[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"skill:01M6GA0C96F07NMV6NZVCZ6HMN":3,"skill-same:01M6GA0C96F07NMV6NZVCZ6HMN":99},{"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":31,"publishedAt":52,"linkOnly":53,"markdownContent":54,"markdownBody":55,"frontMatter":56,"refName":77,"commitSha":78,"skillDirectory":79,"forksCount":80,"repositoryHtmlUrl":81,"repositoryHomepageUrl":6,"ownerHtmlUrl":82,"ownerBlogUrl":6,"ownerDescription":83,"updatedAt":84,"install":85,"resources":98},"01M6GA0C96F07NMV6NZVCZ6HMN","live-dashboard",null,"Build self-updating dashboards from live sources.","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\u002F82\u002F8232300ca251f11b485cc30b0306a3e9af8f75553545b7683e3951f470b67ac7\u002FSKILL.md",[18,23,26],{"categoryNo":19,"categoryName":20,"taxonomyType":21,"taxonomyTypeDesc":22},"01JBSEEDCAT000000000000013","分析与可视化","SCENARIO","使用场景",{"categoryNo":24,"categoryName":25,"taxonomyType":21,"taxonomyTypeDesc":22},"01JBSEEDCAT000000000000023","Skill与智能体开发",{"categoryNo":27,"categoryName":28,"taxonomyType":29,"taxonomyTypeDesc":30},"01JBSEEDCAT000000000000033","数据分析师","PROFESSION","适用职业",[32,33,34,35,36,37,38,39,40,41,42,43,44,45,46,47,48,49,50,51],"live dashboard","dashboard","live","Google-Workspace","respond","sources","self","only","good","html","short","directory","reporting","monitoring","product","inbox","run","status","change","google","2026-11-10 10:12:30",false,"---\nname: live-dashboard\ndescription: \"Build self-updating dashboards from live sources.\"\nversion: 0.2.0\nauthor: Teknium (teknium1), Hermes Agent\nlicense: MIT\nplatforms: [linux, macos, windows]\nmetadata:\n  hermes:\n    tags: [dashboards, monitoring, status, automation, reporting]\n    category: productivity\n    related_skills: [product-price-monitor, competitor-news-monitor, email-inbox-triage, google-workspace]\n    blueprint:\n      schedule: \"0 8 * * *\"\n      prompt: \"Load the live-dashboard skill and run the refresh tick for every dashboard.json under the Hermes home directory's dashboards\u002F folder. Mark failed reads stale without overwriting last-known-good values, regenerate each index.html from its state file, and deliver a short summary ONLY on material change or new needs-attention items — otherwise respond with [SILENT].\"\n---\n\n# Live Dashboard\n\nTurn one sentence — \"make a dashboard for our visa applications, update it daily from the email threads and the case-status site\" — into a persistent, self-refreshing status page. The user describes what they want to see; you define the data contract, build a self-contained HTML dashboard, verify one live refresh, then schedule the recurring tick.\n\nSetup runs once in the foreground; the recurring refresh runs as a `cronjob` tick. Installing this skill offers a daily all-dashboards sweep via `\u002Fsuggestions` (the frontmatter blueprint).\n\n## When to Use\n\n- \"Make a dashboard for \u003Cproject\u002Fprocess> and keep it updated.\"\n- \"I want one place to see the status of \u003Cdeals \u002F applications \u002F bugs \u002F shipments>.\"\n- \"Track \u003Cthing> across my email and \u003Cwebsite> and show me where it stands.\"\n- \"Show me the \u003Cslug> dashboard.\" (re-render\u002Fpreview an existing one)\n- A cron tick fires for an existing dashboard (steps 5-7).\n\nDon't use for: one-off status questions (answer directly), price\u002Favailability thresholds on a single item (use `product-price-monitor`), or company news tracking (use `competitor-news-monitor`).\n\n## Prerequisites\n\n- At least one source connector the dashboard will read from: email\u002Fcalendar via `himalaya` or `google-workspace`, websites via `web_extract` or `browser_navigate`, local files via `read_file`. If none is configured, renegotiate the sources in step 1 before writing any artifact.\n- `cronjob` for the recurring tick.\n- Optional: the `desktop_preview` tool (Hermes desktop app sessions). When it is in the toolset, dashboards render in the in-app preview pane; otherwise the user is given the file path.