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Plan, produce, adapt, finish, deliver, and improve platform-ready short vertical social videos from a brief, script, transcript, or source media. Use for TikTok videos, Instagram or Facebook Reels, YouTube Shorts, LinkedIn vertical clips, and cross-platform social cutdowns when the work requires audience and objective definition, an honest hook and promise, short-form beat or shot planning, UI-safe layout, captions and accessibility, speech/music/SFX mixing, platform-specific exports, rights and AI or sponsorship disclosure, analytics-led retention iteration, or final QA and repair. Do not use as a provider-specific image, video, voice, or music generation guide.

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Provider-independent captions and media accessibility direction for AI agents producing or finishing generated videos, ads, social clips, explainers, avatar videos, documentaries, podcasts/video recuts, training media, and localized content. Use when planning, authoring, reviewing, localizing, burning in, exporting, or QAing captions, subtitles, SDH, transcripts, audio description, flashing/motion safety, caption readability, or accessible media handoff files.

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 audio-first podcast episodes with generative tools — design the show and episode format (interview, narrative, news brief, two-host conversational), write scripts for the ear, decide between fully-synthetic and hybrid (recorded human + synthetic) production and meet the disclosure duty each triggers, cast and direct multi-voice TTS for consistency and chemistry, build episode structure (cold open, intro/outro, segments, ad slots), assemble and edit, clear music and SFX rights, hit podcast loudness and delivery standards, ship metadata/chapters/transcripts through RSS, and pass platform AI-content policy and QA before publishing. Use this skill whenever the deliverable is a podcast episode or a podcast show bible, or when an agent must make production, rights, disclosure, or delivery decisions for spoken-word audio. Not for music tracks, single-voice notification prompts, or video where picture leads (route audio-for-video to a video skill).

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Provider-independent dialogue editing and ADR direction for AI agents producing generated videos, films, ads, avatar clips, explainers, localization/dubbing, podcasts, recuts, and social content. Use for dialogue prep, repair, room tone, take comping, sync, ADR cueing, dubbing direction, pronunciation, de-essing, plosives, mouth clicks, voice continuity, synthetic voice consent boundaries, captions/transcripts handoff, mix handoff, loudness, intelligibility, accessibility, and QA.

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Detect transcription factor binding footprints in ATAC-seq using TOBIAS, HINT-ATAC, Wellington, or scprinter. Use when identifying bound TF sites within accessible regions, correcting Tn5 insertion bias before footprinting, choosing between cleavage-based and aggregate-based footprinters, or comparing differential TF activity between conditions.

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Build tissue and condition-specific metabolic models using GIMME, iMAT, and INIT algorithms with expression data constraints. Create models that reflect cell-type specific metabolism. Use when building tissue-specific metabolic models or integrating transcriptomics with FBA.

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Bulk-query Ensembl BioMart (and other BioMart instances) for cross-database ID mapping, gene/transcript/exon coordinates, and ortholog tables. Use when batch-converting Ensembl IDs to other namespaces (HGNC, RefSeq, UniProt, Entrez), pulling gene coordinate tables for thousands of genes, building ortholog wide-tables across species, or replacing slow Ensembl REST loops with one-shot bulk export. Encodes BioMart's XML query format, R biomaRt vs Python pybiomart trade-off, mart-vs-dataset hierarchy, and the URL endpoint that's BioMart-specific (separate from rest.ensembl.org).

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Detects allele-specific transcription factor or histone modification binding from heterozygous-variant ChIP-seq using WASP (reference-bias filter; mandatory upstream), RASQUAL (joint QTL + bias-corrected testing), BaalChIP (Bayesian beta-binomial with copy-number-aware overdispersion), and AlleleSeq (personalized diploid genome). Handles imprinted-locus awareness, X-inactivation artifacts, cancer copy-number imbalance, and integration with downstream caQTL / bQTL mapping. Use when identifying variants with allelic effects on TF binding, fine-mapping causal regulatory variants, validating deep-learning variant predictions, or characterizing cis-acting regulatory effects.

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Workflow for gene and transcript quantification from RNA-seq reads using alignment-based or alignment-free tools.

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。

Bulk transcriptomics differential expression with count-aware modeling, design validation, contrast handling, thresholded exports, and publication-ready DE figures.

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。

把凌亂的文件（會議逐字稿、多場會議混在一起的檔案、實驗／數據報告、論文、財報）變成可直接上台的設計感簡報的工作流。 Use this skill whenever the user wants to turn a document, meeting notes, transcript, report, spreadsheet, or raw data into slides / a presentation / a deck — 包括他們說「做成簡報」「整理成投影片」「幫我做一份簡報」「把這份報告變簡報」 「turn this into a presentation / slides / a deck」，即使沒有明說步驟。 也適用於「只有主題沒有素材」（如「幫我做一份 AI 發展趨勢的簡報」）——會先做主題研究再進入流程。 也適用於跨 session 銜接（「繼續做 xxx 的簡報」「接上次」）——會定位進度再銜接。 它會先清點內容並把敏感資料（姓名、薪資、競業條款、個資）攔進備援區、停下來等使用者確認範圍， 再把「有設計感」翻成具體色碼與版型規格、生成單一 HTML 簡報， 並對任何圖表用原始數據重算統計值、抓出原文寫錯的數字。 Also use it whenever the user needs figures or charts from a report recomputed from the source data rather than trusted blindly. 也支援 Keynote Magic Move 式的 Morph Transition 轉場（使用者說「Magic Move」「Morph」「物件飛過去的轉場」時）。

