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概要と使いどころ
Audit how a brand is currently expressed across touchpoints and flag drift from its defined tokens, voice, and strategy. Use to inventory and critique an existing brand before changing it.
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Grounded brand decisions from a curated corpus — archetype, voice, naming, colour psychology, logo-style fit, messaging frameworks, archetype→type mapping. Use to ground brand strategy and identity.
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Ground a brand strategy from the corpus — archetype, opposable positioning, voice and tone, messaging framework. Use to decide who a brand is for, what it stands for, and how it sounds.
日本語の概要は準備中です。原文の説明を表示しています。
All agents have equal voice; decisions made by majority vote.
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Agentes de voz representam a fronteira da interação com IA - humanos falando naturalmente com sistemas de IA. O desafio não é apenas reconhecimento e síntese de fala, mas alcançar fluxo de conversa natural com latência inferior a 800ms enquanto se lidam com interrupções, ruído de fundo e nuances emocionais. Esta habilidade cobre duas arquiteturas: fala-para-fala (OpenAI Realtime API, menor latência, mais natural) e pipeline (STT→LLM→TTS, mais controle, mais fácil de depurar). Insight-chave: latência é a restrição. Hu
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Use when Invoice-Downloader work involves mailbox batch tests, truth audit, regression validation, P0/P1/P2 decisions, packaged frontend acceptance, or clean reruns.
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Use when the user wants text to sound more human, says writing sounds "too AI" or "too ChatGPT," asks to humanize or rewrite a draft to feel natural, or shares content wanting it to feel authentic and less robotic. Also applies to LinkedIn posts, blog drafts, or emails where the user wants a more genuine voice.
日本語の概要は準備中です。原文の説明を表示しています。
Validate Commodore 64 SID 6581/8580 sound emulation in EMULATORS, including $D400-$D7FF register decoding, voices, frequency, pulse width, control bits, ADSR/envelope behavior, oscillator sync/ring/noise/test, filters, volume DAC/sample clicks, paddles, read-only registers, mirrors, and reSID integration. Use when Codex reviews or edits SID, Sound, audio wrapper, register, filter, waveform, envelope, or mapped SID behavior.
日本語の概要は準備中です。原文の説明を表示しています。
Writing quality guidelines, formatting conventions, and styling constraints for documentation. Trigger when: - Writing, editing, or auditing documentation files, READMEs, markdown files, or guides. - Modifying files with suffixes like: *.md, *.qmd, *.txt, *.rst. - Prompt contains keywords: doc, documentation, spelling, grammar, headers, links, table alignment, Divio, tone, voice, clarity.
日本語の概要は準備中です。原文の説明を表示しています。
运用《声纹技术：从核心算法到工程实践》(王泉) 的方法论,指导声纹识别系统的设计、选型与工程落地。适用于用户要设计声纹识别/说话人验证系统的技术方案、评估声纹特征提取方法(MFCC/i-vector/x-vector/ECAPA-TDNN)的优劣、做声纹反欺诈或活体检测的技术选型、以及将声纹技术落地到实际产品(电话客服/智能音箱/安防)时使用。
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Audit a composer output against four hard checks before delivery — cite integrity, voice rules, word count, schema validity. Always invoked after the polisher (English) or humanizer-* (Arabic / Hebrew). Emits a VerificationReport Pydantic object; orchestrator branches on `overall_passed`. Target ≥0.9 score per run. Triggers automatically as the final composer sub-agent; not user-facing.
日本語の概要は準備中です。原文の説明を表示しています。
Extract text, tables, and structured data from documents using Azure Document Intelligence (@azure-rest/ai-document-intelligence). Use when processing invoices, receipts, IDs, forms, or building custom document models.
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Build document analysis applications with Azure Document Intelligence (Form Recognizer) SDK for Java. Use when extracting text, tables, key-value pairs from documents, receipts, invoices, or building custom document models.
