「script」の検索結果

Search, order, and manage phone numbers by location, features, and coverage.

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 an agent must join, observe, react in, transcribe, summarize, or follow up on a Zoom, Google Meet, Microsoft Teams, or Webex meeting with Telnyx Meeting Bot. Handles vague requests, request-specific live polling, name/phrase and semantic triggers, explicitly authorized speak/chat actions, recovery, and all implemented transcript artifact types.

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。

Send and receive SMS/MMS, handle opt-outs and delivery webhooks. Use for notifications, 2FA, or messaging apps.

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 voice assistants with custom instructions, knowledge bases, and tool integrations.

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。

10DLC brand and campaign registration for US A2P messaging compliance. Assign phone numbers to campaigns.

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 sales battlecards with feature comparisons, objection handling scripts, positioning statements, and win themes for competitive deal scenarios. Use when the user requests competitive battlecard creation or provides relevant inputs for this workflow.

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。

Automate repetitive tasks and workflows using scripting, file watchers, scheduled jobs, CI triggers, and API polling to eliminate manual toil. Use when the user requests task automation or provides relevant inputs for this workflow.

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。

Audit agent skills, plugins, prompts, manifests, scripts, dependencies, and bundled assets for provenance, prompt-injection, permission, execution, exfiltration, persistence, and update risk. Use when evaluating a third-party skill before installing, enabling, updating, publishing, or distributing it; reviewing an untrusted SKILL.md, agent configuration, MCP integration, archive, or repository; comparing a package with a known-good version; or investigating unexpected tool, network, credential, or filesystem 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。

Design, implement, and validate reproducible machine-learning pipelines spanning data preparation, training, evaluation, registry, and deployment gates. Use when the user requests an ML pipeline, needs to turn model scripts into an orchestrated workflow, or provides pipeline components that must be connected safely.

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。

Design and validate model-facing tool definitions with clear names, action-oriented descriptions, bounded JSON Schema parameters, explicit side effects, safe defaults, idempotency, errors, and realistic tests. Use when creating function-calling tools, MCP tools, agent actions, structured tool inputs, or when a model selects the wrong tool, invents arguments, or causes unsafe side effects.

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。

Think and work like an expert Geneticist. Use when a task calls for Geneticist judgment. Reasons from particulate inheritance, segregation, recombination, allele frequency, and genotype-phenotype evidence through ACMG/AMP-ClinGen classification, gnomAD/ClinVar/OMIM, HPO phenotyping, and PLINK/GATK/VEP QC while treating sample swaps, cryptic relatedness, population stratification, LD tagging, phenocopies, winner's curse, and build/transcript mismatch as first-class failure modes.

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。

Think and work like an expert Exercise Physiologist. Use when a task calls for Exercise Physiologist judgment. Reason from the Fick principle and verified gas exchange: separate VO2max, VT1/RCP, MLSS, and lactate kinetics before metabolic carts, biopsy, MRS, or periodization prescriptions.

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。

Run a skill's evals and report results. Use when the user wants to evaluate a skill, run evals, benchmark a skill, validate triggers, optimize a description, or grade skill outputs.

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。

当需要为 AI 定义工具接口、设计调用规范、实现工具发现与编排机制时调用此 skill。典型场景包括：设计 AI agent 的工具集、定义 JSON Schema/XML/TypeScript 格式的工具描述、实现工具权限控制与并行调度、设计子代理委托架构。 不适用于：定义 AI 身份（persona-design）、安全规则（safety-guardrails）、记忆存储（memory-system）。 关键 trigger 信号：AI 需要调用外部 API 或服务、工具数量超过 10 个需要发现机制、需要区分工具权限层级、需要子代理并行执行、工具调用涉及敏感操作需要审批。

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 production OpenAI Realtime voice agents and low-latency spoken interactions with live audio sessions, WebRTC or WebSocket transport, voice activity detection, tool/function calling, prompt design, logging, consent, privacy, safety, latency, and cost controls. Use for speech-to-speech agents and live voice UX; do not use for separate request-based transcription, text-to-speech, or offline audio generation work.

