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Visualises RNA-modification data with transcript-feature metagene plots (Guitar GuitarPlot with 5'UTR / CDS / 3'UTR scaling; MetaPlotR; deepTools `computeMatrix scale-regions`), peak-centred heatmaps (ComplexHeatmap; deepTools plotHeatmap), IP-vs-input paired browser tracks (bigWig of log2 IP/input via deepTools `bamCompare`; ggcoverage; pyGenomeTracks; Gviz; IGV / UCSC track hubs), DRACH sequence-logo plots (ggseqlogo; MEME), 5'UTR / CDS / 3'UTR stacked-bar feature-distribution summaries, and volcano / MA plots for differential modification. Establishes stop-codon enrichment in the metagene plot as the biological QC anchor for any MeRIP dataset (Dominissini 2012 *Nature* 485:201; Meyer 2012 *Cell* 149:1635 — concurrent founding papers from different labs both showed this independently). Use when producing the canonical metagene plot with stop-codon enrichment as a QC anchor, building paired IP/input genome-browser tracks at single-locus resolution, plotting peak-centred heatmaps clustered by condition, summarising peak distribution across transcript features for figure 1, generating DRACH motif logos as sanity checks on the peak set, rendering volcano plots of differential m6A, or reproducing the Dominissini 2012 / Meyer 2012 stop-codon enrichment plot.

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Azure AI Transcription SDK for Python. Use for real-time and batch speech-to-text transcription with timestamps and diarization.

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OpenAI's general-purpose speech recognition model. Supports 99 languages, transcription, translation to English, and language identification. Six model sizes from tiny (39M params) to large (1550M params). Use for speech-to-text, podcast transcription, or multilingual audio processing. Best for robust, multilingual ASR.

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Create a verbatim transcript for a YouTube URL using Google Gemini (speaker labels, paragraph breaks; no time codes). Use when the user asks to transcribe a YouTube video or wants a clean transcript (no timestamps).

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通过逐段讨论，将笔记、零散文字或转录稿组织成便于读者理解的文章，比较开篇方案与段落作用，并把商定的内容保存到独立文件中。

• 把零散笔记整理成文章
• 根据转录稿组织文章
• 动笔前比较开篇角度

将笔记、访谈转录和研究资料整理为博客文章、指南、教程或通讯，参照既有文风和品牌要求安排结构，并用所提供的材料支撑事实性主张。

• 将笔记或访谈转录整理成文章
• 按品牌既有文风撰写文章
• 编写实用指南与教程

将需要记忆的事实转为问答卡片，按回答情况安排复习间隔。支持从YouTube字幕生成测验、按领域管理卡片集合、导入导出CSV，并在本地保存卡片。

• 将需要记忆的事实制成卡片
• 学习已到复习日期的卡片
• 通过测验检查对YouTube视频的理解

获取YouTube视频字幕，并整理为摘要、带时间标记的章节、分章摘要、X系列帖子或博客文章，也可提取带时间标记的引用。

• 快速了解长视频的要点
• 制作带时间标记的章节及分章摘要
• 将视频整理为X系列帖子或博客文章

将对话文本或截图转换为带动态气泡的视频素材，可设置应用风格外观、头像、昵称和设备边框，并输出透明背景视频或可继续编辑的项目文件。

• 在短视频中加入对话
• 在产品演示中叠加消息
• 通过聊天重现故事

Turn agent activity and transcript token counts into a cost report organized around completed outcomes. Separate estimates from measured spending, examine waste and rework, and export readable HTML with supporting JSON, CSV, and evidence.

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• Reviewing weekly agent spending and completed work
• Comparing costs per completed outcome
• Investigating the cost of loops and rework

Convert articles, reports, or documentation into an English or Chinese podcast with two conversational hosts. Create a dialogue script, generate speech, and combine it into an MP3 with a readable transcript.

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• Turning an article into a conversational podcast
• Adapting a report for listening
• Explaining technical documentation through dialogue

Search local session histories across Codex, Claude Code, OpenCode, and other coding agents. Find earlier requests, inspect transcripts and child sessions, and reconstruct past work using recorded evidence, with filters for dates, projects, platforms, and models.

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• Finding work done a few days ago
• Checking whether a migration was already completed
• Reviewing tasks delegated to child agents

Recover context from local coding-agent transcripts and produce a checkpoint covering the objective, completed work, blockers, and next step. Explicit import requests support read-only recovery, with continuation governed by the current workspace rules and the user's request.

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• Recover context using a session ID
• Summarize unfinished work from local logs
• Review JSONL exports or Markdown handoffs

Add synchronized subtitles and text effects to an existing single-speaker video. Choose from 35 visual styles, including readable lower captions and words placed behind the person, with local transcription, subject cutout, previews, and final video compositing.

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• Add readable subtitles to an explainer video
• Place an emphasized word behind the speaker
• Create themed caption effects for social videos

Turn interviews, surveys, support conversations, and public reviews into evidence-based customer insights. Identify recurring problems, buying triggers, and customer language, then build research reports, quote collections, or personas and plan interviews or surveys to fill gaps.

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• Analyze customer interview transcripts
• Find recurring themes in reviews and support tickets
• Build customer personas from research evidence

Predict spatial gene expression from H&E-stained tissue images using DeepSpot-M. Query a released panel of about 19,000 genes and combine predictions from small image tiles into slide-wide maps for research analysis.

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• Mapping predicted marker-gene expression across a tumor section
• Predicting expression across slides without matching gene-expression assays
• Adding predicted expression to a histology image analysis pipeline

Build real-time voice assistants in JavaScript or TypeScript using Azure AI Voice Live. Covers two-way audio streaming, authentication, speech turn detection, transcription events, and calling application functions during conversations in Node.js or browsers.

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• Build a voice assistant in Node.js
• Stream microphone audio from a browser
• Configure speech boundaries and transcription events

Helps build Python workflows that extract information from documents, images, audio, and video using Azure AI Content Understanding. Covers document text, timed transcripts, video frames, and invoice fields for search and automated processing.

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• Preparing document content for AI search
• Transcribing audio with timestamps
• Extracting transcripts and key frames from video

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

Build real-time voice applications in Python with Azure AI Voice Live. Covers two-way audio streaming, transcripts, conversation history, and handling interruptions, with examples for authentication and configuring when the assistant responds.

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• Build a voice assistant in Python
• Display transcripts during voice conversations
• Stop an audio response when the user interrupts

Build AI agents that make phone calls and send or receive SMS through the AgentPhone API. Manage phone numbers, configure voice agents and event notifications, and inspect call transcripts and account usage.

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• Create an AI voice agent with a phone number
• Send and receive SMS through AgentPhone
• Review call transcripts and account usage

Analyze Claude Code session transcripts and create an interactive HTML usage report. Explore token consumption, cache performance, subagents, skills, and costly prompts, with findings and improvement suggestions tied to the actual usage data.

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• Reviewing token usage over a chosen period
• Comparing consumption across projects and skills
• Investigating cache performance and breaks

Manually sync OpenClaw chat transcripts to OpenViking and search stored memories using explicit commands. Receive a sync summary or relevant memory entries while leaving the OpenClaw contextEngine slot available for its existing use.

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• Manually sync recorded chat transcripts
• Find stored memories about a specific topic
• Check the summary of a manual sync

Build a connected Markdown Wiki from documents, notes, transcripts, research, and code. Organize knowledge by subject, attach evidence to claims, maintain a navigation index, and integrate new material into existing pages while preserving disagreements and context.

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• Organize scattered documents and notes into a knowledge Wiki
• Add new evidence to an existing Wiki
• Document concepts and relationships found in code