\n\n## Procedure — Setup (foreground, once)\n\n### 1. Define the dashboard contract\n\nFrom the user's sentence, pin down: the dashboard's purpose in one line, the entities being tracked (rows), the fields per entity (columns\u002Findicators), what \"needs attention\" means, the sources each field is read from, and the refresh cadence. Ask about anything ambiguous — a dashboard that tracks the wrong grain is worthless. Done when every field on the dashboard names the source it will be read from.\n\n### 2. Verify each source with one live read\n\nFor each source, do one bounded foreground read now: email\u002Fcalendar via the connector skills (`himalaya`, `google-workspace`), websites via `web_extract` or `browser_navigate`, local files via `read_file`. Record what was actually retrievable — auth walls, missing permissions, or empty results surface here, not on the first scheduled run. Drop or replace sources that fail. Done when every field's source returned real data or was explicitly renegotiated with the user.\n\n### 3. Build the dashboard artifact\n\nWrite two files under the Hermes home directory's `dashboards\u002F\u003Cslug>\u002F` (the same directory that holds `config.yaml`; never assume a fixed location):\n\n- `dashboard.json` — the contract plus current state: purpose, entities, per-field values, per-field source + retrieval timestamp, a `needs_attention` list, and a change log (append-only, most recent first).\n- `index.html` — a single self-contained HTML page (inline CSS, no external requests) rendering the state: a header with purpose and last-updated time, a \"Needs attention\" section on top, the entity table, and the recent-changes list. Regenerate it from `dashboard.json` on every refresh; never hand-edit HTML state.\n\nPopulate both from the step-2 reads, then show the result (step 8). Done when the page renders the live data and every value on it carries a retrieval timestamp in `dashboard.json`.\n\n### 4. Schedule the refresh\n\nOnly after step 3 succeeded, schedule the tick. If the daily all-dashboards sweep from `\u002Fsuggestions` is already scheduled and its cadence suits, it will pick this dashboard up — say so and stop. Otherwise create a per-dashboard job whose prompt names the state file:\n\n```\ncronjob(action=\"create\",\n        schedule=\u003Ccadence from the contract, e.g. \"0 8 * * *\">,\n        prompt=\"Load the live-dashboard skill and run the refresh tick for the dashboard at \u003Cabsolute path to dashboards\u002F\u003Cslug>\u002Fdashboard.json>.\",\n        deliver=\u003Cuser's destination>)\n```\n\nPick a cadence that respects source rate limits. Done when a job covering this dashboard exists and its prompt names the state-file path (or the sweep).\n\n## Procedure — Tick (each scheduled run)\n\n### 5. Re-read sources and diff\n\nLoad `dashboard.json` (for the sweep: every `dashboards\u002F*\u002Fdashboard.json`, one at a time), re-read each field from its named source, and compute a field-level diff against the stored state. A failed source read means unknown state: keep the last good value, mark the field stale with the failure time, and never overwrite good data with an error. Done when every field is either updated, unchanged, or explicitly marked stale.\n\n### 6. Update state and re-render\n\nApply the diff to `dashboard.json`: update values and timestamps, append material changes to the change log, and recompute `needs_attention` against the contract's attention rules. Regenerate `index.html` from the updated state, then show the result (step 8). Done when the JSON and HTML agree and the change log entry for this run exists (or the run is recorded as no-change).\n\n### 7. Deliver on material change, else stay silent\n\nIf the diff contains material changes or new needs-attention items, deliver a short summary: what changed, what needs attention, and where the dashboard is. Otherwise respond with `[SILENT]` — no \"still watching\" noise unless the user asked for a periodic digest. Done when delivery matches the diff.