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Content-Derived Design — reads existing HTML and writes a stronger standalone page from headings, facts, names, dates, numbers, links, emails, and colors already in that file. CLI: npx reimagine-it --auto -i page.html -o out.html; also variations, lock, and audit. Use when the user says /reimagine-it, "reimagine it", "reinvent this", "redesign this page", "make an infographic", wants a content-aware redesign or a visual leap instead of a mood board. All 17 tokens: webpage, infographic, svg, 3js, simulation, artistic, cinematic, dashboard, photography, landing, editorial, gradient, showcase, motion, glass, lookbook, particles — plus leftover words as a brief. Also /reimagine-it audit for quality checks. The agent runs the CLI; it does not hand-author the page. Installed via npx skills add Kayforkind/reimagine-it or plugin marketplace. Not /better. Not a mood board. Does not ingest PDF, PPTX, or DOCX.

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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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options income, covered call strategy, cash secured puts, credit spreads, iron condor, wheel strategy, premium selling, yield enhancement, defined risk income, monthly income options

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。

Thesis report synthesis — turn a thesis's markdown artifacts into its letter-size thesis-report.html, then OPTIMIZE it against real page renders. Four-step loop — pack (deterministic Python bundle of all sources + report/metrics.json), author (the LLM writes report/content.html — narrative, KPI tiles, badges, timeline, tables and citations are LLM judgment), assemble (deterministic validation, template injection, Q50 pins, Q47 overflow gate), render + optimize (Chrome headless per-page PNGs — the LLM reads them and iterates until every page is visually clean). Spec 046 Q46–Q50.

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Med-adapted recent-quarter review: last print financials, pipeline-milestone awareness, and FDA-event context — reads the quarter through the med lens (milestones moved, runway, regulatory updates) rather than generic financials alone.

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Testing workflow skill for finding high-value test candidates, writing focused tests, generating realistic workloads, reviewing test value, and diagnosing test-suite health. Use for prompts about what to test next, adding or improving tests, reviewing whether a test is worth keeping, low-signal or flaky tests, workload scenarios, or test-suite trust. Do not use for general QA discussion unless the user wants a concrete testing workflow or artifact.

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Use Cartesia Sonic and related Cartesia voice APIs for production speech: text-to-speech, realtime WebSocket TTS, voice selection, instant and professional voice cloning, pronunciation/language/emotion controls, voice localization, voice changer, pricing/concurrency planning, privacy/security review, and QA for narration, ads, localization, dubbing, avatars, and interactive voice agents.

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Produce, direct, generate, QA, and integrate non-speech audio with ElevenLabs Text to Sound Effects / Sound Effects API. Use when an agent needs custom SFX, foley, ambience, loops, stingers, impacts, UI sounds, musical one-shots, trailer braams, or sound-design layers for video, ads, social edits, games, apps, podcasts, audiobooks, or interactive media using ElevenLabs.

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 Stability AI Stable Audio production work: selecting Stable Audio hosted API or open-weight models, generating or editing music, loops, sound effects, foley, beds, stingers, and sonic-branding audio from text or source audio, planning rights-safe uploads, setting model parameters, polling asynchronous jobs, and reviewing generated audio for media projects.

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Select, integrate, and operate multi-model video-generation gateways — hosted inference aggregators such as fal.ai, Replicate, and WaveSpeed that expose many third-party video (and video-adjacent audio) models behind one account, one API surface, and one bill. Use when deciding whether to route video generation through a gateway versus a direct model-provider API; when comparing gateways on catalog, async/queue job design, webhooks, pricing, schema discovery, and version pinning; and when operating gateway workloads in production — spend controls, retries, cross-gateway failover, content- safety differences, data retention, and commercial-rights passthrough of the underlying model. Not for direct model-provider APIs, local/self-hosted inference, model training/fine-tuning, or image-only gateway use.

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Produce text-to-speech with Alibaba/Qwen Qwen3-TTS through DashScope/Model Studio or open-weight Qwen3-TTS checkpoints. Use when an agent must choose Qwen3-TTS models, voices, realtime versus non-realtime synthesis, voice cloning, voice design, instruction/prosody controls, multilingual or dialect speech, audio artifact handling, regional routing, pricing/privacy/licensing constraints, or production QA for narration, characters, assistants, audiobooks, ads, localization, or voice-enabled media.

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Produce and review production image-generation and image-editing workflows with Amazon Nova Canvas on Amazon Bedrock, including native InvokeModel payloads, safe authentication, validation, retries, cost controls, provenance, and lifecycle migration checks. Use when a task names Nova Canvas, amazon.nova-canvas-v1:0, Bedrock image generation, Canvas inpainting/outpainting/background removal, image conditioning, color guidance, image variation, virtual try-on, or Canvas fine-tuning.

