[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"skill:01M6GFJSWZHJZ9MRDMDT1PCBH4":3,"skill-same:01M6GFJSWZHJZ9MRDMDT1PCBH4":59},{"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":18,"publishedAt":30,"linkOnly":31,"markdownContent":32,"markdownBody":33,"frontMatter":34,"refName":37,"commitSha":38,"skillDirectory":39,"forksCount":40,"repositoryHtmlUrl":41,"repositoryHomepageUrl":6,"ownerHtmlUrl":42,"ownerBlogUrl":6,"ownerDescription":43,"updatedAt":44,"install":45,"resources":58},"01M6GFJSWZHJZ9MRDMDT1PCBH4","concise-communication",null,"Communicate concisely, match user's preferred tone and verbosity, avoid unnecessary formatting.","zapabob\u002FSkills","zapabob","https:\u002F\u002Favatars.githubusercontent.com\u002Fu\u002F130830376?v=4","01M6DBMYZAGRTFQDSQYW3W764P","峯岸 亮","01M6DBMZ3GKDSJ01NZ9XTZD7JD",2,"MIT","https:\u002F\u002Fgithub.com\u002Fzapabob\u002FSkills\u002Fblob\u002Fmain\u002Farchive\u002Fskill-md-reviewed\u002Fsha256\u002Fdb\u002Fdba544a5d1a925550b0aadb579be523b30caa19540124220018a99b0e6d8aa49\u002FSKILL.md",[],[19,20,21,22,23,24,25,26,27,28,29],"communication","concise communication","concise","hermes","hermes agent","user","tone","formatting","communicate","concisely","match","2026-11-10 10:12:30",false,"---\r\nname: concise-communication\r\ndescription: Communicate concisely, match user's preferred tone and verbosity, avoid unnecessary formatting.\r\nversion: 1.0.0\r\nauthor: Hermes Agent\r\nlicense: MIT\r\n---\r\n# Concise Communication Skill\r\n\r\nThis skill encodes the user's preferences for communication style, learned from session corrections.\r\n\r\n## Core Preferences\r\n- **Japanese language**: Respond in Japanese unless user switches language.\r\n- **Conciseness**: Provide the minimum necessary information. Avoid verbose explanations unless explicitly asked for detail.\r\n- **Formatting**: Use plain Japanese sentences; avoid excessive Markdown formatting (e.g., no need for bold, italics, lists unless they add clear value).\r\n- **Tone**: Friendly but direct, matching a casual yet helpful tone (e.g., \"ボブにゃん\").\r\n- **Verbosity**: If user says \"just give me the answer\" or \"stop doing X\", comply immediately.\r\n- **Confirmation**: Do not over-explain corrections; acknowledge and adjust.\r\n\r\n## Guidelines\r\n1. When user expresses frustration about verbosity, shorten the next response.\r\n2. If user asks for a URL or specific fact, provide it directly without preamble.\r\n3. Avoid repeating known context unless user requests a recap.\r\n4. Use simple sentence structures; prefer short paragraphs.\r\n5. If unsure, ask for clarification rather than guessing.\r\n6. When user asks to create or verify something, provide the minimal steps and then show the result of execution (e.g., command output) rather than just describing what would be done.\r\n\r\n## Time and schedules\r\n- Before saying next cron time or \"約N分後\", run `date` and use live JST. Do not invent next-run from chat memory.\r\n- If user says 「時間が違う」, re-check clock and correct briefly.\r\n- For cron management, use simple stop\u002Fstart commands as preferred by user. Avoid complex explanations unless asked.\r\n\r\n## Cron digests\r\n- When user says 「こんな感じにして」 for a cron digest, match that shape on later summaries of the same job.\r\n- Warashibe arb KPI line must stay: 利益≥¥500 かつ 利益率≥30%.\r\n\r\n## Pitfalls\r\n- Over-formatting with Markdown when plain text suffices.\r\n- Providing background information when user only asked for a result.\r\n- Using overly formal language when user prefers casual tone.\r\n- Stating next-run times without checking live clock (user: 「時間が違うよ」).\r\n\r\n---","# Concise Communication Skill\r\n\r\nThis skill encodes the user's preferences for communication style, learned from session corrections.\r\n\r\n## Core Preferences\r\n- **Japanese language**: Respond in Japanese unless user switches language.\r\n- **Conciseness**: Provide the minimum necessary information. Avoid verbose explanations unless explicitly asked for detail.\r\n- **Formatting**: Use plain Japanese sentences; avoid excessive Markdown formatting (e.g., no need for bold, italics, lists unless they add clear value).\r\n- **Tone**: Friendly but direct, matching a casual yet helpful tone (e.g., \"ボブにゃん\").