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Azure AI Document Intelligence SDK for .NET. Extract text, tables, and structured data from documents using prebuilt and custom models. Use for invoice processing, receipt extraction, ID document analysis, and custom document models. Triggers: "Document Intelligence", "DocumentIntelligenceClient"...
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Auri: assistente de voz inteligente (Alexa + Claude claude-opus-4-20250805). Visao do produto, persona Vitoria Neural, stack AWS, modelo Free/Pro/Business/Enterprise, roadmap 4 fases, GTM, north star WAC e analise competitiva.
日本語の概要は準備中です。原文の説明を表示しています。
Integracao completa com Amazon Alexa para criar skills de voz inteligentes, transformar Alexa em assistente com Claude como cerebro (projeto Auri) e integrar com AWS ecosystem (Lambda, DynamoDB, Polly, Transcribe, Lex, Smart Home).
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Build multi-step AI content creation pipelines combining image, video, audio, and text. Workflow examples: generate image -> animate -> add voiceover -> merge with music. Tools: FLUX, Veo, Kokoro TTS, OmniHuman, media merger, upscaling. Use for: YouTube videos, social media content, market...
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Create AI marketing videos for ads, promos, product launches, and brand content. Models: Veo, Seedance, Wan, FLUX for visuals, Kokoro for voiceover. Types: product demos, testimonials, explainers, social ads, brand videos. Use for: Facebook ads, YouTube ads, product launches, brand awarene...
日本語の概要は準備中です。原文の説明を表示しています。
AI-powered presentation generation via the 2slides API — create slides from text, match a reference image style, summarize documents into decks, add AI voice narration, and export pages/audio. Use for any "make slides", "create a deck", or "slides from this document" request.
日本語の概要は準備中です。原文の説明を表示しています。
Verify Stripe subscription billing cycles using a test clock. Use when you need to simulate time passing to trigger subscription renewals, recurring invoices, or to confirm that the next billing date generates the expected charge in Stripe test mode.
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Plan and execute authorized vishing (voice phishing) pretext calls to assess employee susceptibility to social engineering and evaluate security awareness controls.
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Use when writing blog posts or documentation markdown files - provides writing style guide (active voice, present tense), content structure patterns, and MDC component usage. Overrides brevity rules for proper grammar. Use nuxt-content for MDC syntax, nuxt-ui for component props.
日本語の概要は準備中です。原文の説明を表示しています。
Given an existing Style, generate a human-readable brand guidelines document covering colors, typography, voice, do/don't, imagery rules, and usage examples. Use when the user asks for a brand book, brand guide, or design system document.
日本語の概要は準備中です。原文の説明を表示しています。
Knowledge base from the FAA Human Factors Design Standard (HF-STD-001B, 2016) — the FAA's consolidated human-factors / human-systems-integration design criteria for systems it manages, operates, or maintains. Use for requirement-level design rules on: general human-factors design principles; automation and function allocation; designing equipment for maintenance; displays, controls, and visual indicators; alarms, audio, and voice communications; the computer-human interface (information presentation, coding, interaction styles, windows, dialogue); keyboards, input devices, and workstation/workplace ergonomics; system security, personnel safety, environment, anthropometry, and user documentation; plus intended-use and tailoring guidance. It is a quantified, source-attributed synthesis (heavily citing MIL-STD-1472G, MIL-HDBK-759C, DOD-HFDG-ATCCS, NUREG-0700, NASA-STD-3000, ANSI, OSHA, ISO 9241). Complements nasa-hsi as a parallel HSI tradition from the civil-aviation domain. Scope limits: it is design criteria, NOT an HSI lifecycle/process model (use nasa-hsi, nasa-npr-7123, or dau-se-guidebook for process); it does NOT reproduce the third-party standards it cites; it is FAA-acquisition-oriented (ATC, towers, TRACONs, airway facilities), not a general consumer-UX guide; and it is thin on modern touchscreen/mobile, web, and AI-driven interface patterns and on quantitative human-reliability analysis.
日本語の概要は準備中です。原文の説明を表示しています。