[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"skill:01M6MJBAJ8NAPVXE3A4NETJR2P":3,"skill-same:01M6MJBAJ8NAPVXE3A4NETJR2P":96},{"skillNo":4,"name":5,"nameZh":6,"description":7,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":15,"licenseFileUrl":16,"sourceHtmlUrl":17,"categories":18,"keywords":24,"publishedAt":45,"linkOnly":46,"markdownContent":47,"markdownBody":48,"frontMatter":49,"refName":53,"commitSha":54,"skillDirectory":55,"forksCount":56,"repositoryHtmlUrl":57,"repositoryHomepageUrl":58,"ownerHtmlUrl":59,"ownerBlogUrl":60,"ownerDescription":61,"updatedAt":62,"install":63,"resources":76},"01M6MJBAJ8NAPVXE3A4NETJR2P","magic-hour-product-visuals",null,"Create or edit a Magic Hour product image with controlled composition, geometry, branding and copy space. Use for product shots, hero images, packaging and ecommerce visuals when Magic Hour is requested or is the project's chosen media provider.","hashgraph-online\u002Fawesome-codex-plugins","hashgraph-online","https:\u002F\u002Favatars.githubusercontent.com\u002Fu\u002F160371962?v=4","01M6CNB6NRJVNNGN14TR01Q6D3","HOL (Hashgraph Online)","01M6JT1HSKKG9V68KQAQGBA7XP",1554,"MIT","https:\u002F\u002Fgithub.com\u002Fhashgraph-online\u002Fawesome-codex-plugins\u002Fblob\u002Fmain\u002Fplugins\u002Fmagichourhq\u002Fskills\u002Fskills\u002Fmagic-hour-product-visuals\u002FLICENSE.txt","https:\u002F\u002Fgithub.com\u002Fhashgraph-online\u002Fawesome-codex-plugins\u002Fblob\u002Fmain\u002Fplugins\u002Fmagichourhq\u002Fskills\u002Fskills\u002Fmagic-hour-product-visuals\u002FSKILL.md",[19],{"categoryNo":20,"categoryName":21,"taxonomyType":22,"taxonomyTypeDesc":23},"01JBSEEDCAT000000000000031","产品经理","PROFESSION","适用职业",[25,26,27,28,29,30,31,32,33,34,35,36,37,38,39,40,41,42,43,44],"visuals","magic hour product visuals","magic","product","ecommerce","image","hero","create","for","with","branding","geometry","project","provider","images","use","packaging","edit","Media","Composition","2026-11-10 10:12:30",false,"---\nname: magic-hour-product-visuals\ndescription: Create or edit a Magic Hour product image with controlled composition, geometry, branding and copy space. Use for product shots, hero images, packaging and ecommerce visuals when Magic Hour is requested or is the project's chosen media provider.\nlicense: MIT\nmetadata:\n  author: magichourhq\n  version: \"1.3.0\"\n---\n\n# Magic Hour product visuals\n\nDeliver a product image that fits its intended placement and preserves the details that make the product recognizable. Treat a project ID as an intermediate result and inspect the finished image before calling it complete.\n\nGeneration consumes Magic Hour credits. Use a connected Magic Hour creation MCP at `https:\u002F\u002Fmcp.magichour.ai\u002F` when available. Otherwise read `references\u002Fsetup.md`. Discover the current schema before choosing a model, resolution, image count, or cost.\n\nInfer the treatment from the customer's intended use; recommend one direction instead of asking them to choose technical parameters. Honor existing budget and delegated creative decisions, inspect intermediate results yourself and continue unless the user requested draft approval. Show the finished image first; retain technical records with the project. For catalog, lifestyle, detail, in-hand or coordinated sets, read [reference photoshoot](references\u002Fphotoshoot.md).\n\n## Define the deliverable\n\nExtract or infer:\n\n- where the image will appear, such as a product page, ad, marketplace listing, or website hero\n- aspect ratio, resolution, crop tolerance, and required negative space\n- product shape, material, finish, color, label, logo, and exact text\n- camera angle, scale in frame, surface, background, lighting, and shadow\n- details that must remain unchanged\n- visible failures that make the image unusable\n\nFor a hero, specify which side needs empty space for copy. For an ecommerce listing, keep the full product inside the frame with a clean silhouette. When exact product identity, packaging, or branding matters, use an authorized reference and edit it rather than recreating it from text.\n\n## Choose generation or editing\n\n- With no source image, call `generate_image`.\n- With a usable source that needs a new setting, cleanup, relighting, repositioning, or other controlled change, call `edit_image`.