\n\n## Procedure — Show the dashboard (after every build or re-render, and on request)\n\n### 8. Render where the user can see it\n\n- Desktop\u002FGUI session (`desktop_preview` is in the toolset): `desktop_preview(action=\"open\", url=\u003Cabsolute path to index.html>, label=\u003Cdashboard purpose>)` so the page renders live in the preview pane beside the chat; re-open after each re-render so the pane shows the new state.\n- Any other session (CLI, messenger, cron tick without a GUI): report the absolute path of `index.html` and offer to open it where the platform allows.\n\nDone when the user has either seen the rendered page or been told exactly where it lives.\n\n## Pitfalls\n\n- Building the page before verifying the sources — auth failures then surface on an unattended run.\n- Overwriting last-known-good values with an error page or empty read.\n- Rendering state into HTML only — `dashboard.json` is the source of truth; HTML is a projection.\n- Alerting on every refresh instead of on material change.\n- Tracking the wrong grain (per-thread when the user thinks per-application).\n- Hardcoding the Hermes home path — resolve it from the running install (the directory holding `config.yaml`) and write absolute paths into cron prompts.\n- Calling `desktop_preview` outside a desktop session — it is only in the toolset for GUI sessions; fall back to the path.\n\n## Verification\n\n- [ ] Every dashboard field names its source, and each source passed one foreground read before scheduling.\n- [ ] `dashboard.json` and `index.html` exist and agree; every value carries a retrieval timestamp.\n- [ ] Failed reads marked fields stale without destroying last-known-good state.\n- [ ] Ticks deliver only on material change; no-change runs were `[SILENT]`.\n- [ ] The change log replays the dashboard's history from the state file alone.\n- [ ] The dashboard was shown in the preview pane (desktop) or its path reported (elsewhere).\n","# Live Dashboard\n\nTurn one sentence — \"make a dashboard for our visa applications, update it daily from the email threads and the case-status site\" — into a persistent, self-refreshing status page. The user describes what they want to see; you define the data contract, build a self-contained HTML dashboard, verify one live refresh, then schedule the recurring tick.\n\nSetup runs once in the foreground; the recurring refresh runs as a `cronjob` tick. Installing this skill offers a daily all-dashboards sweep via `\u002Fsuggestions` (the frontmatter blueprint).\n\n## When to Use\n\n- \"Make a dashboard for \u003Cproject\u002Fprocess> and keep it updated.\"\n- \"I want one place to see the status of \u003Cdeals \u002F applications \u002F bugs \u002F shipments>.\"\n- \"Track \u003Cthing> across my email and \u003Cwebsite> and show me where it stands.\"\n- \"Show me the \u003Cslug> dashboard.\" (re-render\u002Fpreview an existing one)\n- A cron tick fires for an existing dashboard (steps 5-7).\n\nDon't use for: one-off status questions (answer directly), price\u002Favailability thresholds on a single item (use `product-price-monitor`), or company news tracking (use `competitor-news-monitor`).\n\n## Prerequisites\n\n- At least one source connector the dashboard will read from: email\u002Fcalendar via `himalaya` or `google-workspace`, websites via `web_extract` or `browser_navigate`, local files via `read_file`. If none is configured, renegotiate the sources in step 1 before writing any artifact.\n- `cronjob` for the recurring tick.\n- Optional: the `desktop_preview` tool (Hermes desktop app sessions). When it is in the toolset, dashboards render in the in-app preview pane; otherwise the user is given the file path.