[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"skill:01M6DBCC58YASF78VYMMZXWK3V":3,"skill-same:01M6DBCC58YASF78VYMMZXWK3V":73},{"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":26,"publishedAt":47,"linkOnly":48,"markdownContent":49,"markdownBody":50,"frontMatter":51,"refName":53,"commitSha":54,"skillDirectory":55,"forksCount":14,"repositoryHtmlUrl":56,"repositoryHomepageUrl":6,"ownerHtmlUrl":57,"ownerBlogUrl":6,"ownerDescription":6,"updatedAt":58,"install":59,"resources":72},"01M6DBCC58YASF78VYMMZXWK3V","fal-ai-media",null,"Unified media generation via fal.ai MCP — image, video, and audio. Covers text-to-image (Nano Banana), text\u002Fimage-to-video (Seedance, Kling, Veo 3), text-to-speech (CSM-1B), and video-to-audio (ThinkSound). Use when the user wants to generate images, videos, or audio with AI.","Prekzursil\u002Fagent-skills-toolchain","Prekzursil","https:\u002F\u002Favatars.githubusercontent.com\u002Fu\u002F54636077?v=4","01M6DACZ1PCQHD99SCR1YXG28B","Andrei Mihai Visalon","01M6DACZ670WZF535V3WYYSS4Z",0,"MIT","https:\u002F\u002Fgithub.com\u002FPrekzursil\u002Fagent-skills-toolchain\u002Fblob\u002Fmain\u002F.agents\u002Fskills\u002Ffal-ai-media\u002FSKILL.md",[18,23],{"categoryNo":19,"categoryName":20,"taxonomyType":21,"taxonomyTypeDesc":22},"01JBSEEDCAT000000000000016","图像与多媒体","SCENARIO","使用场景",{"categoryNo":24,"categoryName":25,"taxonomyType":21,"taxonomyTypeDesc":22},"01JBSEEDCAT000000000000023","Skill与智能体开发",[27,28,29,30,31,32,33,34,35,36,37,38,39,40,41,42,43,44,45,46],"Media","fal ai media","fal","text","media generation","generation","banana","veo","nano banana","images","use","user","MCP","Audio","Video","CSM","Text-to-Image","speech","generate","image","2026-11-10 10:12:30",false,"---\nname: fal-ai-media\ndescription: Unified media generation via fal.ai MCP — image, video, and audio. Covers text-to-image (Nano Banana), text\u002Fimage-to-video (Seedance, Kling, Veo 3), text-to-speech (CSM-1B), and video-to-audio (ThinkSound). Use when the user wants to generate images, videos, or audio with AI.\norigin: ECC\n---\n\n# fal.ai Media Generation\n\nGenerate images, videos, and audio using fal.ai models via MCP.\n\n## When to Activate\n\n- User wants to generate images from text prompts\n- Creating videos from text or images\n- Generating speech, music, or sound effects\n- Any media generation task\n- User says \"generate image\", \"create video\", \"text to speech\", \"make a thumbnail\", or similar\n\n## MCP Requirement\n\nfal.ai MCP server must be configured. Add to `~\u002F.claude.json`:\n\n```json\n\"fal-ai\": {\n  \"command\": \"npx\",\n  \"args\": [\"-y\", \"fal-ai-mcp-server\"],\n  \"env\": { \"FAL_KEY\": \"YOUR_FAL_KEY_HERE\" }\n}\n```\n\nGet an API key at [fal.ai](https:\u002F\u002Ffal.ai).\n\n## MCP Tools\n\nThe fal.ai MCP provides these tools:\n- `search` — Find available models by keyword\n- `find` — Get model details and parameters\n- `generate` — Run a model with parameters\n- `result` — Check async generation status\n- `status` — Check job status\n- `cancel` — Cancel a running job\n- `estimate_cost` — Estimate generation cost\n- `models` — List popular models\n- `upload` — Upload files for use as inputs\n\n---\n\n## Image Generation\n\n### Nano Banana 2 (Fast)\nBest for: quick iterations, drafts, text-to-image, image editing.