動画編集、サムネイル、マンガ、音声（3,145 件）
概要と使いどころ
Use Agent Media when an agent needs to create captioned vertical UGC videos, narrated b-roll overlays, reusable characters, images, and voice through a hosted MCP server and companion skills.
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。
Transcribes one explicitly authorized Brazilian Portuguese or Spanish audio or video file through the metered BRAINIALL API, then creates speaker-labelled JSON, SRT, and WebVTT with word timestamps and no automatic retry.
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。
Manage and tag music libraries with beets, the Python-based CLI tool that auto-tags audio files using MusicBrainz metadata. Import, organize, deduplicate, and query your music collection with a powerful plugin system and flexible query language.
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。
An agent skill that uses BlurHash, the compact image placeholder representation algorithm by Wolt, to generate and decode tiny hash strings that represent blurred previews of images. Enables instant placeholder rendering in web and mobile applications while full images load.
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。
Generates social media graphics and OG images dynamically via Bannerbear REST API. Manages template modifications, font layers, and signed URL generation for on-the-fly image personalization.
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。
Auto-Editor is a command-line application that automatically edits video and audio by analyzing loudness, motion, and other signals to cut dead space. It exports to Premiere Pro, DaVinci Resolve, Final Cut Pro, ShotCut, and Kdenlive timelines.
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 smartcrop when an agent needs to choose a sensible crop automatically instead of center-cropping every image. The workflow scores visual saliency, returns crop coordinates for a target aspect ratio, and hands those coordinates to an image pipeline that renders the final thumbnail or social card.
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。
Summarizes audio content using AssemblyAI's LeMUR (Large Language Model for Audio Understanding) API. Chains the /v2/transcript endpoint with /lemur/v3/generate/summary for contextual audio intelligence.
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 structured intelligence from audio using the AssemblyAI API with sentiment analysis, entity detection, topic modeling, and auto-chapter generation. Uses the assemblyai Python SDK for transcript processing pipelines.
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 apko to build small OCI images from declarative package manifests when supply-chain clarity and minimal contents matter more than a conventional Dockerfile flow.
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。
Streams audio from Twilio Media Streams over WebSocket to AssemblyAI real-time transcription, extracting speaker-diarized transcripts with word-level timestamps. Triggers entity detection and sentiment analysis via AssemblyAI LeMUR on completed call segments. Results are pushed to HubSpot or Salesforce contact records via their REST APIs.
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。
Transcribes audio and generates auto-chapters with summaries using AssemblyAI's /v2/transcript endpoint with auto_chapters=true. Extracts key topics, sentiment analysis, and content safety labels via AssemblyAI SDK.
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。
Identifies audio content using Chromaprint/AcoustID fingerprinting, Shazam API recognition, and ACRCloud monitoring. Matches music, speech, and ambient audio against fingerprint databases.
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。
Integrate Audiobookshelf's self-hosted audiobook and podcast server into AI agent workflows. Agents can manage libraries, track listening progress, search metadata, and automate podcast episode downloads through the comprehensive REST 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。
audioFlux is a deep learning tool library for audio and music analysis and feature extraction, supporting dozens of time-frequency transforms and hundreds of feature combinations for classification, separation, MIR, and ASR tasks.
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。
Separates audio tracks into individual stems (vocals, drums, bass, other) using Meta's Demucs neural network model via the demucs Python package. Supports batch processing of WAV and MP3 files, outputs isolated stems in FLAC or WAV format, and integrates with FFmpeg for format conversion and loudness matching post-separation.
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。
Download a supported video URL with yt-dlp and upload the preserved file plus metadata to archive.org as a repeatable preservation job.
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。
Track approved container images and write back the matching GitOps manifest changes instead of hand-editing tags across Argo CD applications.
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。
Give Claude Code a video perception layer that extracts frames, transcribes audio, and lets Claude answer questions about local videos or YouTube URLs.
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。
Calls Adobe Firefly's text-to-image and generative fill APIs for batch asset creation. Manages Adobe IMS OAuth tokens and enforces Content Credentials (C2PA) metadata on all 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。
Inspect captured RAM images to enumerate processes, modules, handles, and suspicious in-memory behavior before escalation or evidence handoff.
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 wants to post or schedule to YouTube, a Facebook Page or Mastodon through Publora. YouTube needs a video on every post, Facebook publishes to Pages only, Mastodon caps at 500 characters. Not for the platforms that have their own skill.
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 wants to post or schedule to X (Twitter) through Publora, including threads auto-split past 280 characters, up to 4 images, or a video up to 140 seconds. X needs a paid Publora plan. Not for Threads or Bluesky (each has its own skill).
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 wants to post or schedule to a Telegram channel or group through Publora, using a bot. Covers Telegram markdown, silent delivery, link previews and forward protection. Bot API caps media captions at 1,024 characters and videos at 50 MB. Not for other platforms (each has its own skill).
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。