[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"skill:01M6GGSQGJXADV711Z28CMPN8W":3,"skill-same:01M6GGSQGJXADV711Z28CMPN8W":71},{"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":44,"linkOnly":45,"markdownContent":46,"markdownBody":47,"frontMatter":48,"refName":49,"commitSha":50,"skillDirectory":51,"forksCount":52,"repositoryHtmlUrl":53,"repositoryHomepageUrl":6,"ownerHtmlUrl":54,"ownerBlogUrl":6,"ownerDescription":55,"updatedAt":56,"install":57,"resources":70},"01M6GGSQGJXADV711Z28CMPN8W","nemoclaw-user-get-started",null,"Installs NemoClaw, launches a sandbox, and runs the first agent prompt. Use when onboarding, installing, or launching a NemoClaw sandbox for the first time. Trigger keywords - nemoclaw quickstart, install nemoclaw openclaw sandbox, nemohermes quickstart, hermes agent nemoclaw, run hermes openshell sandbox, nemoclaw prerequisites, nemoclaw supported platforms, nemoclaw hardware software, nemoclaw windows wsl2 setup, nemoclaw install windows docker desktop.","zapabob\u002FSkills","zapabob","https:\u002F\u002Favatars.githubusercontent.com\u002Fu\u002F130830376?v=4","01M6DBMYZAGRTFQDSQYW3W764P","峯岸 亮","01M6DBMZ3GKDSJ01NZ9XTZD7JD",2,"Apache-2.0","https:\u002F\u002Fgithub.com\u002Fzapabob\u002FSkills\u002Fblob\u002Fmain\u002Farchive\u002Fskill-md-reviewed\u002Fsha256\u002Ff0\u002Ff0be3e455e3447a0bc1d253ce0f4eda45d8a42ffb4220188b00745be8fce2edd\u002FSKILL.md",[18],{"categoryNo":19,"categoryName":20,"taxonomyType":21,"taxonomyTypeDesc":22},"01JBSEEDCAT000000000000023","Skill与智能体开发","SCENARIO","使用场景",[24,25,26,27,28,29,30,31,32,33,34,35,36,37,38,39,40,41,42,43],"get started","get","nemoclaw user get started","user","prompt","nemoclaw quickstart","trigger","software","time","use","install","docker","hermes agent","hermes","first","quickstart","desktop","run","windows","sandbox","2026-11-10 10:12:30",false,"---\nname: \"nemoclaw-user-get-started\"\ndescription: \"Installs NemoClaw, launches a sandbox, and runs the first agent prompt. Use when onboarding, installing, or launching a NemoClaw sandbox for the first time. Trigger keywords - nemoclaw quickstart, install nemoclaw openclaw sandbox, nemohermes quickstart, hermes agent nemoclaw, run hermes openshell sandbox, nemoclaw prerequisites, nemoclaw supported platforms, nemoclaw hardware software, nemoclaw windows wsl2 setup, nemoclaw install windows docker desktop.\"\nlicense: \"Apache-2.0\"\n---\n# NemoClaw Quickstart with OpenClaw\n\nFollow these steps to get started with NemoClaw and your first sandboxed OpenClaw agent.\n\n**Note:**\n\nMake sure you have completed reviewing the [Prerequisites](references\u002Fprerequisites.md) before following this guide.\n\n## Install NemoClaw and Onboard OpenClaw Agent\n\nDownload and run the installer script.\nThe script installs Node.js if it is not already present, then runs the guided onboard wizard to create a sandbox, configure inference, and apply security policies.\n\n**Note:**\n\nNemoClaw creates a fresh OpenClaw instance inside the sandbox during the onboarding process.\n\n```bash\ncurl -fsSL https:\u002F\u002Fwww.nvidia.com\u002Fnemoclaw.sh | bash\n```\n\nThe piped installer prompts through your terminal. In headless scripts or CI,\npass explicit acceptance to the `bash` side of the pipe:\n\n```console\n$ curl -fsSL https:\u002F\u002Fwww.nvidia.com\u002Fnemoclaw.sh | NEMOCLAW_NON_INTERACTIVE=1 NEMOCLAW_ACCEPT_THIRD_PARTY_SOFTWARE=1 bash\n```\n\nIf you use nvm or fnm to manage Node.js, the installer might not update your current shell's PATH.\nIf `nemoclaw` is not found after install, run `source ~\u002F.bashrc` (or `source ~\u002F.zshrc` for zsh) or open a new terminal.\n\nOn Linux, the installer checks Docker before it installs NemoClaw.\nIf Docker is missing, the installer downloads the official Docker convenience script, asks for `sudo`, installs Docker, and starts the Docker service when systemd is available.\nIf Docker is installed but your current shell cannot use the Docker socket yet, the installer adds your user to the `docker` group when needed and exits with a recovery command.\n\nOn macOS, the installer uses the Docker-driver OpenShell gateway path with Docker Desktop or Colima.\n\n```console\n$ newgrp docker\n$ curl -fsSL https:\u002F\u002Fwww.nvidia.com\u002Fnemoclaw.sh | bash\n```\n\nOn DGX Spark, DGX Station, and Windows WSL, an interactive installer offers express install after you accept the third-party software notice.\nExpress install switches onboarding to non-interactive mode, allows `sudo` password prompts for required host changes, and selects the managed local inference path for that platform.