[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"skill:01M6BXVSJQTC4SWB1AR8DX56XD":3,"skill-same:01M6BXVSJQTC4SWB1AR8DX56XD":72},{"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":6,"sourceHtmlUrl":16,"categories":17,"keywords":23,"publishedAt":38,"linkOnly":39,"markdownContent":40,"markdownBody":41,"frontMatter":42,"refName":43,"commitSha":44,"skillDirectory":45,"forksCount":46,"repositoryHtmlUrl":47,"repositoryHomepageUrl":48,"ownerHtmlUrl":49,"ownerBlogUrl":12,"ownerDescription":50,"updatedAt":51,"install":52,"resources":65},"01M6BXVSJQTC4SWB1AR8DX56XD","sandbox-ocr",null,"Read the text in an image from a Code node or CodeAct action, with tesseract.js running on the host","nodetool-ai\u002Fnodetool","nodetool-ai","https:\u002F\u002Favatars.githubusercontent.com\u002Fu\u002F164873569?v=4","01M6BXPFDW36K9K1MR8ZH63HG2","nodetool.ai","01M6BXPFJ893XM219GQN60B0WK",628,"AGPL-3.0","https:\u002F\u002Fgithub.com\u002Fnodetool-ai\u002Fnodetool\u002Fblob\u002Fmain\u002Fpackages\u002Fsandbox-packs\u002Fsandbox-ocr\u002FSKILL.md",[18],{"categoryNo":19,"categoryName":20,"taxonomyType":21,"taxonomyTypeDesc":22},"01JBSEEDCAT000000000000016","图像与多媒体","SCENARIO","使用场景",[24,25,26,27,28,29,30,31,32,33,34,35,36,37],"sandbox","ocr","sandbox ocr","image","code","js","text","node","read","host","tesseract","with","action","running","2026-11-10 10:12:30",false,"---\nname: sandbox-ocr\ndescription: Read the text in an image from a Code node or CodeAct action, with tesseract.js running on the host\n---\n\n# OCR in the sandbox\n\nSpecifier: `@nodetool-ai\u002Fsandbox-ocr`. Import it at the top of the body.\n\ntesseract.js runs a WASM engine, spawns workers, and downloads its language\ndata on first use — none of which the guest can do. This pack is a **host\nmodule**: the import resolves to a generated facade over NodeTool's own\nimplementation.\n\n## recognize — image bytes to text\n\n```js\nimport { recognize } from \"@nodetool-ai\u002Fsandbox-ocr\";\n\nconst { text, confidence, words } = await recognize(\n  await workspace.readBytes(\"receipt.png\")\n);\nconst total = words.find((w) => \u002F^\\d+[.,]\\d{2}$\u002F.test(w.text));\nreturn { text, confidence, total: total?.text ?? null };\n```\n\nOne call gives you all three readings:\n\n- `text` — the whole page as one string.\n- `confidence` — the page mean, 0–100.\n- `words` — `{text, confidence, bbox: {x, y, width, height}}` per word, in\n  reading order, with the box in image pixels.\n\nPass `{ language: \"eng+deu\" }` for anything other than English; the codes are\nTesseract's, `+`-joined. The data file for a language it has not seen before is\ndownloaded the first time you ask for it, so that call is slower.\n\nGet the bytes from `workspace.readBytes`, from `await response.bytes()`, or\nfrom an asset with `assetToSandbox`.\n\n## Gotchas\n\n- **`recognize` is async**, and the first call to it pays for engine startup.\n- **10 MB per image.** Larger input is refused by name.\n- **20 000 words per page.**\n- **Straight, sharp scans read best.** Use `image.rotate` and `image.adjust` to\n  deskew and raise contrast before you hand the bytes over.\n","# OCR in the sandbox\n\nSpecifier: `@nodetool-ai\u002Fsandbox-ocr`. Import it at the top of the body.\n\ntesseract.js runs a WASM engine, spawns workers, and downloads its language\ndata on first use — none of which the guest can do. This pack is a **host\nmodule**: the import resolves to a generated facade over NodeTool's own\nimplementation.\n\n## recognize — image bytes to text\n\n```js\nimport { recognize } from \"@nodetool-ai\u002Fsandbox-ocr\";\n\nconst { text, confidence, words } = await recognize(\n  await workspace.readBytes(\"receipt.png\")\n);\nconst total = words.find((w) => \u002F^\\d+[.,]\\d{2}$\u002F.test(w.text));\nreturn { text, confidence, total: total?.text ?? null };\n```\n\nOne call gives you all three readings:\n\n- `text` — the whole page as one string.\n- `confidence` — the page mean, 0–100.\n- `words` — `{text, confidence, bbox: {x, y, width, height}}` per word, in\n  reading order, with the box in image pixels.\n\nPass `{ language: \"eng+deu\" }` for anything other than English; the codes are\nTesseract's, `+`-joined. The data file for a language it has not seen before is\ndownloaded the first time you ask for it, so that call is slower.