「voice」の検索結果

Builds a personal voice profile from roughly 90 days of the user's own sent messages and meeting speech, then drafts emails and documents that match how the user actually writes, returning the profile and every draft as Markdown for the user to keep, paste or send themselves. Use when the user asks to "write this like me", "match my voice", "draft this in my tone", "build my voice profile" or "refresh my voice profile". Do not use for an announcement in the organisation's voice, use announcement-drafter instead, nor for a weekly status email, use weekly-status-update-writer instead. Drafts for human review; never approves, authorises or signs off.

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。

Reads an accounts payable exception list (mismatches, possible duplicates, missing or exhausted purchase orders, missing receipts, vendor or bank detail differences) with any invoice, purchase order and receipt data supplied, and returns a DRAFT action sheet: per line, the exception as stated, the facts as read, the difference where both sides exist, one proposed next action for the accounts payable clerk to perform, who or what it needs, and a draft query, with UNKNOWN wherever the data is silent. Use when the user asks to "review these invoice exceptions", "work through the AP exception queue", "what should I do with these blocked invoices", "propose next steps for the three-way match failures" or "sort out the duplicate and missing PO invoices". Do not use for a purchase order log screened for anomalies, use purchase-order-anomaly-review instead; for an expense claim against policy, use expense-policy-precheck. Drafts for human review; never approves, authorises or signs off.

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。

Use when the user asks to "codify how our founder sounds", "build a founder voice dossier", or "set our content pillars"; runs an 80%-extraction interview over the user's OWN posts, emails, and decks (never competitor scraping, never an invented persona) and produces the versioned voice record — a per-platform register map (incl. 小红书/微信公众号), banned phrases, per-context disclosure lines (the ECHO C2 upstream), a few-shot bank built exclusively from own posts, and 3-5 content pillars with Estimated %-allocations — submitted via memory/events/channels.ndjson for channel-registry to store as voice-dossier.md, the record every Craft-phase skill reads first. Not for the brand-level voice canon — use brand-language-codifier; not for audience/persona research — use audience-mapper. 声音档案/品牌语气/创始人语气/内容支柱/披露声明

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。

Check invoices and receipts line by line against your offers and list what matches, what differs and what has no offer. Nothing is paid or sent. Use for "check my invoices", "match invoices to offers", "does this invoice match the quote".

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。

Organize, categorize, track, and manage invoices systematically with automated extraction of invoice data, payment tracking, and financial organization. Use when processing invoice uploads, extracting invoice details (date, amount, vendor), categorizing expenses, tracking payment status, organizing receipts, generating financial reports, or building accounting and bookkeeping systems.

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。

Build a client invoice — "make an invoice for", "create an invoice", "bill this client for". Parses plain text into line items, computes subtotal, tax and total with the math sanity-checked.

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。

High-quality voice synthesis with 18 personas, 32 languages, sound effects, batch processing, and voice design using ElevenLabs API.

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。

Choose or design a speaking voice when the user asks for a new, different, custom, invented, or generated voice, or restore the voice used immediately before the current one.

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。

Build voice AI agents with ElevenLabs. Use when creating voice assistants, customer service bots, interactive voice characters, or any real-time voice conversation experience.

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。

Triage GitHub issues, review contributor pull requests, diagnose CI, and prepare explicitly requested releases for VoiceStudio's Electron desktop app and Python backend. Use for repository maintenance work, not ordinary VoiceStudio audio generation.

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。

Detect AI-generated deepfake audio used in voice phishing (vishing) by extracting spectral features (MFCC, spectral centroid, spectral contrast, zero-crossing rate) and classifying samples with machine learning models, supporting batch audio analysis, confidence scoring, and forensic reporting. Use for deepfake voice detection, vishing investigations, AI-generated speech analysis, voice cloning detection, or audio authenticity verification.

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。

Create SEO-optimized marketing content with consistent brand voice. Includes brand voice analyzer, SEO optimizer, content frameworks, and social media templates. Use when writing blog posts, creating social media content, analyzing brand voice, optimizing SEO, planning content calendars, or when user mentions content creation, brand voice, SEO optimization, social media marketing, or content strategy.

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。

Drafts overdue-invoice reminder emails from the ledger (MYOB, NetSuite, QuickBooks, Xero, or Zoho Books) plus PayPal, Stripe, and Airwallex data, matched to each customer's payment history and tone (gentle for good customers, firm for repeat late payers). Sends via PayPal with owner approval; everything else queues as a mail draft, with the Airwallex hosted pay link included where one exists. Use when the user asks "who owes me money," mentions overdue invoices, or wants to follow up on unpaid invoices.

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。

This skill generates, creates, or builds brand voice guidelines from source materials. It should be used when the user asks to "generate brand guidelines", "create a style guide", "extract brand voice", "create guidelines from calls", "consolidate brand materials", "analyze my sales calls for brand voice", "build a brand playbook from documents", "synthesize a voice and tone guide", or uploads brand documents, transcripts, or meeting recordings for brand analysis. Also triggers when the user has a discovery report and wants to convert it into actionable guidelines.