\nUnless `NEMOCLAW_POLICY_TIER` is set, it applies sandbox policy in `suggested` mode with the `balanced` tier by default, using the base sandbox policy plus supported package, model, web-search, and local-inference presets.\nOn WSL, express install selects the Windows-host Ollama setup path.\nSet `NEMOCLAW_NO_EXPRESS=1` to skip the express prompt, or set `NEMOCLAW_PROVIDER` before launching the installer when you want to choose a provider yourself.\n\nThe installer auto-launches `nemoclaw onboard` when it can locate the freshly-installed binary.\nIf it cannot locate the binary, or if blocking host preflight checks fail, it does not launch the wizard automatically.\nIn that case, the installer prints the relevant diagnostics and a `To finish setup, run:` block with the explicit `nemoclaw onboard` command.\n\n**Note:**\n\nThe onboard flow builds the sandbox image with `NEMOCLAW_DISABLE_DEVICE_AUTH=1` so the dashboard is immediately usable during setup.\nThis is a build-time setting baked into the sandbox image, not a runtime knob.\nIf you export `NEMOCLAW_DISABLE_DEVICE_AUTH` after onboarding finishes, it has no effect on an existing sandbox.\n\n### Review the Configuration Before the Sandbox Build\n\nAfter you enter the sandbox name, the wizard prints a review summary and asks for final confirmation before registering the provider, prompting for optional integrations, and building the sandbox image.\nFor example, if you picked an OpenAI-compatible endpoint, the summary looks like the following:\n\n```text\n  ──────────────────────────────────────────────────\n  Review configuration\n  ──────────────────────────────────────────────────\n  Provider:      compatible-endpoint\n  Model:         openai\u002Fopenai\u002Fgpt-5.5\n  API key:       COMPATIBLE_API_KEY (staged for OpenShell gateway registration)\n  Web search:    disabled\n  Messaging:     none\n  Sandbox name:  my-gpt-claw\n  Note:          Sandbox build typically takes 5–15 minutes on this host.\n  ──────────────────────────────────────────────────\n  Web search and messaging channels will be prompted next.\n  Apply this configuration? [Y\u002Fn]:\n```\n\nThe default is `Y`, so you can press Enter once to continue. Answer `n` to abort cleanly, fix the entries, and re-run `nemoclaw onboard`.\n\nNon-interactive runs (`NEMOCLAW_NON_INTERACTIVE=1`) print the summary for log clarity but skip the prompt.\n\n### Configure Web Search and Messaging\n\nAfter you confirm the summary, NemoClaw registers the selected provider with the OpenShell gateway and sets the `inference.local` route.\nThe wizard then asks whether to enable Brave Web Search.\nIf you enable it, enter a Brave Search API key when prompted.\n\nThe wizard also offers messaging channels such as Telegram, Discord, Slack, WeChat, and WhatsApp.\nPress a channel number to toggle it, then press Enter to continue.\nIf you select a channel, NemoClaw validates the token format before it bakes the channel configuration into the sandbox.\nFor example, Slack bot tokens must start with `xoxb-`.\nWeChat and WhatsApp are experimental.\nReview Messaging Channels (use the `nemoclaw-user-manage-sandboxes` skill) before enabling them.\n\n### Choose Network Policy Presets\n\nAfter the sandbox image builds and OpenClaw starts inside the sandbox, NemoClaw asks which network policy tier to apply.\nThe default **Balanced** tier includes common development presets such as npm, PyPI, Hugging Face, Homebrew, and Brave Search when the selected agent supports web search.\nUse the arrow keys or `j` and `k` to move, Space to select, and Enter to confirm.\n\nThe preset selector lets you include more destinations, such as GitHub, Jira, Slack, Telegram, or local inference.\nPress `r` to toggle a selected preset between read-only and read-write when the preset supports both modes.\n\nWhen the install completes, a summary confirms the running environment.\nBefore printing the summary, NemoClaw verifies that the sandbox gateway and dashboard port forward are reachable.\nInference route and messaging bridge checks are reported as warnings when they need more time or additional configuration.\nThe `Model` and provider line reflects the inference option you picked during onboarding.\nThe example below shows the result if you picked an OpenAI-compatible endpoint during onboarding.