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。

Produce, direct, integrate, and quality-control ElevenLabs text-to-speech for narration, character performance, multilingual media, long-form voiceover, and streamed or batch AI-content audio. Use when selecting ElevenLabs models or voices; preparing spoken text; controlling pronunciation, pacing, emotion, and code-switching; using TTS APIs; cloning or designing a voice with consent; repairing artifacts; mastering deliverables; or evaluating generated speech. Excludes music, sound-effect generation, conversational-agent design, and general speech recognition except transcription used to verify TTS.

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 production realtime voice agents with Hume's Empathic Voice Interface (EVI): speech-to-speech sessions, empathic/prosodic response design, EVI 3 versus EVI 4-mini selection, WebSocket and SDK integration, tools/function calling, interruption/barge-in, turn-taking, transcripts/audio artifacts, pricing/limits, privacy, safety, consent, and QA.

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 Amazon Transcribe for AWS-based speech-to-text production: batch S3 transcription, real-time streaming, captions/subtitles, diarization, channel identification, custom vocabularies, vocabulary filters, language identification, PII/PHI handling, toxicity detection, Call Analytics, Medical, and secure S3/IAM/KMS workflows.

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 this skill when a media-production agent needs Google Cloud speech and voice services for transcription, captions/subtitles, long-form audio analysis, live caption planning, Text-to-Speech narration, Chirp 3 / Gemini-TTS voice selection, consented custom voice workflows, dubbing/localization planning, pricing/quotas/region checks, or speech-related safety and data-governance decisions.

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。

Produce, edit, extend, and govern short videos with xAI's direct Grok Imagine Video API. Use for text-to-video, image-to-video, multi-reference video, natural-language video edits, video continuation, exact media-cost approval, asynchronous request recovery, Files/Batch integration, moderation review, and API privacy or residency decisions. Covers `grok-imagine-video` and image-only `grok-imagine-video-1.5`; excludes Grok consumer subscriptions, Grok on X, still-image generation, voice APIs, and third-party gateways.

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 and evaluate low-latency spoken, multimodal, and translation experiences with Google Gemini Live API and Gemini Enterprise Agent Platform Live API. Use when a media-production or voice-agent workflow needs real-time audio input/output, barge-in, voice configuration, live transcription, live translation, tool/function calling during a spoken session, WebSocket session design, latency QA, quotas/cost review, or Google/Vertex data-governance tradeoffs.

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。

Operate AudioShake's cloud source-separation service (developer.audioshake.ai) to split a recording into stems. Use when a task involves isolating vocals, drums, bass, guitar, piano, keys, strings, or winds from music; separating dialogue / music / effects (DME) for film-TV post-production, localization, and dubbing; splitting a mixed recording into one stem per speaker; lyric transcription or word-level alignment; music detection/identification; or speech denoise/dereverb. Covers the Tasks API job lifecycle (assets, targets, formats, polling vs webhooks, credits, limits), choosing which stem targets a production actually needs, reviewing separated stems for bleed / artifacts / transient smearing / phase problems and repairing them, the rights and consent questions raised by separating copyrighted or third-party recordings, and the decision boundary for when a local open model such as Demucs is the better route than the API. Not for generating or synthesizing new audio, mixing, or mastering.

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 an agent must make TwelveLabs do real video-understanding work: indexing footage, semantic/visual search across an archive, generating descriptions, summaries, chapters, highlights, and tags from video, producing multimodal embeddings, or wiring TwelveLabs into a media-production pipeline (NLE panels, logging, compliance review, metadata). Covers the current model families (Marengo for search/embeddings, Pegasus for video-to-text analysis), the v1.3 Video Understanding API (indexes, assets, tasks, search, analyze, embed), prompt construction for analysis, capability and format limits, pricing/quota math, output quality review (hallucination and timestamp accuracy), and privacy/rights obligations when footage shows real people. Not for generating or editing video pixels — this is analysis and retrieval.

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 for Deepgram speech and voice production workflows: speech-to-text transcription, live captions, diarization, audio intelligence, Aura text-to-speech, Flux and Voice Agent live audio, model selection, cost/limits/privacy checks, artifact custody, and production QA.

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。