\n\n```\ngenerate(\n  app_id: \"fal-ai\u002Fnano-banana-2\",\n  input_data: {\n    \"prompt\": \"a futuristic cityscape at sunset, cyberpunk style\",\n    \"image_size\": \"landscape_16_9\",\n    \"num_images\": 1,\n    \"seed\": 42\n  }\n)\n```\n\n### Nano Banana Pro (High Fidelity)\nBest for: production images, realism, typography, detailed prompts.\n\n```\ngenerate(\n  app_id: \"fal-ai\u002Fnano-banana-pro\",\n  input_data: {\n    \"prompt\": \"professional product photo of wireless headphones on marble surface, studio lighting\",\n    \"image_size\": \"square\",\n    \"num_images\": 1,\n    \"guidance_scale\": 7.5\n  }\n)\n```\n\n### Common Image Parameters\n\n| Param | Type | Options | Notes |\n|-------|------|---------|-------|\n| `prompt` | string | required | Describe what you want |\n| `image_size` | string | `square`, `portrait_4_3`, `landscape_16_9`, `portrait_16_9`, `landscape_4_3` | Aspect ratio |\n| `num_images` | number | 1-4 | How many to generate |\n| `seed` | number | any integer | Reproducibility |\n| `guidance_scale` | number | 1-20 | How closely to follow the prompt (higher = more literal) |\n\n### Image Editing\nUse Nano Banana 2 with an input image for inpainting, outpainting, or style transfer:\n\n```\n# First upload the source image\nupload(file_path: \"\u002Fpath\u002Fto\u002Fimage.png\")\n\n# Then generate with image input\ngenerate(\n  app_id: \"fal-ai\u002Fnano-banana-2\",\n  input_data: {\n    \"prompt\": \"same scene but in watercolor style\",\n    \"image_url\": \"\u003Cuploaded_url>\",\n    \"image_size\": \"landscape_16_9\"\n  }\n)\n```\n\n---\n\n## Video Generation\n\n### Seedance 1.0 Pro (ByteDance)\nBest for: text-to-video, image-to-video with high motion quality.\n\n```\ngenerate(\n  app_id: \"fal-ai\u002Fseedance-1-0-pro\",\n  input_data: {\n    \"prompt\": \"a drone flyover of a mountain lake at golden hour, cinematic\",\n    \"duration\": \"5s\",\n    \"aspect_ratio\": \"16:9\",\n    \"seed\": 42\n  }\n)\n```\n\n### Kling Video v3 Pro\nBest for: text\u002Fimage-to-video with native audio generation.\n\n```\ngenerate(\n  app_id: \"fal-ai\u002Fkling-video\u002Fv3\u002Fpro\",\n  input_data: {\n    \"prompt\": \"ocean waves crashing on a rocky coast, dramatic clouds\",\n    \"duration\": \"5s\",\n    \"aspect_ratio\": \"16:9\"\n  }\n)\n```\n\n### Veo 3 (Google DeepMind)\nBest for: video with generated sound, high visual quality.\n\n```\ngenerate(\n  app_id: \"fal-ai\u002Fveo-3\",\n  input_data: {\n    \"prompt\": \"a bustling Tokyo street market at night, neon signs, crowd noise\",\n    \"aspect_ratio\": \"16:9\"\n  }\n)\n```\n\n### Image-to-Video\nStart from an existing image:\n\n```\ngenerate(\n  app_id: \"fal-ai\u002Fseedance-1-0-pro\",\n  input_data: {\n    \"prompt\": \"camera slowly zooms out, gentle wind moves the trees\",\n    \"image_url\": \"\u003Cuploaded_image_url>\",\n    \"duration\": \"5s\"\n  }\n)\n```\n\n### Video Parameters\n\n| Param | Type | Options | Notes |\n|-------|------|---------|-------|\n| `prompt` | string | required | Describe the video |\n| `duration` | string | `\"5s\"`, `\"10s\"` | Video length |\n| `aspect_ratio` | string | `\"16:9\"`, `\"9:16\"`, `\"1:1\"` | Frame ratio |\n| `seed` | number | any integer | Reproducibility |\n| `image_url` | string | URL | Source image for image-to-video |\n\n---\n\n## Audio Generation\n\n### CSM-1B (Conversational Speech)\nText-to-speech with natural, conversational quality.