reviewing supported storage schema versions
• Checking preservation of unfamiliar configuration fields
• Reviewing writes that must not overwrite existing files

Use when setting up, customizing, or troubleshooting the Salesforce Path component on Opportunity, Lead, Case, or custom objects. Triggers: 'add guidance to stages', 'key fields on path', 'celebrate closed won', 'path not showing', 'configure path steps', 'confetti on stage change'. NOT for creating the stage picklist — use admin/opportunity-management. NOT for in-app prompts — use admin/in-app-guidance-and-walkthroughs. Metadata: PathAssistant, PathAssistantStep, PathAssistantSettings, pathAssistantEnabled, canOverrideAutoPathCollapseWithUserPref, runtime_sales_pathassistant:pathAssistant, picklistValueName, recordTypeName, BusinessProcess.

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Manage AI assistant configurations and peer-to-peer mesh network connections in the NV oOS Pro Toolkit. Covers assistant creation, model configuration, provider setup, peer discovery, mesh networking, and cross-assistant communication. Use when creating or editing AI assistants, configuring model providers, setting up peer connections, managing mesh network topology, or debugging assistant behavior.

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Design a general-purpose assistant for tasks such as email summaries, short reply drafts, and note capture. The playbook defines task boundaries, completion criteria, and concise responses, with only the tools needed for the requested work.

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• Designing an assistant for email summaries
• Building a helper for short reply drafts
• Defining the scope of a note-taking assistant

After scaffolded practice, run an unassisted check with no AI help. Use to distinguish supported performance from what the learner can currently do independently.

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Provision a client-brand AI assistant in the NV oOS Pro Toolkit — brand intake, system-prompt authoring, tool selection, an idempotent provisioning script, credentials, and end-to-end verification. Use when creating a brand manager or social media assistant for a client brand (e.g. Aerlinn), onboarding a new brand into the Design Stack, replicating an existing brand assistant, or updating a brand assistant's prompt, tools, or campaign copy.

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Operational guide for the NV oOS assistant export/import track — the canonical nvoos-assistant bundle format (v1), the shared portability engine, its five surfaces (WP-CLI, REST, admin UI, AI tools, backup provider), the Pro blueprint exporter, credential-redaction rules, legacy/blueprint import compatibility, test conventions, and the Content Graph port checklist. Use when extending or debugging assistant export/import, adding a surface, changing the bundle schema, fixing round-trip fidelity, or continuing the portability track ("continue the portability plan", "add assistant export to X").

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Create a practice-area guide for a legal clinic that sets intake questions, how much help AI gives students, supervisor review requirements, checks using other plugins, and local rules. The guide configures how student-facing skills behave.

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• Set intake questions for each clinic practice area
• Adjust AI assistance to match teaching goals
• Define which student outputs require supervisor review

Manage Home Assistant configuration safely and fast — edit and deploy YAML (automations, blueprints, scripts, scenes, templates, MQTT), validate with ha core check, deploy via git or rapid scp, reload-vs-restart correctly, verify changes from logs, traces and entity state, and build Lovelace dashboards. Use for any Home Assistant config, automation, template, or dashboard work over SSH/hass-cli/MCP.

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Use when the user asks about Higgsfield Assist (the built-in GPT-5 copilot), how to use the platform's native AI assistant, credit optimization strategies, plan selection, how to get more from fewer credits, or platform efficiency tips.

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Initiate natural language Q&A through Amazon's storefront Alexa shopping assistant to get shopping guidance answers, recommended product groups, ASIN lists, and follow-up questions. Each call supports only 1 prompt; for follow-ups, the agent must summarize context and concatenate a new question for a new request. A url can be used to supplement Amazon page context. Trigger when the user mentions Amazon Alexa, Alexa shopping assistant, Amazon smart assistant, AI shopping guide, conversational product selection, natural language shopping, Amazon chat Q&A, Amazon Alexa shopping, conversational shopping, AI shopping assistant, follow-up questions, product recommendation conversation, context follow-ups. Even if the user does not explicitly mention "Alexa", if their need is to "ask for product recommendations on Amazon using natural language", this skill should also be triggered.

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Design, create, or validate saved and transient Vapi voice assistants. Use for new phone or web agents, production system prompts and first messages, saved-versus-transient architecture, model/voice/transcriber selection, multilingual compatibility, existing tool attachment, native call-control tools, assistant hooks, and Create Assistant API validation errors.