\n\n## Procedure — Setup (foreground, once)\n\n### 1. Define the dashboard contract\n\nFrom the user's sentence, pin down: the dashboard's purpose in one line, the entities being tracked (rows), the fields per entity (columns\u002Findicators), what \"needs attention\" means, the sources each field is read from, and the refresh cadence. Ask about anything ambiguous — a dashboard that tracks the wrong grain is worthless. Done when every field on the dashboard names the source it will be read from.\n\n### 2. Verify each source with one live read\n\nFor each source, do one bounded foreground read now: email\u002Fcalendar via the connector skills (`himalaya`, `google-workspace`), websites via `web_extract` or `browser_navigate`, local files via `read_file`. Record what was actually retrievable — auth walls, missing permissions, or empty results surface here, not on the first scheduled run. Drop or replace sources that fail. Done when every field's source returned real data or was explicitly renegotiated with the user.\n\n### 3. Build the dashboard artifact\n\nWrite two files under the Hermes home directory's `dashboards\u002F\u003Cslug>\u002F` (the same directory that holds `config.yaml`; never assume a fixed location):\n\n- `dashboard.json` — the contract plus current state: purpose, entities, per-field values, per-field source + retrieval timestamp, a `needs_attention` list, and a change log (append-only, most recent first).\n- `index.html` — a single self-contained HTML page (inline CSS, no external requests) rendering the state: a header with purpose and last-updated time, a \"Needs attention\" section on top, the entity table, and the recent-changes list. Regenerate it from `dashboard.json` on every refresh; never hand-edit HTML state.\n\nPopulate both from the step-2 reads, then show the result (step 8). Done when the page renders the live data and every value on it carries a retrieval timestamp in `dashboard.json`.\n\n### 4. Schedule the refresh\n\nOnly after step 3 succeeded, schedule the tick. If the daily all-dashboards sweep from `\u002Fsuggestions` is already scheduled and its cadence suits, it will pick this dashboard up — say so and stop. Otherwise create a per-dashboard job whose prompt names the state file:\n\n```\ncronjob(action=\"create\",\n        schedule=\u003Ccadence from the contract, e.g. \"0 8 * * *\">,\n        prompt=\"Load the live-dashboard skill and run the refresh tick for the dashboard at \u003Cabsolute path to dashboards\u002F\u003Cslug>\u002Fdashboard.json>.\",\n        deliver=\u003Cuser's destination>)\n```\n\nPick a cadence that respects source rate limits. Done when a job covering this dashboard exists and its prompt names the state-file path (or the sweep).\n\n## Procedure — Tick (each scheduled run)\n\n### 5. Re-read sources and diff\n\nLoad `dashboard.json` (for the sweep: every `dashboards\u002F*\u002Fdashboard.json`, one at a time), re-read each field from its named source, and compute a field-level diff against the stored state. A failed source read means unknown state: keep the last good value, mark the field stale with the failure time, and never overwrite good data with an error. Done when every field is either updated, unchanged, or explicitly marked stale.\n\n### 6. Update state and re-render\n\nApply the diff to `dashboard.json`: update values and timestamps, append material changes to the change log, and recompute `needs_attention` against the contract's attention rules. Regenerate `index.html` from the updated state, then show the result (step 8). Done when the JSON and HTML agree and the change log entry for this run exists (or the run is recorded as no-change).\n\n### 7. Deliver on material change, else stay silent\n\nIf the diff contains material changes or new needs-attention items, deliver a short summary: what changed, what needs attention, and where the dashboard is. Otherwise respond with `[SILENT]` — no \"still watching\" noise unless the user asked for a periodic digest. Done when delivery matches the diff.