\n\n```\ngenerate(\n  app_id: \"fal-ai\u002Fcsm-1b\",\n  input_data: {\n    \"text\": \"Hello, welcome to the demo. Let me show you how this works.\",\n    \"speaker_id\": 0\n  }\n)\n```\n\n### ThinkSound (Video-to-Audio)\nGenerate matching audio from video content.\n\n```\ngenerate(\n  app_id: \"fal-ai\u002Fthinksound\",\n  input_data: {\n    \"video_url\": \"\u003Cvideo_url>\",\n    \"prompt\": \"ambient forest sounds with birds chirping\"\n  }\n)\n```\n\n### ElevenLabs (via API, no MCP)\nFor professional voice synthesis, use ElevenLabs directly:\n\n```python\nimport os\nimport requests\n\nresp = requests.post(\n    \"https:\u002F\u002Fapi.elevenlabs.io\u002Fv1\u002Ftext-to-speech\u002F\u003Cvoice_id>\",\n    headers={\n        \"xi-api-key\": os.environ[\"ELEVENLABS_API_KEY\"],\n        \"Content-Type\": \"application\u002Fjson\"\n    },\n    json={\n        \"text\": \"Your text here\",\n        \"model_id\": \"eleven_turbo_v2_5\",\n        \"voice_settings\": {\"stability\": 0.5, \"similarity_boost\": 0.75}\n    }\n)\nwith open(\"output.mp3\", \"wb\") as f:\n    f.write(resp.content)\n```\n\n### VideoDB Generative Audio\nIf VideoDB is configured, use its generative audio:\n\n```python\n# Voice generation\naudio = coll.generate_voice(text=\"Your narration here\", voice=\"alloy\")\n\n# Music generation\nmusic = coll.generate_music(prompt=\"upbeat electronic background music\", duration=30)\n\n# Sound effects\nsfx = coll.generate_sound_effect(prompt=\"thunder crack followed by rain\")\n```\n\n---\n\n## Cost Estimation\n\nBefore generating, check estimated cost:\n\n```\nestimate_cost(\n  estimate_type: \"unit_price\",\n  endpoints: {\n    \"fal-ai\u002Fnano-banana-pro\": {\n      \"unit_quantity\": 1\n    }\n  }\n)\n```\n\n## Model Discovery\n\nFind models for specific tasks:\n\n```\nsearch(query: \"text to video\")\nfind(endpoint_ids: [\"fal-ai\u002Fseedance-1-0-pro\"])\nmodels()\n```\n\n## Tips\n\n- Use `seed` for reproducible results when iterating on prompts\n- Start with lower-cost models (Nano Banana 2) for prompt iteration, then switch to Pro for finals\n- For video, keep prompts descriptive but concise — focus on motion and scene\n- Image-to-video produces more controlled results than pure text-to-video\n- Check `estimate_cost` before running expensive video generations\n\n## Related Skills\n\n- `videodb` — Video processing, editing, and streaming\n- `video-editing` — AI-powered video editing workflows\n- `content-engine` — Content creation for social platforms\n","# fal.ai Media Generation\n\nGenerate images, videos, and audio using fal.ai models via MCP.