视频·图像·音频技能

Provider-independent governance workflow for verifying and correcting human- or model-generated video descriptions. Use for pre-caption critique and post-caption revision, aspect-by-aspect factual review, critique precision/recall/constructiveness, second-stage peer review, calibration, appeals, versioned triplets, provenance, and acceptance reporting; not for pixel/audio QA, accessibility captioning, model training, or creative shot direction.

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Provider-independent production guidance for converting observed video into precise, objective, temporally ordered language. Use for shot descriptions, searchable metadata, dataset captions, reference logs, generation-prompt handoffs, and analysis across subject, scene, motion, spatial, and camera aspects; not for deciding what to shoot, accessibility captions, creative interpretation, or provider-specific video analysis APIs.

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Provider-independent color grading and finishing direction for generated video, ads, trailers, product films, social clips, explainers, and mixed-source edits. Use when planning, directing, reviewing, or QAing color correction, shot matching, exposure, contrast, saturation, skin/product color protection, look development, LUT/reference use, SDR/HDR color management, delivery constraints, generated-media artifacts, editor/compositor handoff, and finishing QC.

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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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Generate Xiaohongshu (XHS / RedNote) cover images using GPT Image 2 / Codex image generation first, with the legacy Gemini CLI as fallback. Triggers for cover generation: "生成封面", "小红书封面", "xhs封面", "制作封面", "帮我做张图", "XHS cover", "RedNote cover". Triggers for cover editing: "修改封面", "改一下封面", "上一张图基础上", "基于这张图调整", "不要重新做", "edit this cover". Triggers for style learning: "学习这个风格", "提取风格", "我想自定义风格", "这张图的风格", "learn this style", "extract style". Always trigger this skill when user mentions 小红书/XHS/RedNote together with 封面/cover/图片, OR when user uploads a reference image and asks about creating a similar style.

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Use when user asks to synthesize speech, convert text to audio, or read text aloud. 讯飞超拟人语音合成 - 支持文本转语音、语音合成（发音人/语速/语调/音量/输出格式）。大模型语音合成技能。语音合成, 文字转语音, 超拟人, TTS.

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Use when user asks to translate videos, dub video content, or localize videos into other languages. Translate videos with AI-powered dubbing using iFlytek (Xfei) Video Translation API. Supports video language translation, voice dubbing, multilingual video localization, 视频翻译, 视频配音, 视频本地化. Features task creation, task list, task details retrieval. Ideal for content creators and localization teams.

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Use when user asks to clone a voice, train a custom voice model, or synthesize speech with a cloned voice. iFlytek Voice Clone tts(声音复刻) — train a custom voice model from audio samples and synthesize speech with the cloned voice. Supports the full workflow: get training text → create task → upload audio → submit training → poll results → synthesize with cloned voice. Pure Python stdlib, no pip dependencies.

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Use when user asks to analyze an image, describe image contents, or answer questions about a picture. iFlytek Image Understanding (图片理解) — analyze and answer questions about images using Spark Vision model. WebSocket API, pure Python stdlib, no pip dependencies.

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ifly-pdf-image-ocr skill supporting both image OCR (AI-powered LLM OCR) and PDF document recognition. Use when user asks to OCR images, extract text from images/PDFs, convert PDF to Word/Markdown, or perform any OCR tasks on images or PDFs. Supports multi-language text extraction, document layout understanding, and various output formats.

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Ultra-fast speech transcription using iFLYTEK Speed Transcription API. Transcribe audio files (WAV/PCM/MP3) up to 5 hours in ~20 seconds per hour. Supports Chinese, English, and 202+ Chinese dialects with automatic language detection. Use when user asks to transcribe audio files, convert speech to text, or mentions "speed transcription" or "极速转写".

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Review SDS-PAGE or protein purification gel images using DNA sequence, protein sequence, base-pair length, expected protein size, and lane labels. Use when the user wants to judge whether a gel ran well, whether the main band matches the expected product, or whether there may be impurities, degradation, aggregation, or low expression.

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Extract full transcripts and captions from YouTube videos for content analysis, summarization, note-taking, and repurposing. Supports multiple languages and auto-generated captions. Ideal for research, content creation, and accessibility workflows.

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Research podcasts, episodes, and audio content by searching YouTube (where most podcasts crosspost), web sources, and transcript databases. Discover relevant shows, track guest appearances, and analyze topic coverage in the podcast ecosystem.

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Search videos, analyze channels, extract captions, read comments, and discover trends on YouTube through SandBase. Use when asked for YouTube research, video discovery, channel analysis, content strategy research, comment sentiment, or video transcript extraction.

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Plan and produce short AI videos with SandBase image, video, music, and speech models. Use for commercials, social clips, explainers, short films, storyboards, or multi-shot video generation; use a simpler image or audio skill when no video deliverable is needed.

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Create, implement, or review video template frame light leak cinema work with format, accessibility, performance, and visual-verification controls. Use when the requested deliverable depends on video template frame light leak cinema.

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Create, implement, or review video template frame glitch title work with format, accessibility, performance, and visual-verification controls. Use when the requested deliverable depends on video template frame glitch title.

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Create, implement, or review html video production work with format, accessibility, performance, and visual-verification controls. Use when the requested deliverable depends on html video production.

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Create, implement, or review imagemagick image manipulation work with format, accessibility, performance, and visual-verification controls. Use when the requested deliverable depends on imagemagick image manipulation.

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Generate free images with Agnes Image 2.1 Flash through the Agnes API, including text-to-image, image-to-image, high-density visual prompts, URL results, and local downloads. Use when the user asks for 免费图片, 免费的图片模型, free image API, Agnes image, Agnes Image 2.1 Flash, free AI image generation, image-to-image via Agnes, or wants a free image model Agent skill.

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Create free Agnes video generation tasks and retrieve video results through Agnes-Video-V2.0, including text-to-video, image-to-video, multi-image video, keyframe animation, async polling, and video download. Use when the user asks for 免费视频, 免费的视频模型, free video API, Agnes video, Agnes-Video-V2.0, text-to-video, image-to-video, keyframes, or wants a free video model Agent skill.

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Best practices for Remotion - Video creation in React

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cheat-on-skill 的核心。连 BOSS 直聘真实招聘数据 + 网页信号，按用户能力画像找「高薪 × 你学得动 × AI 增强」交集里的候选岗位。每个岗位给：薪资量级 / 需求热度 / 你的差距 / 可学性分 / 诚实学习周期，并过 AI 影响分类与反诈红线。触发词："帮我找岗位"/"找AI时代高薪工作"/"有什么我能学的高薪岗"/"skill scan"/"扫一遍招聘"。前置：需要 .skill-state.json（无则先路由到 skill-init）。

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