\n- AI Image Editor requires an input image. Never route a prompt-only creation request to it.\n\nUse one image at a resolution that reveals the product's critical details and fits its placement. A low-resolution preview is useful for composition, not final label fidelity. Check cost against existing authorization and ask only when it does not cover the intended work. Prefer the live recommended model for a general request and choose a specialist only when the current schema describes the needed behavior.\n\n## Write a production brief\n\nWrite the prompt in this order:\n\n1. intended image type and aspect ratio\n2. one product with material, shape, color, and orientation\n3. exact composition and space allocation\n4. lighting, surface, background, shadow, and reflection\n5. required label, logo, or text in quotation marks\n6. elements that must remain fixed\n7. concrete rejection conditions\n\nUse direct visual language. A useful pattern is:\n\n`Premium 16:9 product hero photograph. One [product] in the right third, fully visible, with clean negative space across the left 40 percent. [Camera and material]. [Lighting, surface, and background]. Preserve [shape, colors, logo, and exact label]. No extra objects, duplicate text, warped geometry, unintended marks, or watermark.`\n\nFor editing, describe the change first and then state what remains unchanged. Compare against the original reference, not just the prompt: a prettier bottle with a different cap or viewpoint is still a failed preservation edit. Do not stack unrelated styles or ask one image to show several scenes. Keep promotional copy in a separate layout layer when a suitable tool is available; preserve text already printed on the product.\n\n## Inspect before delivery\n\nWait for the existing image project with `wait_for_image_project`. After it reports `complete`, use the exact returned download URL and inspect the actual output for:\n\n- actual downloaded dimensions, aspect ratio, crop, product scale, and requested negative space; do not trust the requested ratio alone\n- straight edges, plausible materials, and coherent reflections and shadows\n- accurate product geometry, cap, handle, controls, packaging, and colors\n- one correct instance of required text or logo\n- no misspelling, duplicate label, invented brand-like mark, or distracting object; disclose any service watermark and do not promise an unwatermarked file without checking eligibility\n- no anatomy or identity problem when a person is intentionally present\n\nIf the result fails, change the smallest useful variable. Use AI Image Editor for a localized correction when the rest of the image is strong; regenerate when composition or product identity is fundamentally wrong. Another generation spends credits, so stay inside the user's authorized budget.\n\nWhen the product image will become video, accept the still first and use the image-to-video skill when installed. Otherwise discover `create_video_from_image`, pass the accepted image, prompt for motion, retain the ID, wait and inspect the complete clip. Do not require another skill installation to finish a supported request. Return the finished artifact, its saved location and any material limitation; retain project IDs for recovery.\n","# Magic Hour product visuals\n\nDeliver a product image that fits its intended placement and preserves the details that make the product recognizable. Treat a project ID as an intermediate result and inspect the finished image before calling it complete.\n\nGeneration consumes Magic Hour credits. Use a connected Magic Hour creation MCP at `https:\u002F\u002Fmcp.magichour.ai\u002F` when available. Otherwise read `references\u002Fsetup.md`. Discover the current schema before choosing a model, resolution, image count, or cost.\n\nInfer the treatment from the customer's intended use; recommend one direction instead of asking them to choose technical parameters. Honor existing budget and delegated creative decisions, inspect intermediate results yourself and continue unless the user requested draft approval. Show the finished image first; retain technical records with the project. For catalog, lifestyle, detail, in-hand or coordinated sets, read [reference photoshoot](references\u002Fphotoshoot.md).