\n\nGet the bytes from `workspace.readBytes`, from `await response.bytes()`, or\nfrom an asset with `assetToSandbox`.\n\n## Gotchas\n\n- **`recognize` is async**, and the first call to it pays for engine startup.\n- **10 MB per image.** Larger input is refused by name.\n- **20 000 words per page.**\n- **Straight, sharp scans read best.** Use `image.rotate` and `image.adjust` to\n  deskew and raise contrast before you hand the bytes over.\n",{"name":5,"description":7},"main","c7226baa82daca42a19a5855c116544f97aa8bac","packages\u002Fsandbox-packs\u002Fsandbox-ocr",90,"https:\u002F\u002Fgithub.com\u002Fnodetool-ai\u002Fnodetool","https:\u002F\u002Fnodetool.ai\u002F","https:\u002F\u002Fgithub.com\u002Fnodetool-ai","No-code AI development","2026-11-12 03:00:58",{"source":8,"skillName":5,"commands":53,"prompt":63,"zipAvailable":64},[54,57,60],{"tool":55,"command":56},"npx","npx skills add nodetool-ai\u002Fnodetool --skill sandbox-ocr",{"tool":58,"command":59},"bunx","bunx skills add nodetool-ai\u002Fnodetool --skill sandbox-ocr",{"tool":61,"command":62},"pnpm","pnpm dlx skills add nodetool-ai\u002Fnodetool --skill sandbox-ocr","安装技能，技能地址：https:\u002F\u002Fgithub.com\u002Fnodetool-ai\u002Fnodetool\u002Fblob\u002Fmain\u002Fpackages\u002Fsandbox-packs\u002Fsandbox-ocr\u002FSKILL.md",true,[66],{"path":67,"resourceType":68,"resourceTypeDesc":69,"sizeBytes":70,"sourceHtmlUrl":71},"package.json","REFERENCE","参考文档",856,"https:\u002F\u002Fgithub.com\u002Fnodetool-ai\u002Fnodetool\u002Fblob\u002Fmain\u002Fpackages\u002Fsandbox-packs\u002Fsandbox-ocr\u002Fpackage.json",[73,107,133,148,164,189],{"skillNo":74,"name":75,"nameZh":6,"description":76,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":15,"licenseFileUrl":6,"sourceHtmlUrl":77,"categories":78,"keywords":87,"publishedAt":38},"01M6BY4D93R0Q9400ZHJ04DXP1","nodetool","Use the NodeTool MCP server to build, validate, run, and debug visual AI workflows, and to work with assets, collections, and jobs. Use when the user mentions NodeTool or asks for a workflow graph, a node, or a media generation run on their NodeTool server.","https:\u002F\u002Fgithub.com\u002Fnodetool-ai\u002Fnodetool\u002Fblob\u002Fmain\u002Fplugins\u002Fchatgpt\u002Fnodetool\u002Fskills\u002Fnodetool\u002FSKILL.md",[79,82],{"categoryNo":80,"categoryName":81,"taxonomyType":21,"taxonomyTypeDesc":22},"01JBSEEDCAT000000000000023","Skill与智能体开发",{"categoryNo":83,"categoryName":84,"taxonomyType":85,"taxonomyTypeDesc":86},"01JBSEEDCAT000000000000030","开发工程师","PROFESSION","适用职业",[75,88,89,90,91,92,93,94,95,96,97,98,99,31,100,101,102,103,104,35,105,106],"MCP","mcp server","workflow","workflows","validate","debug","run","graph","server","Media","assets","work","use","visual","generation","collections","media generation","for","when",{"skillNo":108,"name":109,"nameZh":6,"description":110,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":15,"licenseFileUrl":6,"sourceHtmlUrl":111,"categories":112,"keywords":114,"publishedAt":38},"01M6BY4AEB05ZPBRVD078ATR2H","wan-2-6-prompting","Prompt Alibaba's Wan 2.6 video — text-to-video with a global style line plus timing-bracketed shots, and image-to-video that describes only what changes over time. Covers the shot-mode switch per provider, the prompt budget, negative prompts, motion intensity wording, audio input and prompt expansion. Use whenever the model id names a Wan 2.6 video route (alibaba\u002Fwan-2.6\u002Ftext-to-video, alibaba\u002Fwan-2.6\u002Fimage-to-video, wan-video\u002Fwan-2.6-t2v, wan-video\u002Fwan-2.6-i2v, wan-video\u002Fwan2.6-i2v-flash) on generate_video, animate_image or a TextToVideo node. Not for Wan 2.5 or 2.7, or the Wan 2.6 image routes.","https:\u002F\u002Fgithub.com\u002Fnodetool-ai\u002Fnodetool\u002Fblob\u002Fmain\u002Fpackages\u002Fsystem-skills\u002Fwan-2-6-prompting\u002FSKILL.md",[113],{"categoryNo":19,"categoryName":20,"taxonomyType":21,"taxonomyTypeDesc":22},[115,116,27,117,118,119,120,30,121,122,123,31,124,125,126,127,128,129,130,131,132],"wan 2 6 