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Security-Scanner Agent fuer fabrikIQ und andere Projekte. Fuehrt umfassende Sicherheitspruefungen durch. Trigger bei: (1) Pre-commit Validation, (2) PR-Creation, (3) Weekly Security Audits, (4) Nach Dependency-Updates, (5) Vor Production Deployments. <example> Context: User moechte vor einem Commit sicherstellen, dass keine Secrets committed werden. user: "Ich will gleich committen. Pruefe mal auf Secrets." assistant: "Ich starte den security-scanner Agent, um den Code auf API Keys, Tokens und andere Secrets zu pruefen." <Task tool call to security-scanner agent> </example> <example> Context: Weekly Security Audit des fabrikIQ-Projekts. user: "Fuehre den woechentlichen Security-Scan durch." assistant: "Ich fuehre einen vollstaendigen Security-Scan durch: Secret Detection, Dependency Audit, OWASP Patterns, Security Headers und Rate Limiting." <Task tool call to security-scanner agent> </example> <example> Context: User hat Dependencies aktualisiert und will Vulnerabilities pruefen. user: "Ich habe npm update und pip install -U gemacht. Gibt es Sicherheitsprobleme?" assistant: "Ich scanne die aktualisierten Dependencies auf bekannte Vulnerabilities mit dem security-scanner Agent." <Task tool call to security-scanner agent> </example> <example> Context: PR-Review mit Security-Fokus. user: "Review den PR #42 auf Security-Probleme." assistant: "Ich analysiere die geaenderten Dateien im PR auf Security-Patterns: SQL Injection, XSS, Hardcoded Credentials und fehlende Input-Validation." <Task tool call to security-scanner agent> </example>

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Add regression tests to AI-assisted code changes so previously found bugs are checked automatically. Test required API fields and sandbox response contracts, then run tests and builds before AI review to catch recurring omissions and inconsistent behavior.

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• Add regression tests after fixing a bug
• Check required API response fields
• Review sandbox and production response consistency

Investigate a Homecore capability by tracing relevant source files, tests, and accepted architecture decisions. Check documented status and limitations before proposing code, while keeping implementation presence separate from deployment compatibility or claims of Home Assistant parity.

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• Find source files and design decisions for a Homecore capability
• Check documented implementation status and limitations
• Review focused tests before proposing code changes

Design and build AI agents for business, research, operations, or creative work. Define essential actions and knowledge, start with a simple execution loop, and add progress tracking or separate child agents as needs emerge.

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• Designing an assistant for business tasks
• Building a research agent
• Choosing essential actions and knowledge

Build voice assistants and conversational characters with ElevenLabs. Configure voices, language models, and external tools, then connect conversations to a website widget or use Twilio integration for outbound phone calls.

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• Creating a voice bot for customer support
• Embedding a voice assistant on a website
• Building an interactive voice character

Build Java applications that exchange live audio with AI assistants using Azure AI VoiceLive. The skill covers authentication, streaming sessions, speech detection, voice selection, transcription, and handling responses over WebSocket, a persistent two-way connection.

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• Implementing a real-time voice assistant in Java
• Configuring speech detection and interruptions
• Adding transcription and noise reduction

Support product planning for Auri, a voice assistant combining Alexa and Claude. Covers product vision, the Vitoria Neural persona, AWS architecture, service tiers, a four-phase roadmap, market launch planning, success metrics, and competitive analysis.

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• Reviewing Auri product requirements
• Organizing service tiers and the development roadmap
• Considering market launch plans and competitors

Build voice skills for Amazon Alexa and plan an assistant that uses Claude for its intelligence. Covers integration with AWS services including Lambda, DynamoDB, Polly, Transcribe, and Lex, as well as Smart Home.

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• Developing voice skills for Amazon Alexa
• Building an Alexa assistant that uses Claude
• Planning Alexa integrations with AWS services

Turns supplied AI agent evaluation results into reports that distinguish autonomous success, human-assisted success, failure, timeout, and invalid runs. Makes metric denominators, retries, timing, costs, and comparison conditions explicit to support evidence-based decisions.

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• Separating autonomous and human-assisted success rates
• Reporting evaluations with retries and invalid runs
• Comparing agents or releases under matched conditions

Check whether the iMessage channel can read messages on a Mac and review who is allowed to contact the assistant. Get guidance on required permissions, current access rules, and the next setup step.

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• Check initial iMessage channel setup
• Investigate why texts do not reach the assistant
• Review approved senders and access rules

Design hands-on workshops with short explanations, immediate exercises, and quick self-checks. Use brief dialogue between a teacher and an assistant to guide practice, then finish with a small project that combines what learners have tried.

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• Create a workshop built around hands-on practice
• Turn long explanations into short briefs and exercises
• Write guiding dialogue for a teacher and assistant