\n\n## Define the deliverable\n\nExtract or infer:\n\n- where the image will appear, such as a product page, ad, marketplace listing, or website hero\n- aspect ratio, resolution, crop tolerance, and required negative space\n- product shape, material, finish, color, label, logo, and exact text\n- camera angle, scale in frame, surface, background, lighting, and shadow\n- details that must remain unchanged\n- visible failures that make the image unusable\n\nFor a hero, specify which side needs empty space for copy. For an ecommerce listing, keep the full product inside the frame with a clean silhouette. When exact product identity, packaging, or branding matters, use an authorized reference and edit it rather than recreating it from text.\n\n## Choose generation or editing\n\n- With no source image, call `generate_image`.\n- With a usable source that needs a new setting, cleanup, relighting, repositioning, or other controlled change, call `edit_image`.\n- AI Image Editor requires an input image. Never route a prompt-only creation request to it.\n\nUse one image at a resolution that reveals the product's critical details and fits its placement. A low-resolution preview is useful for composition, not final label fidelity. Check cost against existing authorization and ask only when it does not cover the intended work. Prefer the live recommended model for a general request and choose a specialist only when the current schema describes the needed behavior.\n\n## Write a production brief\n\nWrite the prompt in this order:\n\n1. intended image type and aspect ratio\n2. one product with material, shape, color, and orientation\n3. exact composition and space allocation\n4. lighting, surface, background, shadow, and reflection\n5. required label, logo, or text in quotation marks\n6. elements that must remain fixed\n7. concrete rejection conditions\n\nUse direct visual language. A useful pattern is:\n\n`Premium 16:9 product hero photograph. One [product] in the right third, fully visible, with clean negative space across the left 40 percent. [Camera and material]. [Lighting, surface, and background]. Preserve [shape, colors, logo, and exact label]. No extra objects, duplicate text, warped geometry, unintended marks, or watermark.`\n\nFor editing, describe the change first and then state what remains unchanged. Compare against the original reference, not just the prompt: a prettier bottle with a different cap or viewpoint is still a failed preservation edit. Do not stack unrelated styles or ask one image to show several scenes. Keep promotional copy in a separate layout layer when a suitable tool is available; preserve text already printed on the product.\n\n## Inspect before delivery\n\nWait for the existing image project with `wait_for_image_project`. After it reports `complete`, use the exact returned download URL and inspect the actual output for:\n\n- actual downloaded dimensions, aspect ratio, crop, product scale, and requested negative space; do not trust the requested ratio alone\n- straight edges, plausible materials, and coherent reflections and shadows\n- accurate product geometry, cap, handle, controls, packaging, and colors\n- one correct instance of required text or logo\n- no misspelling, duplicate label, invented brand-like mark, or distracting object; disclose any service watermark and do not promise an unwatermarked file without checking eligibility\n- no anatomy or identity problem when a person is intentionally present\n\nIf the result fails, change the smallest useful variable. Use AI Image Editor for a localized correction when the rest of the image is strong; regenerate when composition or product identity is fundamentally wrong. Another generation spends credits, so stay inside the user's authorized budget.\n\nWhen the product image will become video, accept the still first and use the image-to-video skill when installed. Otherwise discover `create_video_from_image`, pass the accepted image, prompt for motion, retain the ID, wait and inspect the complete clip. Do not require another skill installation to finish a supported request. Return the finished artifact, its saved location and any material limitation; retain project IDs for recovery.