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 operate rights-aware Bria FIBO and FIBO Lite image-generation workflows with structured prompts, reference images, asynchronous status handling, webhooks, cost gates, and safe artifact downloads. Use when a user asks for Bria/FIBO generation, refinement, inspiration, reproducibility, hosted API integration, or a licensed-data image workflow; do not use for FIBO Edit, video, generic image editing, or third-party FIBO gateways.

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Use ACE-Step and ACE-Step 1.5 for local or hosted AI music generation, including text-to-music, lyrics-to-song, instrumental beds, covers, repainting, stem/track extraction, track completion, LoRA personalization, REST/Python/Gradio workflows, rights review, and music integration for video, ads, games, and social content.

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Provider-independent VFX compositing direction for generated video, ads, trailers, product films, social clips, explainers, mixed-source edits, and image/video composites. Use when an agent must plan, brief, generate, integrate, repair, or quality-check visual effects composites involving plates, alpha/mattes, keying, roto, tracking, stabilization, matchmove, lighting/color integration, grain/noise/sharpness, shadows/reflections/contact, depth/atmosphere, AI-generated elements, clean plates, editor/colorist handoff, rights/safety, or compositing 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。

Provider-independent title design and kinetic typography direction for video, animation, ads, explainers, social hooks, brand films, lyric/text videos, title cards, main titles, lower thirds, captions-as-design, and other motion-led text. Use when an agent must plan, prompt, implement, hand off, iterate, or QA typography hierarchy, readability, timing, reveal/hold/exit, motion semantics, line breaks, safe areas, localization, brand constraints, accessibility, flashing/motion safety, or production specs for animated text.

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。

Provider-independent media quality control and delivery direction for generated images, video, audio, ads, product content, social clips, broadcast and streaming assets, localization packages, and mixed-source edits. Use when an agent must define final export specs, inspect technical and perceptual quality, check captions/audio/color/accessibility/provenance/rights, create delivery sheets, version filenames, checksums, manifests, package deliverables, set acceptance or rejection criteria, and perform final delivery QA before handoff to a platform, broadcaster, streamer, client, or ad trafficker.

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。

Provider-independent provenance, rights, consent, disclosure, and release governance for AI-generated media. Use when producing or reviewing generated images, video, audio, ads, avatars, product content, social clips, documentaries, localization, music, sound, or campaign assets that need source-rights checks, model/provider term checks, likeness or voice consent, trademark/logo review, copyrighted-character/style risk triage, music licensing, C2PA/content credentials, provenance ledgers, release notes, platform disclosures, jurisdiction/client caveats, or rights 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。

Provider-independent character design and continuity direction for generated media. Use when an agent must create, preserve, revise, or QA a recurring character across AI-generated images, video clips, avatars, animation, comics, ads, product mascots, serialized social posts, or multi-shot campaigns; especially when building character bibles, reference packs, prompts, expression/pose ranges, costume/hair/makeup/prop continuity, identity and likeness safeguards, iteration plans, handoff notes, or continuity reviews.

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。

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。

Provider-independent audio mixing and mastering direction for AI agents finishing generated videos, ads, trailers, explainers, podcasts, recuts, avatar clips, music videos, documentaries, and social content. Use when planning, mixing, repairing, mastering, QCing, or delivering dialogue, music, ambience, and sound effects, including loudness/true-peak targets, intelligibility, accessibility, stems, stereo/immersive decisions, platform/client specs, and final audio 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。

Provider-independent sound design and Foley direction for generated media. Use when an agent must plan, prompt, source, generate, edit, mix, hand off, repair, or QA sound effects, Foley, ambience, impacts, transitions, UI/product audio, emotional sound design, or accessibility-safe captions for videos, ads, trailers, animation, avatar clips, explainers, games/trailers, product films, and social edits.

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。

Provider-independent editing and montage direction for AI agents producing generated videos, ads, trailers, social clips, explainers, product videos, documentary-style pieces, and music- or beat-driven cuts. Use when planning, revising, QAing, or handing off an edit: story structure, shot selection, continuity, montage theory, rhythm and pacing, J/L cuts, match cuts, cutaways, transitions, beat sync, platform timing, source/generated asset management, revision workflow, and composition handoff.

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Provider-independent workflow for producing UGC-style paid and social ads, creator testimonials, product demos, hooks, before/after concepts, app walkthroughs, TikTok/Reels/Shorts variants, synthetic-persona or avatar UGC, ad-policy checks, disclosure planning, rights/consent review, delivery specs, 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。