prompting","prompting","generate","Budget","Video","Audio","animate","model","flash","only","route","time","line","input","text-to-video","image-to-video","mode","expansion",{"skillNo":134,"name":135,"nameZh":6,"description":136,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":15,"licenseFileUrl":6,"sourceHtmlUrl":137,"categories":138,"keywords":141,"publishedAt":38},"01M6BY47T4748ZG5ZMTAR97ZWZ","video-workflow","Build a reusable NodeTool video workflow for batches or repeated inputs. For a single finished piece, use a storyboard skill.","https:\u002F\u002Fgithub.com\u002Fnodetool-ai\u002Fnodetool\u002Fblob\u002Fmain\u002Fpackages\u002Fsystem-skills\u002Fvideo-workflow\u002FSKILL.md",[139,140],{"categoryNo":19,"categoryName":20,"taxonomyType":21,"taxonomyTypeDesc":22},{"categoryNo":80,"categoryName":81,"taxonomyType":21,"taxonomyTypeDesc":22},[90,119,142,75,100,143,144,145,146,105,147],"video workflow","reusable","storyboard","build","batches","single",{"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":15,"licenseFileUrl":6,"sourceHtmlUrl":152,"categories":153,"keywords":155,"publishedAt":38},"01M6BY4587N2SYN315SXGEMZC3","video-clone","Analyze a reference video and recreate its shot structure with a new product or cast in NodeTool.","https:\u002F\u002Fgithub.com\u002Fnodetool-ai\u002Fnodetool\u002Fblob\u002Fmain\u002Fpackages\u002Fsystem-skills\u002Fvideo-clone\u002FSKILL.md",[154],{"categoryNo":19,"categoryName":20,"taxonomyType":21,"taxonomyTypeDesc":22},[119,156,157,158,159,75,160,161,162,35,163],"video clone","clone","product","analyze","reference","cast","structure","new",{"skillNo":165,"name":166,"nameZh":6,"description":167,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":15,"licenseFileUrl":6,"sourceHtmlUrl":168,"categories":169,"keywords":171,"publishedAt":38},"01M6BY4257C2KQYYMD9EK6DK8E","video-audio-continuity","Keep sound continuous across a multi-scene piece cut from generated video — why one clip per scene hard-cuts the audio at every boundary, when to write all the scenes into a single generation instead, the sound-design vocabulary that survives a provider's copyright filter, and how to check the length, the aspect ratio and the mix of what came back. Use when a piece has more than one scene and the video model writes its own audio (Seedance 2, Veo 3, MiniMax H3, Kling 2.6 and later), or when a cut's sound drops out at the shot changes.","https:\u002F\u002Fgithub.com\u002Fnodetool-ai\u002Fnodetool\u002Fblob\u002Fmain\u002Fpackages\u002Fsystem-skills\u002Fvideo-audio-continuity\u002FSKILL.md",[170],{"categoryNo":19,"categoryName":20,"taxonomyType":21,"taxonomyTypeDesc":22},[119,120,172,173,174,175,176,177,122,178,179,180,181,182,183,184,185,186,187,188,106],"video audio continuity","continuity","design","boundary","how","why","write","generated","later","back","across","cut","how to","filter","mix","at","veo 3",{"skillNo":190,"name":191,"nameZh":6,"description":192,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":15,"licenseFileUrl":6,"sourceHtmlUrl":193,"categories":194,"keywords":196,"publishedAt":38},"01M6BY3ZANBSQMZRH4MG55R8Z7","veo-3-prompting","Prompt Google's Veo 3 video line — the five-element shot\u002Fsetting\u002Fsubject\u002Faction\u002Fdialogue structure, the cinematography vocabulary it reads directly, duration and aspect-ratio tradeoffs, the audio and auto-fix switches per provider, and the fixes for visual drift, temporal inconsistency and audio mismatch. Use whenever the model id contains veo3 or veo-3 (fal-ai\u002Fveo3.1 and its fast, lite, image-to-video, first-last-frame and reference-to-video routes, fal-ai\u002Fveo3\u002Fimage-to-video, google\u002Fveo3.1 on atlascloud, google\u002Fveo-3 and google\u002Fveo-3.1 on replicate, kie's veo-3-1, and Gemini's own veo-3.1-generate-preview) on generate_video, animate_image, generate_video_from_references or a TextToVideo node.","https:\u002F\u002Fgithub.com\u002Fnodetool-ai\u002Fnodetool\u002Fblob\u002Fmain\u002Fpackages\u002Fsystem-skills\u002Fveo-3-prompting\u002FSKILL.md",[195],{"categoryNo":19,"categoryName":20,"taxonomyType":21,"taxonomyTypeDesc":22},[197,198,116,188,27,199,200,117,201,202,119,120,121,122,203,204,205,206,207,208,209,162,210,211,212],"veo 3 prompting","veo","google","gemini","fast","first","fal","kie","replicate","fix","auto","references","drift","preview","element","auto-fix"]