\n",{"name":5,"license":15,"metadata":50,"description":7},{"author":51,"version":52},"magichourhq","1.3.0","main","2b63f856ce19c2a797929cacabd9e0fc936812fa","plugins\u002Fmagichourhq\u002Fskills\u002Fskills\u002Fmagic-hour-product-visuals",468,"https:\u002F\u002Fgithub.com\u002Fhashgraph-online\u002Fawesome-codex-plugins","https:\u002F\u002Fhol.org\u002Fplugins\u002Fbest-codex-plugins","https:\u002F\u002Fgithub.com\u002Fhashgraph-online","https:\u002F\u002Fhol.org","Open-source standards and developer tools for interoperable AI agents: discovery, identity, communication, payments, privacy and security.","2026-11-11 02:22:54",{"source":8,"skillName":5,"commands":64,"prompt":74,"zipAvailable":75},[65,68,71],{"tool":66,"command":67},"npx","npx skills add hashgraph-online\u002Fawesome-codex-plugins --skill magic-hour-product-visuals",{"tool":69,"command":70},"bunx","bunx skills add hashgraph-online\u002Fawesome-codex-plugins --skill magic-hour-product-visuals",{"tool":72,"command":73},"pnpm","pnpm dlx skills add hashgraph-online\u002Fawesome-codex-plugins --skill magic-hour-product-visuals","安装技能，技能地址：https:\u002F\u002Fgithub.com\u002Fhashgraph-online\u002Fawesome-codex-plugins\u002Fblob\u002Fmain\u002Fplugins\u002Fmagichourhq\u002Fskills\u002Fskills\u002Fmagic-hour-product-visuals\u002FSKILL.md",true,[77,83,88,92],{"path":78,"resourceType":79,"resourceTypeDesc":80,"sizeBytes":81,"sourceHtmlUrl":82},"agents\u002Fopenai.yaml","REFERENCE","参考文档",266,"https:\u002F\u002Fgithub.com\u002Fhashgraph-online\u002Fawesome-codex-plugins\u002Fblob\u002Fmain\u002Fplugins\u002Fmagichourhq\u002Fskills\u002Fskills\u002Fmagic-hour-product-visuals\u002Fagents\u002Fopenai.yaml",{"path":84,"resourceType":85,"resourceTypeDesc":86,"sizeBytes":87,"sourceHtmlUrl":16},"LICENSE.txt","LICENSE","许可证",1076,{"path":89,"resourceType":79,"resourceTypeDesc":80,"sizeBytes":90,"sourceHtmlUrl":91},"references\u002Fphotoshoot.md",3744,"https:\u002F\u002Fgithub.com\u002Fhashgraph-online\u002Fawesome-codex-plugins\u002Fblob\u002Fmain\u002Fplugins\u002Fmagichourhq\u002Fskills\u002Fskills\u002Fmagic-hour-product-visuals\u002Freferences\u002Fphotoshoot.md",{"path":93,"resourceType":79,"resourceTypeDesc":80,"sizeBytes":94,"sourceHtmlUrl":95},"references\u002Fsetup.md",1193,"https:\u002F\u002Fgithub.com\u002Fhashgraph-online\u002Fawesome-codex-plugins\u002Fblob\u002Fmain\u002Fplugins\u002Fmagichourhq\u002Fskills\u002Fskills\u002Fmagic-hour-product-visuals\u002Freferences\u002Fsetup.md",[97,125,148,181,200,214],{"skillNo":98,"name":99,"nameZh":6,"description":100,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":101,"licenseFileUrl":6,"sourceHtmlUrl":102,"categories":103,"keywords":104,"publishedAt":45},"01M716A6ETNB9B1SQ3GXZC75VR","deja-search","deja-vu memory — search the user's past AI coding sessions with the deja CLI. Holds what they already settled and never wrote into the repo (naming rules, banned or already-tried tools, required checks before merge, preferred values, who owns what). Use before your first edit in a task, before you call a change done or ready to merge, before you recommend a tool, library, design or reviewer, before re-debugging an error that may already be solved, when they say 'didn't we fix this before', 'what did we decide about X' or 'I already have that', and before telling them something on this machine does not exist.","Apache-2.0","https:\u002F\u002Fgithub.com\u002Fhashgraph-online\u002Fawesome-codex-plugins\u002Fblob\u002Fmain\u002Fplugins\u002Fvshulcz\u002Fdeja-vu\u002Fskills\u002Fdeja-search\u002FSKILL.md",[],[105,106,107,108,109,110,111,112,113,114,115,116,117,118,119,120,121,122,123,124],"search","deja search","error","ready","never","memory","re","decide","fix","design","debugging","when","you","done","reviewer","io","change","cli","merge","past",{"skillNo":126,"name":127,"nameZh":6,"description":128,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":101,"licenseFileUrl":6,"sourceHtmlUrl":129,"categories":130,"keywords":131,"publishedAt":45},"01M716A3J2W5SENSE9VGMXB375","deja-reflect","End-of-session reflection and memory curation with deja-vu. Review what was decided, what commands broke and what repaired them, and record durable project rules or decisions with deja remember so the next session starts with them.","https:\u002F\u002Fgithub.com\u002Fhashgraph-online\u002Fawesome-codex-plugins\u002Fblob\u002Fmain\u002Fplugins\u002Fvshulcz\u002Fdeja-vu\u002Fskills\u002Fdeja-reflect\u002FSKILL.md",[],[132,133,134,135,110,136,37,137,138,139,140,141,142,120,34,143,144,145,146,147],"reflect","deja