\n\n## Procedure — Show the dashboard (after every build or re-render, and on request)\n\n### 8. Render where the user can see it\n\n- Desktop\u002FGUI session (`desktop_preview` is in the toolset): `desktop_preview(action=\"open\", url=\u003Cabsolute path to index.html>, label=\u003Cdashboard purpose>)` so the page renders live in the preview pane beside the chat; re-open after each re-render so the pane shows the new state.\n- Any other session (CLI, messenger, cron tick without a GUI): report the absolute path of `index.html` and offer to open it where the platform allows.\n\nDone when the user has either seen the rendered page or been told exactly where it lives.\n\n## Pitfalls\n\n- Building the page before verifying the sources — auth failures then surface on an unattended run.\n- Overwriting last-known-good values with an error page or empty read.\n- Rendering state into HTML only — `dashboard.json` is the source of truth; HTML is a projection.\n- Alerting on every refresh instead of on material change.\n- Tracking the wrong grain (per-thread when the user thinks per-application).\n- Hardcoding the Hermes home path — resolve it from the running install (the directory holding `config.yaml`) and write absolute paths into cron prompts.\n- Calling `desktop_preview` outside a desktop session — it is only in the toolset for GUI sessions; fall back to the path.\n\n## Verification\n\n- [ ] Every dashboard field names its source, and each source passed one foreground read before scheduling.\n- [ ] `dashboard.json` and `index.html` exist and agree; every value carries a retrieval timestamp.\n- [ ] Failed reads marked fields stale without destroying last-known-good state.\n- [ ] Ticks deliver only on material change; no-change runs were `[SILENT]`.\n- [ ] The change log replays the dashboard's history from the state file alone.\n- [ ] The dashboard was shown in the preview pane (desktop) or its path reported (elsewhere).\n",{"name":5,"author":57,"license":15,"version":58,"metadata":59,"platforms":73,"description":7},"Teknium (teknium1), Hermes Agent","0.2.0",{"hermes":60},{"tags":61,"category":64,"blueprint":65,"related_skills":68},[62,45,49,63,44],"dashboards","automation","productivity",{"prompt":66,"schedule":67},"Load the live-dashboard skill and run the refresh tick for every dashboard.json under the Hermes home directory's dashboards\u002F folder. Mark failed reads stale without overwriting last-known-good values, regenerate each index.html from its state file, and deliver a short summary ONLY on material change or new needs-attention items — otherwise respond with [SILENT].","0 8 * * *",[69,70,71,72],"product-price-monitor","competitor-news-monitor","email-inbox-triage","google-workspace",[74,75,76],"linux","macos","windows","main","0d1434f89f4bc6b07e9d272accd8c1013768820f","archive\u002Fskill-md-reviewed\u002Fsha256\u002F82\u002F8232300ca251f11b485cc30b0306a3e9af8f75553545b7683e3951f470b67ac7",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":86,"prompt":96,"zipAvailable":97},[87,90,93],{"tool":88,"command":89},"npx","npx skills add zapabob\u002FSkills --skill live-dashboard",{"tool":91,"command":92},"bunx","bunx skills add zapabob\u002FSkills --skill live-dashboard",{"tool":94,"command":95},"pnpm","pnpm dlx skills add zapabob\u002FSkills --skill live-dashboard","安装技能，技能地址：https:\u002F\u002Fgithub.com\u002Fzapabob\u002FSkills\u002Fblob\u002Fmain\u002Farchive\u002Fskill-md-reviewed\u002Fsha256\u002F82\u002F8232300ca251f11b485cc30b0306a3e9af8f75553545b7683e3951f470b67ac7\u002FSKILL.md",true,[],[100,129,164,191,215,230],{"skillNo":101,"name":102,"nameZh":6,"description":103,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":15,"licenseFileUrl":6,"sourceHtmlUrl":104,"categories":105,"keywords":113,"publishedAt":52},"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",[106,109,110],{"categoryNo":107,"categoryName":108,"taxonomyType":21,"taxonomyTypeDesc":22},"01JBSEEDCAT000000000000010","后端与接口",{"categoryNo":24,"categoryName":25,"taxonomyType":21,"taxonomyTypeDesc":22},{"categoryNo":111,"categoryName":112,"taxonomyType":29,"taxonomyTypeDesc":30},"01JBSEEDCAT000000000000030","开发工程师",[102,114,75,115,116,74,76,117,118,119,120,121,122,123,124,125,77,126,127,128],"openclaw","cli","github","official","search","https","social-media","api","Media","hermes","hermes