\r\n- **Verbosity**: If user says \"just give me the answer\" or \"stop doing X\", comply immediately.\r\n- **Confirmation**: Do not over-explain corrections; acknowledge and adjust.\r\n\r\n## Guidelines\r\n1. When user expresses frustration about verbosity, shorten the next response.\r\n2. If user asks for a URL or specific fact, provide it directly without preamble.\r\n3. Avoid repeating known context unless user requests a recap.\r\n4. Use simple sentence structures; prefer short paragraphs.\r\n5. If unsure, ask for clarification rather than guessing.\r\n6. When user asks to create or verify something, provide the minimal steps and then show the result of execution (e.g., command output) rather than just describing what would be done.\r\n\r\n## Time and schedules\r\n- Before saying next cron time or \"約N分後\", run `date` and use live JST. Do not invent next-run from chat memory.\r\n- If user says 「時間が違う」, re-check clock and correct briefly.\r\n- For cron management, use simple stop\u002Fstart commands as preferred by user. Avoid complex explanations unless asked.\r\n\r\n## Cron digests\r\n- When user says 「こんな感じにして」 for a cron digest, match that shape on later summaries of the same job.\r\n- Warashibe arb KPI line must stay: 利益≥¥500 かつ 利益率≥30%.\r\n\r\n## Pitfalls\r\n- Over-formatting with Markdown when plain text suffices.\r\n- Providing background information when user only asked for a result.\r\n- Using overly formal language when user prefers casual tone.\r\n- Stating next-run times without checking live clock (user: 「時間が違うよ」).\r\n\r\n---",{"name":5,"author":35,"license":15,"version":36,"description":7},"Hermes Agent","1.0.0","main","0d1434f89f4bc6b07e9d272accd8c1013768820f","archive\u002Fskill-md-reviewed\u002Fsha256\u002Fdb\u002Fdba544a5d1a925550b0aadb579be523b30caa19540124220018a99b0e6d8aa49",0,"https:\u002F\u002Fgithub.com\u002Fzapabob\u002FSkills","https:\u002F\u002Fgithub.com\u002Fzapabob","The Open University of JAPAN　2019-now\r\n\r\nTokyo University of Science　2007-2010","2026-10-26 16:29:01",{"source":8,"skillName":5,"commands":46,"prompt":56,"zipAvailable":57},[47,50,53],{"tool":48,"command":49},"npx","npx skills add zapabob\u002FSkills --skill concise-communication",{"tool":51,"command":52},"bunx","bunx skills add zapabob\u002FSkills --skill concise-communication",{"tool":54,"command":55},"pnpm","pnpm dlx skills add zapabob\u002FSkills --skill concise-communication","安装技能，技能地址：https:\u002F\u002Fgithub.com\u002Fzapabob\u002FSkills\u002Fblob\u002Fmain\u002Farchive\u002Fskill-md-reviewed\u002Fsha256\u002Fdb\u002Fdba544a5d1a925550b0aadb579be523b30caa19540124220018a99b0e6d8aa49\u002FSKILL.md",true,[],[60,96,131,158,185,202],{"skillNo":61,"name":62,"nameZh":6,"description":63,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":15,"licenseFileUrl":6,"sourceHtmlUrl":64,"categories":65,"keywords":79,"publishedAt":30},"01M6GJTE1GESGGF9K028Y7753E","xurl","X\u002FTwitter via xurl CLI: post, search, DM, media, v2 API.","https:\u002F\u002Fgithub.com\u002Fzapabob\u002FSkills\u002Fblob\u002Fmain\u002Fregistry\u002Fskills\u002Fxurl\u002Fvariants\u002Fhermes-agent\u002FSKILL.md",[66,71,74],{"categoryNo":67,"categoryName":68,"taxonomyType":69,"taxonomyTypeDesc":70},"01JBSEEDCAT000000000000010","后端与接口","SCENARIO","使用场景",{"categoryNo":72,"categoryName":73,"taxonomyType":69,"taxonomyTypeDesc":70},"01JBSEEDCAT000000000000023","Skill与智能体开发",{"categoryNo":75,"categoryName":76,"taxonomyType":77,"taxonomyTypeDesc":78},"01JBSEEDCAT000000000000030","开发工程师","PROFESSION","适用职业",[62,80,81,82,83,84,85,86,87,88,89,90,91,22,23,92,37,93,94,95],"openclaw","macos","cli","github","linux","windows","official","search","https","social-media","api","Media","twitter","social","via","post",{"skillNo":97,"name":98,"nameZh":6,"description":99,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":15,"licenseFileUrl":6,"sourceHtmlUrl":100,"categories":101,"keywords":113,"publishedAt":30},"01M6GJT8S1PXQ8WPXT1HSNBWH2","writing-plans","Write implementation plans: bite-sized