reflect","brew","remember","project rules","session","end","reflection","Rules","decisions","review","record","github","next","https","node",{"skillNo":149,"name":150,"nameZh":6,"description":151,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":101,"licenseFileUrl":6,"sourceHtmlUrl":152,"categories":153,"keywords":165,"publishedAt":45},"01M715T3RR4BAYSR57HPPTJ0PF","revid","Make, edit, export and post AI videos with Revid (revid.ai) through the Revid MCP server. Use whenever the user wants a short-form or long-form video made (from an idea, a script, a URL, an article, a PDF, a tweet, a product page, their own clips, or a song), wants to find what is going viral on TikTok, YouTube, Instagram or X before making something, wants to edit or re-export an existing Revid project, generate a standalone AI image or clip, make a series episode, or publish and schedule a finished video to connected social accounts. Covers setup (hosted MCP with OAuth, or an API key), the 36 tools, credits, polling and the rules for publishing. Routes to the more specific revid-* skills when one fits.","https:\u002F\u002Fgithub.com\u002Fhashgraph-online\u002Fawesome-codex-plugins\u002Fblob\u002Fmain\u002Fplugins\u002Ftmakersas\u002Frevid-skills\u002Fskills\u002Frevid\u002FSKILL.md",[154,159,162],{"categoryNo":155,"categoryName":156,"taxonomyType":157,"taxonomyTypeDesc":158},"01JBSEEDCAT000000000000010","后端与接口","SCENARIO","使用场景",{"categoryNo":160,"categoryName":161,"taxonomyType":157,"taxonomyTypeDesc":158},"01JBSEEDCAT000000000000016","图像与多媒体",{"categoryNo":163,"categoryName":164,"taxonomyType":157,"taxonomyTypeDesc":158},"01JBSEEDCAT000000000000023","Skill与智能体开发",[150,166,167,168,169,170,37,171,111,172,173,174,175,116,176,30,177,178,179,180],"Video","short-form","standalone","PDF","viral","tiktok","short","social","MCP","song","URL","mcp server","schedule","api","publish",{"skillNo":182,"name":183,"nameZh":6,"description":184,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":101,"licenseFileUrl":6,"sourceHtmlUrl":185,"categories":186,"keywords":187,"publishedAt":45},"01M71569ZM2X3H5RBFK8PVKMK2","review-study","Review a QuestionPunk survey before launch for wording, answer choices, branching, and missing settings. Use for check my survey or review this draft before publishing.","https:\u002F\u002Fgithub.com\u002Fhashgraph-online\u002Fawesome-codex-plugins\u002Fblob\u002Fmain\u002Fplugins\u002Fquestionpunk\u002Fcodex-plugin\u002Fskills\u002Freview-study\u002FSKILL.md",[],[188,189,142,33,190,191,192,193,40,194,195,196,197,198,199],"study","review study","answer","missing","survey","publishing","check","draft","settings","launch","my","branching",{"skillNo":201,"name":202,"nameZh":6,"description":203,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":101,"licenseFileUrl":6,"sourceHtmlUrl":204,"categories":205,"keywords":206,"publishedAt":45},"01M71567GV0C35YQBY0DPGR86B","manage-study","Find QuestionPunk studies, check status, publish an explicitly requested draft, or retrieve its participant link. Use for find my survey, publish this study, or how many people responded.","https:\u002F\u002Fgithub.com\u002Fhashgraph-online\u002Fawesome-codex-plugins\u002Fblob\u002Fmain\u002Fplugins\u002Fquestionpunk\u002Fcodex-plugin\u002Fskills\u002Fmanage-study\u002FSKILL.md",[],[207,188,208,33,192,40,209,194,195,180,210,211,212,213,198],"manage study","manage","people","how","find","link","status",{"skillNo":215,"name":216,"nameZh":6,"description":217,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":101,"licenseFileUrl":6,"sourceHtmlUrl":218,"categories":219,"keywords":220,"publishedAt":45},"01M71565A8TCA01AZQZRGRYMFZ","create-study","Create a saved QuestionPunk survey draft from a research brief or edit specified questions. Use for requests such as make a customer feedback survey or shorten my onboarding study.","https:\u002F\u002Fgithub.com\u002Fhashgraph-online\u002Fawesome-codex-plugins\u002Fblob\u002Fmain\u002Fplugins\u002Fquestionpunk\u002Fcodex-plugin\u002Fskills\u002Fcreate-study\u002FSKILL.md",[],[221,188,32,222,223,224,33,225,192,226,40,227,228,195,229,230,231,232,42,198],"create study","brief","as","feedback","customer feedback","research brief","shorten","saved","research","requests","customer","questions"]