agent","twitter","social","via","post",{"skillNo":130,"name":131,"nameZh":6,"description":132,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":15,"licenseFileUrl":6,"sourceHtmlUrl":133,"categories":134,"keywords":146,"publishedAt":52},"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",[135,138,141,142,143],{"categoryNo":136,"categoryName":137,"taxonomyType":21,"taxonomyTypeDesc":22},"01JBSEEDCAT000000000000015","视觉设计",{"categoryNo":139,"categoryName":140,"taxonomyType":21,"taxonomyTypeDesc":22},"01JBSEEDCAT000000000000018","写作与文案",{"categoryNo":24,"categoryName":25,"taxonomyType":21,"taxonomyTypeDesc":22},{"categoryNo":111,"categoryName":112,"taxonomyType":29,"taxonomyTypeDesc":30},{"categoryNo":144,"categoryName":145,"taxonomyType":29,"taxonomyTypeDesc":30},"01JBSEEDCAT000000000000036","内容创作者",[147,148,149,150,75,151,74,152,76,153,154,155,156,157,158,159,160,161,162,163],"writing","writing plans","plans","design","review","workflow","documentation","tasks","development","code","planning","code-review","subagent","write","superpowers","paths","test-driven-development",{"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":173,"publishedAt":52},"01M6GJST0H5X7WHBJ3BZK0DVKH","whisper","OpenAI's general-purpose speech recognition model. Supports 99 languages, transcription, translation to English, and language identification. Six model sizes from tiny (39M params) to large (1550M params). Use for speech-to-text, podcast transcription, or multilingual audio processing. Best for robust, multilingual ASR.","https:\u002F\u002Fgithub.com\u002Fzapabob\u002FSkills\u002Fblob\u002Fmain\u002Fregistry\u002Fskills\u002Fwhisper\u002Fvariants\u002Fhermes-agent-optional\u002FSKILL.md",[170],{"categoryNo":171,"categoryName":172,"taxonomyType":21,"taxonomyTypeDesc":22},"01JBSEEDCAT000000000000016","图像与多媒体",[166,75,74,174,175,176,177,178,179,180,181,182,183,184,185,186,187,188,189,190],"openai","speech","multimodal","Transformers","ASR","Audio","text","model","speech recognition","use","general","multilingual","translation","english","identification","processing","Audio Processing",{"skillNo":192,"name":193,"nameZh":6,"description":194,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":15,"licenseFileUrl":6,"sourceHtmlUrl":195,"categories":196,"keywords":198,"publishedAt":52},"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",[197],{"categoryNo":19,"categoryName":20,"taxonomyType":21,"taxonomyTypeDesc":22},[199,75,200,201,76,202,203,204,205,206,62,181,207,208,209,210,211,212,213,214],"weights and biases","tensorflow","experiments","pytorch","visualization","registry","real-time","tuning","experiment","log","time","Experiment Tracking","Model Registry","Hyperparameter Tuning","WandB","Real-Time Visualization",{"skillNo":216,"name":217,"nameZh":6,"description":218,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":15,"licenseFileUrl":6,"sourceHtmlUrl":219,"categories":220,"keywords":222,"publishedAt":52},"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",[221],{"categoryNo":24,"categoryName":25,"taxonomyType":21,"taxonomyTypeDesc":22},[217,75,223,116,74,63,224,45,225,226,227,123,124,228,229],"terminal","http","cron","json","rss","devops","with",{"skillNo":231,"name":232,"nameZh":6,"description":233,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":15,"licenseFileUrl":6,"sourceHtmlUrl":234,"categories":235,"keywords":238,"publishedAt":52},"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",[236,237],{"categoryNo":107,"categoryName":108,"taxonomyType":21,"taxonomyTypeDesc":22},{"categoryNo":111,"categoryName":112,"taxonomyType":29,"taxonomyTypeDesc":30},[239,240,241,74,242,174,243,244,245,177,246,121,247,248,249,250,251,252,253,254],"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"]