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Redpanda's Agentic Data Plane: governance infrastructure for building, running, and governing AI agents and MCP servers, plus a proxying AI Gateway for LLM providers, operated via `rpk ai` and the ADP API. Use when creating or managing AI agents (managed or self-managed) via `rpk ai agent` or `AgentRegistryService`; configuring MCP servers (remote or managed catalog, code mode, auth); setting up LLM providers or querying models via `rpk ai llm`/`rpk ai model` or the AI Gateway proxy; or configuring budgets, guardrails, or Cedar access-control policies through the governance APIs. Also covers reading agent transcripts and spending insights, and wiring OAuth clients or providers to the aigw Authorization Server. For the separate rpk cloud mcp control-plane MCP server, see `/redpanda:rpk-cloud`.

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Create cross-platform agent skills from workflow descriptions. Activates when users ask to create an agent, automate a repetitive workflow, create a custom skill, or need advanced agent creation. Triggers on phrases like create agent for, automate workflow, create skill for, every day I have to, daily I need to, turn process into agent, need to automate, create a cross-platform skill, validate this skill, export this skill, migrate this skill, audit this skill, is this skill safe, vet a skill before installing, what does this skill access. Supports single skills, multi-agent suites, transcript processing, template-based creation, interactive configuration, cross-platform export, spec validation, and security auditing of third-party skills before install.

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Agent Media OS, the single skill for every media need in a HyperFrames project. Resolve BGM, SFX, image, icon, brand logo, voice, color grade, or LUT into a frozen local file or paste-ready block + ledger record (one verb, `resolve`); generate via TTS / music / image models when the catalog misses; produce voiceover, transcription, captions, and background removal through one shared audio engine; operate on media (cut / reframe / transform); and reuse assets across projects. Keeps search noise on disk, hands the agent one path or block. Use for any audio, image, icon, logo, voiceover, caption, color-grading, or media-asset need.

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Internal speech module for /codeck. Reads deck content, asks about style and duration only when missing, generates a verbatim speech transcript with stage directions. Outputs $DECK_DIR/speech.md.

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Use when changing REPL clear/reset/resume/surface behavior (onClearTerminal, transcriptSeq remount, Ink Static paths, Ctrl+O/Ctrl+E transitions). Enforces single-owner reset transaction and prevents black-screen/flicker/duplicate-row regressions.

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Implement or refactor Formax tool transcript UI using the Tool UI Blocks (C-lite) pattern (ToolUiBlocks renderer + blocks presenters) to avoid touching many tool presenter files; use when adjusting ⏺/⎿ spacing, indent rules, or migrating additional tools to blocks presenters with targeted Ink/Vitest tests and Codex review before commit.

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AI SDK for Python (the `ai` package). Use for Python model calls (LLMs, image, video, speech, embedding, transcription, reranking, or evaluation), agents, model interaction tests, tool calling, subagents, approvals, durable execution, telemetry, AI SDK UI backends, and custom providers.

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Send an end-to-end-encrypted message to a peer, autonomously. Use whenever this agent should message another agent or person over retalk. Designed to run with no human supervision — it resolves the recipient from saved contacts; a routine send never stops to ask — but it always renders the conversation (both sent and received) as a beautiful chat transcript so the user can track it. (Recipient/relay are set up once by the init skill.)

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Read incoming retalk messages from this session's user's DESIGNATED sender(s) — one-shot, or as a background --follow reader that surfaces new messages in the session as they arrive (on your next turn). agent-talk only ever receives from specific saved peers, never the whole mailbox (safety). `<user>` is this session's user directory (absolute path; from init). Always renders the conversation (sent + received) as a beautiful chat transcript so the user can track it. Use to check mail or stay reachable.

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Use when reviewing, auditing, scoring, or improving a real or synthetic MATLAB AI tutor transcript, tutoring prompt, generated lesson, exercise, feedback sequence, or skill behavior for MATLAB accuracy, active learning, assignment guardrails, feedback quality, debugging support, transfer prompts, and instructor-facing quality recommendations.

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 mining coding-agent session history, archived transcripts, memories, or repeated local work to discover recurring workflows that should become new Agent Skills.

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在 rove 仓库内跑 auto-motion——把 transcription.srt 拆成多段 MG 动画镜头并拼接成竖屏视频(storyboard 分镜 + theme.md 全片主题 + 逐镜头 claude -p 子进程 + ffmpeg 拼接)。本 skill 是薄 wrapper:解析 auto-motion 模板根,继承 rove 品牌 theme,执行逻辑以 auto-motion 仓库的 canonical SKILL.md 为准。当用户说"跑 auto-motion"、"把这个字幕稿/口播稿做成视频"、"给 rove 做一条 MG 宣传片"时使用。

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Fetch Otter.ai transcript data. Sub-skill used by cache-notes and fill-participants when Notes: contains an Otter URL.

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。