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。

Draft Gmail in the user's own voice from the voice profile built by email-voice-profile. Drafts only; the user reviews and sends.

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。

让 Agent 变成能语音对话的机器人：语音文件转文字（支持微信 silk 格式）+ 多音色人格回复（Edge TTS 免费中文音色），全本地零 API 成本。Voice persona chat: transcribe voice messages (incl. WeChat silk) and reply in persona voices.

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。

Use when the user asks to "measure how our narrative is landing", "track echo rate against our canon lexicon", or "check how AI answer engines describe our brand"; produces a resonance report — echo rate (overlap of market language with the narrative-registry canon lexicon, method declared), AI-answer perception via tavily.py --answer (proxy-labeled), share-of-voice on a locked competitor panel (reusing share-of-voice-tracker), and resonance signals from bluesky.py / gdelt.py / pageviews.py — every number labeled Measured / proxy / User-provided, feeding the TALE E dimension and the upstream of the E1 evidence-integrity veto. Not for rebuilding share-of-voice machinery — use share-of-voice-tracker; not for own-site GA4/GSC analytics — use performance-monitor; not for scoring TALE profile result — use narrative-quality-auditor; not for adjudicating claims — use offer-claims-registry. 回声率/AI回答感知/份额之声/共鸣信号

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。

Establish durable brand and voice context for cross-skill consumption. Generates BRAND.md (audience, positioning, do/don't editorial rules, taboo phrases, competitor differentiation) and VOICE.md (existing persona JSON re-expressed as readable prose), both written to the project root. When present, the blog orchestrator auto-loads these files for write, rewrite, brief, outline, calendar, and strategy workflows. Pairs with blog-persona, which manages the structured persona JSON. Use when user says "blog brand", "create brand context", "brand voice doc", "BRAND.md", "VOICE.md", "establish editorial brand", "brand guidelines for blog".

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。

Capture a user's real writing voice from 5-20 prior samples, store a local voice.yaml fingerprint, and enforce it on newsjack drafts so AI tells disappear. Measures voice with named stylometry lenses (Burrows's Delta function-word vector, MATTR lexical diversity, sentence-length burstiness, Biber Dimension-1 register, opener-POS profile, punctuation rates) and gates drafts against the fingerprint as bands, not vibes.

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。

Draft voice-tuned X (Twitter) post variants from a free-form brief. Reads a personal voice guide (generated via generate-voice-guide), produces 2–5 variants with distinct framings (simple-howto, problem-first, hype, mechanism-breakdown, etc.), and self-checks against the voice guide's banned phrases before returning.

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。

Draft voice-tuned LinkedIn post variants from a free-form brief. Reads a personal voice guide (generated via generate-voice-guide), produces 2–5 variants with distinct framings, applies LinkedIn-specific defaults (arrow bullets, "why this matters" beat, 150–500 words), and self-checks against the voice guide's banned phrases before returning.

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。

Analyze a company's published content to extract their brand voice, writing style, and tone guidelines. Reads 10-20 of their best content pieces and produces a brand voice profile covering tone, vocabulary level, sentence structure, formatting patterns, CTAs, and target persona. Useful before writing outreach, content, or campaigns that should match a client's existing 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。

Assemble a cosmic-mythology-voiceover reel from a config — one spoken voiceover carries the whole narrative while N curated stills in one chosen look are weighted beat-synced across the delivered VO duration (cut_dur = VO_dur times weight over the weight sum, so emotional beats hold longer), Ken-Burns-zoomed per still (scale 2x, center crop, zoompan, fade-in first and fade-out last), ffmpeg-concatenated, the VO composited under the picture (libx264 crf18 plus aac), the ONE on-screen hook line faded on over the open with a drawtext alpha window, and Whisper/VEED captions burned along the bottom — never in-world text on a still. This is the FREE deterministic assembly stage (weighted sequence plus Ken-Burns plus concat plus VO composite plus hook overlay plus caption burn); the VO and the stills come from create-vo-elevenlabs and create-image-fal. Use for the cosmic-mythology-voiceover format.

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。

Builds voice and chat AI agents with LiveKit Agents on LiveKit Cloud or a self-hosted server. Use when the user asks to "build a voice agent", "create a LiveKit agent", "add voice AI to my app", "implement handoffs", "structure an agent workflow", "my agent is slow / too chatty", "it says it booked but nothing was saved", "make it confirm before committing", "it keeps re-asking things the caller already said", or is writing code against the LiveKit Agents SDK. Covers architecture: designing for latency, keeping context small, splitting a monolithic agent into handoffs and tasks, and designing for voice. Also covers keeping the model in charge of meaning while code owns state, approvals, and effects. For API specifics use reading-livekit-docs. To check behavior use debugging-livekit-agents and testing-livekit-agents.

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。