\n\n## When to Activate\n\n- User wants to generate images from text prompts\n- Creating videos from text or images\n- Generating speech, music, or sound effects\n- Any media generation task\n- User says \"generate image\", \"create video\", \"text to speech\", \"make a thumbnail\", or similar\n\n## MCP Requirement\n\nfal.ai MCP server must be configured. Add to `~\u002F.claude.json`:\n\n```json\n\"fal-ai\": {\n  \"command\": \"npx\",\n  \"args\": [\"-y\", \"fal-ai-mcp-server\"],\n  \"env\": { \"FAL_KEY\": \"YOUR_FAL_KEY_HERE\" }\n}\n```\n\nGet an API key at [fal.ai](https:\u002F\u002Ffal.ai).\n\n## MCP Tools\n\nThe fal.ai MCP provides these tools:\n- `search` — Find available models by keyword\n- `find` — Get model details and parameters\n- `generate` — Run a model with parameters\n- `result` — Check async generation status\n- `status` — Check job status\n- `cancel` — Cancel a running job\n- `estimate_cost` — Estimate generation cost\n- `models` — List popular models\n- `upload` — Upload files for use as inputs\n\n---\n\n## Image Generation\n\n### Nano Banana 2 (Fast)\nBest for: quick iterations, drafts, text-to-image, image editing.\n\n```\ngenerate(\n  app_id: \"fal-ai\u002Fnano-banana-2\",\n  input_data: {\n    \"prompt\": \"a futuristic cityscape at sunset, cyberpunk style\",\n    \"image_size\": \"landscape_16_9\",\n    \"num_images\": 1,\n    \"seed\": 42\n  }\n)\n```\n\n### Nano Banana Pro (High Fidelity)\nBest for: production images, realism, typography, detailed prompts.\n\n```\ngenerate(\n  app_id: \"fal-ai\u002Fnano-banana-pro\",\n  input_data: {\n    \"prompt\": \"professional product photo of wireless headphones on marble surface, studio lighting\",\n    \"image_size\": \"square\",\n    \"num_images\": 1,\n    \"guidance_scale\": 7.5\n  }\n)\n```\n\n### Common Image Parameters\n\n| Param | Type | Options | Notes |\n|-------|------|---------|-------|\n| `prompt` | string | required | Describe what you want |\n| `image_size` | string | `square`, `portrait_4_3`, `landscape_16_9`, `portrait_16_9`, `landscape_4_3` | Aspect ratio |\n| `num_images` | number | 1-4 | How many to generate |\n| `seed` | number | any integer | Reproducibility |\n| `guidance_scale` | number | 1-20 | How closely to follow the prompt (higher = more literal) |\n\n### Image Editing\nUse Nano Banana 2 with an input image for inpainting, outpainting, or style transfer:\n\n```\n# First upload the source image\nupload(file_path: \"\u002Fpath\u002Fto\u002Fimage.png\")\n\n# Then generate with image input\ngenerate(\n  app_id: \"fal-ai\u002Fnano-banana-2\",\n  input_data: {\n    \"prompt\": \"same scene but in watercolor style\",\n    \"image_url\": \"\u003Cuploaded_url>\",\n    \"image_size\": \"landscape_16_9\"\n  }\n)\n```\n\n---\n\n## Video Generation\n\n### Seedance 1.0 Pro (ByteDance)\nBest for: text-to-video, image-to-video with high motion quality.\n\n```\ngenerate(\n  app_id: \"fal-ai\u002Fseedance-1-0-pro\",\n  input_data: {\n    \"prompt\": \"a drone flyover of a mountain lake at golden hour, cinematic\",\n    \"duration\": \"5s\",\n    \"aspect_ratio\": \"16:9\",\n    \"seed\": 42\n  }\n)\n```\n\n### Kling Video v3 Pro\nBest for: text\u002Fimage-to-video with native audio generation.\n\n```\ngenerate(\n  app_id: \"fal-ai\u002Fkling-video\u002Fv3\u002Fpro\",\n  input_data: {\n    \"prompt\": \"ocean waves crashing on a rocky coast, dramatic clouds\",\n    \"duration\": \"5s\",\n    \"aspect_ratio\": \"16:9\"\n  }\n)\n```\n\n### Veo 3 (Google DeepMind)\nBest for: video with generated sound, high visual quality.