tasks, paths, code.","https:\u002F\u002Fgithub.com\u002Fzapabob\u002FSkills\u002Fblob\u002Fmain\u002Fregistry\u002Fskills\u002Fwriting-plans\u002Fvariants\u002Fhermes-agent\u002FSKILL.md",[102,105,108,109,110],{"categoryNo":103,"categoryName":104,"taxonomyType":69,"taxonomyTypeDesc":70},"01JBSEEDCAT000000000000015","视觉设计",{"categoryNo":106,"categoryName":107,"taxonomyType":69,"taxonomyTypeDesc":70},"01JBSEEDCAT000000000000018","写作与文案",{"categoryNo":72,"categoryName":73,"taxonomyType":69,"taxonomyTypeDesc":70},{"categoryNo":75,"categoryName":76,"taxonomyType":77,"taxonomyTypeDesc":78},{"categoryNo":111,"categoryName":112,"taxonomyType":77,"taxonomyTypeDesc":78},"01JBSEEDCAT000000000000036","内容创作者",[114,115,116,117,81,118,84,119,85,120,121,122,123,124,125,126,127,128,129,130],"writing","writing plans","plans","design","review","workflow","documentation","tasks","development","code","planning","code-review","subagent","write","superpowers","paths","test-driven-development",{"skillNo":132,"name":133,"nameZh":6,"description":134,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":15,"licenseFileUrl":6,"sourceHtmlUrl":135,"categories":136,"keywords":140,"publishedAt":30},"01M6GJST0H5X7WHBJ3BZK0DVKH","whisper","OpenAI's general-purpose speech recognition model. 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Best for robust, multilingual ASR.","https:\u002F\u002Fgithub.com\u002Fzapabob\u002FSkills\u002Fblob\u002Fmain\u002Fregistry\u002Fskills\u002Fwhisper\u002Fvariants\u002Fhermes-agent-optional\u002FSKILL.md",[137],{"categoryNo":138,"categoryName":139,"taxonomyType":69,"taxonomyTypeDesc":70},"01JBSEEDCAT000000000000016","图像与多媒体",[133,81,84,141,142,143,144,145,146,147,148,149,150,151,152,153,154,155,156,157],"openai","speech","multimodal","Transformers","ASR","Audio","text","model","speech recognition","use","general","multilingual","translation","english","identification","processing","Audio Processing",{"skillNo":159,"name":160,"nameZh":6,"description":161,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":15,"licenseFileUrl":6,"sourceHtmlUrl":162,"categories":163,"keywords":167,"publishedAt":30},"01M6GJSMRQ8EETZTYMG72P70EA","weights-and-biases","W&B: log ML experiments, sweeps, model registry, dashboards.","https:\u002F\u002Fgithub.com\u002Fzapabob\u002FSkills\u002Fblob\u002Fmain\u002Fregistry\u002Fskills\u002Fweights-and-biases\u002Fvariants\u002Fhermes-agent\u002FSKILL.md",[164],{"categoryNo":165,"categoryName":166,"taxonomyType":69,"taxonomyTypeDesc":70},"01JBSEEDCAT000000000000013","分析与可视化",[168,81,169,170,85,171,172,173,174,175,176,148,177,178,179,180,181,182,183,184],"weights and biases","tensorflow","experiments","pytorch","visualization","registry","real-time","tuning","dashboards","experiment","log","time","Experiment Tracking","Model Registry","Hyperparameter Tuning","WandB","Real-Time Visualization",{"skillNo":186,"name":187,"nameZh":6,"description":188,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":15,"licenseFileUrl":6,"sourceHtmlUrl":189,"categories":190,"keywords":192,"publishedAt":30},"01M6GJS19KDPRY112JTR326S06","watchers","Poll RSS, JSON APIs, and GitHub with watermark dedup.","https:\u002F\u002Fgithub.com\u002Fzapabob\u002FSkills\u002Fblob\u002Fmain\u002Fregistry\u002Fskills\u002Fwatchers\u002Fvariants\u002Fhermes-agent-optional\u002FSKILL.md",[191],{"categoryNo":72,"categoryName":73,"taxonomyType":69,"taxonomyTypeDesc":70},[187,81,193,83,84,194,195,196,197,198,199,22,23,200,201],"terminal","automation","http","monitoring","cron","json","rss","devops","with",{"skillNo":203,"name":204,"nameZh":6,"description":205,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":15,"licenseFileUrl":6,"sourceHtmlUrl":206,"categories":207,"keywords":210,"publishedAt":30},"01M6GJRHJD2A6Q830SWF9W48BC","serving-llms-vllm","vLLM: high-throughput LLM serving, OpenAI API, quantization.","https:\u002F\u002Fgithub.com\u002Fzapabob\u002FSkills\u002Fblob\u002Fmain\u002Fregistry\u002Fskills\u002Fvllm\u002Fvariants\u002Fhermes-agent\u002FSKILL.md",[208,209],{"categoryNo":67,"categoryName":68,"taxonomyType":69,"taxonomyTypeDesc":70},{"categoryNo":75,"categoryName":76,"taxonomyType":77,"taxonomyTypeDesc":78},[211,212,213,84,214,141,215,216,217,144,218,90,219,220,221,222,223,224,225,226],"llms","vLLM","serving llms vllm","research","openai api","tensor","Inference Serving","Production","llm serving","High Throughput","PagedAttention","Continuous Batching","Quantization","Tensor Parallelism","high-throughput","throughput"]