\n\n```\ngenerate(\n  app_id: \"fal-ai\u002Fveo-3\",\n  input_data: {\n    \"prompt\": \"a bustling Tokyo street market at night, neon signs, crowd noise\",\n    \"aspect_ratio\": \"16:9\"\n  }\n)\n```\n\n### Image-to-Video\nStart from an existing image:\n\n```\ngenerate(\n  app_id: \"fal-ai\u002Fseedance-1-0-pro\",\n  input_data: {\n    \"prompt\": \"camera slowly zooms out, gentle wind moves the trees\",\n    \"image_url\": \"\u003Cuploaded_image_url>\",\n    \"duration\": \"5s\"\n  }\n)\n```\n\n### Video Parameters\n\n| Param | Type | Options | Notes |\n|-------|------|---------|-------|\n| `prompt` | string | required | Describe the video |\n| `duration` | string | `\"5s\"`, `\"10s\"` | Video length |\n| `aspect_ratio` | string | `\"16:9\"`, `\"9:16\"`, `\"1:1\"` | Frame ratio |\n| `seed` | number | any integer | Reproducibility |\n| `image_url` | string | URL | Source image for image-to-video |\n\n---\n\n## Audio Generation\n\n### CSM-1B (Conversational Speech)\nText-to-speech with natural, conversational quality.\n\n```\ngenerate(\n  app_id: \"fal-ai\u002Fcsm-1b\",\n  input_data: {\n    \"text\": \"Hello, welcome to the demo. Let me show you how this works.\",\n    \"speaker_id\": 0\n  }\n)\n```\n\n### ThinkSound (Video-to-Audio)\nGenerate matching audio from video content.\n\n```\ngenerate(\n  app_id: \"fal-ai\u002Fthinksound\",\n  input_data: {\n    \"video_url\": \"\u003Cvideo_url>\",\n    \"prompt\": \"ambient forest sounds with birds chirping\"\n  }\n)\n```\n\n### ElevenLabs (via API, no MCP)\nFor professional voice synthesis, use ElevenLabs directly:\n\n```python\nimport os\nimport requests\n\nresp = requests.post(\n    \"https:\u002F\u002Fapi.elevenlabs.io\u002Fv1\u002Ftext-to-speech\u002F\u003Cvoice_id>\",\n    headers={\n        \"xi-api-key\": os.environ[\"ELEVENLABS_API_KEY\"],\n        \"Content-Type\": \"application\u002Fjson\"\n    },\n    json={\n        \"text\": \"Your text here\",\n        \"model_id\": \"eleven_turbo_v2_5\",\n        \"voice_settings\": {\"stability\": 0.5, \"similarity_boost\": 0.75}\n    }\n)\nwith open(\"output.mp3\", \"wb\") as f:\n    f.write(resp.content)\n```\n\n### VideoDB Generative Audio\nIf VideoDB is configured, use its generative audio:\n\n```python\n# Voice generation\naudio = coll.generate_voice(text=\"Your narration here\", voice=\"alloy\")\n\n# Music generation\nmusic = coll.generate_music(prompt=\"upbeat electronic background music\", duration=30)\n\n# Sound effects\nsfx = coll.generate_sound_effect(prompt=\"thunder crack followed by rain\")\n```\n\n---\n\n## Cost Estimation\n\nBefore generating, check estimated cost:\n\n```\nestimate_cost(\n  estimate_type: \"unit_price\",\n  endpoints: {\n    \"fal-ai\u002Fnano-banana-pro\": {\n      \"unit_quantity\": 1\n    }\n  }\n)\n```\n\n## Model Discovery\n\nFind models for specific tasks:\n\n```\nsearch(query: \"text to video\")\nfind(endpoint_ids: [\"fal-ai\u002Fseedance-1-0-pro\"])\nmodels()\n```\n\n## Tips\n\n- Use `seed` for reproducible results when iterating on prompts\n- Start with lower-cost models (Nano Banana 2) for prompt iteration, then switch to Pro for finals\n- For video, keep prompts descriptive but concise — focus on motion and scene\n- Image-to-video produces more controlled results than pure text-to-video\n- Check `estimate_cost` before running expensive video generations\n\n## Related Skills\n\n- `videodb` — Video processing, editing, and streaming\n- `video-editing` — AI-powered video editing workflows\n- `content-engine` — Content creation for social platforms\n",{"name":5,"origin":52,"description":7},"ECC","main","a298c929b6cbd662e1fce54302ce520d5ceea1a5",".agents\u002Fskills\u002Ffal-ai-media","https:\u002F\u002Fgithub.com\u002FPrekzursil\u002Fagent-skills-toolchain","https:\u002F\u002Fgithub.com\u002FPrekzursil","2026-11-02 14:30:57",{"source":8,"skillName":5,"commands":60,"prompt":70,"zipAvailable":71},[61,64,67],{"tool":62,"command":63},"npx","npx skills add Prekzursil\u002Fagent-skills-toolchain --skill fal-ai-media",{"tool":65,"command":66},"bunx","bunx skills add Prekzursil\u002Fagent-skills-toolchain --skill fal-ai-media",{"tool":68,"command":69},"pnpm","pnpm dlx skills add Prekzursil\u002Fagent-skills-toolchain --skill fal-ai-media","安装技能，技能地址：https:\u002F\u002Fgithub.com\u002FPrekzursil\u002Fagent-skills-toolchain\u002Fblob\u002Fmain\u002F.agents\u002Fskills\u002Ffal-ai-media\u002FSKILL.md",true,[],[74,95,121,148,162,177],{"skillNo":75,"name":76,"nameZh":6,"description":77,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":15,"licenseFileUrl":6,"sourceHtmlUrl":78,"categories":79,"keywords":80,"publishedAt":47},"01M6DF7D7478R55P46REYH4QAC","clarify-requirements","Resolve genuine pre-execution ambiguity by scanning repo context, generating 1-6 grounded options, and asking 1-3 focused questions via AskUserQuestion. NOT for mid-task use (injection risk); NOT when the goal is already unambiguous; use to disambiguate vague prompts before any file edits.","https:\u002F\u002Fgithub.com\u002FPrekzursil\u002Fagent-skills-toolchain\u002Fblob\u002Fmain\u002Ftools\u002Fworkspace-hooks\u002Fskills\u002Fclarify-requirements\u002FSKILL.md",[],[81,82,83,84,85,86,87,88,89,37,90,91,92,93,94],"clarify requirements","clarify","requirements","risk","options","task","prompts","goal","scanning","context","repo","injection","execution","file",{"skillNo":96,"name":97,"nameZh":6,"description":98,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":15,"licenseFileUrl":6,"sourceHtmlUrl":99,"categories":100,"keywords":102,"publishedAt":47},"01M6DF79CA4BHJS66J8EZDBPWJ","openmm-md","Run FREE, open-source, Windows-native GPU molecular dynamics via the openmm-md MCP (OpenMM + CUDA on the local NVIDIA GPU). Use for protein \u002F protein-ligand MD when you want a free stack or are on Windows without a Schrodinger license. Covers the full workflow (prepare, solvate, minimize, equilibrate, production, analyze, mmgbsa) AND an honest decision guide vs Schrodinger Desmond, including how to run Desmond legitimately on Linux or a cloud GPU with a real license. This is a deliberately LESSER free alternative and does NOT replace the schrodinger MCP tools. Do NOT use it to pick a free tool when a validated FEP+, WaterMap, IFD-MD, or Prime MM-GBSA result is actually required.","https:\u002F\u002Fgithub.com\u002FPrekzursil\u002Fagent-skills-toolchain\u002Fblob\u002Fmain\u002Ftools\u002Fmcp\u002Fopenmm-md-mcp\u002Fskill\u002Fopenmm-md\u002FSKILL.md",[101],{"categoryNo":24,"categoryName":25,"taxonomyType":21,"taxonomyTypeDesc":22},[103,104,105,106,107,108,109,110,111,112,113,114,115,116,37,117,118,119,120,39],"openmm md","how","decision","pick","linux","analyze","tool","stack","open","NVIDIA","gpu","license","workflow","windows","free","molecular dynamics","local","do",{"skillNo":122,"name":123,"nameZh":6,"description":124,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":15,"licenseFileUrl":6,"sourceHtmlUrl":125,"categories":126,"keywords":133,"publishedAt":47},"01M6DF76C1MG85VEWP8VZCBNMN","visual-review","Take screenshots of web pages and UI using Playwright for visual review and iteration","https:\u002F\u002Fgithub.com\u002FPrekzursil\u002Fagent-skills-toolchain\u002Fblob\u002Fmain\u002Ftools\u002Feditor\u002Fmetaswarm\u002Fskills\u002Fvisual-review\u002FSKILL.md",[127,130],{"categoryNo":128,"categoryName":129,"taxonomyType":21,"taxonomyTypeDesc":22},"01JBSEEDCAT000000000000003","演示文稿",{"categoryNo":131,"categoryName":132,"taxonomyType":21,"taxonomyTypeDesc":22},"01JBSEEDCAT000000000000008","测试与质量",[134,135,136,137,138,139,140,141,142,143,104,144,145,146,147],"review","visual","visual review","pages","web","false","iteration","take","check","slides","ui","screenshot","playwright","screenshots",{"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":154,"publishedAt":47},"01M6DF73AQVCBZKEN0YXEX9FXP","status","Diagnostic status report — shows metaswarm installation state, project setup, and potential issues","https:\u002F\u002Fgithub.com\u002FPrekzursil\u002Fagent-skills-toolchain\u002Fblob\u002Fmain\u002Ftools\u002Feditor\u002Fmetaswarm\u002Fskills\u002Fstatus\u002FSKILL.md",[],[150,155,156,157,158,159,160,161],"setup","report","project","installation","project setup","issues","state",{"skillNo":163,"name":164,"nameZh":6,"description":165,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":15,"licenseFileUrl":6,"sourceHtmlUrl":166,"categories":167,"keywords":169,"publishedAt":47},"01M6DF6X6C2XB0P6GX76P7TTYV","start","Use when starting work on any task, when the user mentions metaswarm, or when the user wants to begin tracked development work","https:\u002F\u002Fgithub.com\u002FPrekzursil\u002Fagent-skills-toolchain\u002Fblob\u002Fmain\u002Ftools\u002Feditor\u002Fmetaswarm\u002Fskills\u002Fstart\u002FSKILL.md",[168],{"categoryNo":24,"categoryName":25,"taxonomyType":21,"taxonomyTypeDesc":22},[164,170,86,171,172,173,37,38,174,175,176],"start issue","issue","ready","work on issue","work","work on","development",{"skillNo":178,"name":155,"nameZh":6,"description":179,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":15,"licenseFileUrl":6,"sourceHtmlUrl":180,"categories":181,"keywords":182,"publishedAt":47},"01M6DF6QMJ9AJKFKHHKRT005PQ","Interactive project setup — detects your project, configures metaswarm, writes project-local files","https:\u002F\u002Fgithub.com\u002FPrekzursil\u002Fagent-skills-toolchain\u002Fblob\u002Fmain\u002Ftools\u002Feditor\u002Fmetaswarm\u002Fskills\u002Fsetup\u002FSKILL.md",[],[155,157,119,183,159,184],"files","interactive"]