\n\n```text\n──────────────────────────────────────────────────\nNemoClaw is ready\n\nSandbox:  my-gpt-claw\nModel:    openai\u002Fopenai\u002Fgpt-5.5 (Other OpenAI-compatible endpoint)\n\nStart chatting\n\n  Browser:\n    http:\u002F\u002F127.0.0.1:18789\u002F\n\n  Terminal:\n    nemoclaw my-gpt-claw connect\n    then run: openclaw tui\n\nAuthenticated dashboard URL, if needed:\n  nemoclaw my-gpt-claw dashboard-url --quiet\n\nManage later\n\n  Status:      nemoclaw my-gpt-claw status\n  Logs:        nemoclaw my-gpt-claw logs --follow\n  Model:       nemoclaw inference set --model \u003Cmodel> --provider \u003Cprovider> --sandbox my-gpt-claw\n  Policies:    nemoclaw my-gpt-claw policy-add\n  Credentials: nemoclaw credentials reset \u003CKEY> && nemoclaw onboard\n──────────────────────────────────────────────────\n\n[INFO]  === Installation complete ===\n```\n\nIf you picked a different option, the `Model` line shows that provider's model and label instead. For example, you might see `gpt-5.4 (OpenAI)`, `claude-sonnet-4-6 (Anthropic)`, `gemini-2.5-flash (Google Gemini)`, `llama3.1:8b (Local Ollama)`, `nvidia-routed (Model Router)`, or `\u003Cyour-model> (Other OpenAI-compatible endpoint)`.\n\nLoad [references\u002Fquickstart-details.md](references\u002Fquickstart-details.md) for detailed steps on Respond to the Onboard Wizard.\n\n## Run Your First Agent Prompt\n\nYou can chat with the agent from the terminal or the browser.\n\n### Open the OpenClaw UI in a Browser to Chat with the Agent\n\nThe onboard wizard starts a background port forward to the sandbox dashboard, then prints the dashboard URL in the install summary.\nThe default host port is `18789`.\nIf that port is already taken, NemoClaw uses the next free dashboard port, such as `18790`, and prints that port in the final URL.\nIf the chosen port becomes occupied after the sandbox build starts, onboarding rolls back the newly-created sandbox and asks you to retry instead of printing an unreachable dashboard URL.\nThe install transcript does not print the gateway token.\nIf the browser requires authentication, use the `dashboard-url --quiet` command to print a complete URL explicitly.\n\n```text\nnemoclaw my-gpt-claw dashboard-url --quiet\n```\n\nOpen the dashboard URL in your browser.\nIf the browser asks for authentication, run `nemoclaw my-gpt-claw dashboard-url --quiet` and open the returned URL.\nTreat the authenticated URL like a password.\n\n### Chat with the Agent from the Terminal\n\nConnect to the sandbox and use the OpenClaw CLI.\n\n```bash\nnemoclaw my-assistant connect\n# inside the sandbox:\nopenclaw tui\n```\n\n## References\n\n- **Load [references\u002Fquickstart-hermes.md](references\u002Fquickstart-hermes.md)** when users ask for Hermes setup, NemoHermes onboarding, or running Hermes inside OpenShell. Installs NemoClaw, selects the Hermes agent, and launches a sandboxed Hermes API endpoint.\n- **Load [references\u002Fprerequisites.md](references\u002Fprerequisites.md)** when verifying prerequisites before installation. Lists the hardware, software, and container runtime requirements for running NemoClaw.\n- **Load [references\u002Fwindows-preparation.md](references\u002Fwindows-preparation.md)** when preparing a Windows machine for NemoClaw, enabling WSL 2, configuring Docker Desktop for Windows, or troubleshooting a Windows-specific install error. Covers Windows-only preparation steps required before the Quickstart.\n- **Load [references\u002Fquickstart-details.md](references\u002Fquickstart-details.md)** when you need detailed steps for Respond to the Onboard Wizard.\n\n## Related Skills\n\n- `nemoclaw-user-overview` — NemoClaw Overview (use the `nemoclaw-user-overview` skill) to learn what NemoClaw is and its capabilities\n","# NemoClaw Quickstart with OpenClaw\n\nFollow these steps to get started with NemoClaw and your first sandboxed OpenClaw agent.\n\n**Note:**\n\nMake sure you have completed reviewing the [Prerequisites](references\u002Fprerequisites.md) before following this guide.\n\n## Install NemoClaw and Onboard OpenClaw Agent\n\nDownload and run the installer script.\nThe script installs Node.js if it is not already present, then runs the guided onboard wizard to create a sandbox, configure inference, and apply security policies.\n\n**Note:**\n\nNemoClaw creates a fresh OpenClaw instance inside the sandbox during the onboarding process.\n\n```bash\ncurl -fsSL https:\u002F\u002Fwww.nvidia.com\u002Fnemoclaw.sh | bash\n```\n\nThe piped installer prompts through your terminal. In headless scripts or CI,\npass explicit acceptance to the `bash` side of the pipe:\n\n```console\n$ curl -fsSL https:\u002F\u002Fwww.nvidia.com\u002Fnemoclaw.sh | NEMOCLAW_NON_INTERACTIVE=1 NEMOCLAW_ACCEPT_THIRD_PARTY_SOFTWARE=1 bash\n```\n\nIf you use nvm or fnm to manage Node.js, the installer might not update your current shell's PATH.\nIf `nemoclaw` is not found after install, run `source ~\u002F.bashrc` (or `source ~\u002F.zshrc` for zsh) or open a new terminal.\n\nOn Linux, the installer checks Docker before it installs NemoClaw.\nIf Docker is missing, the installer downloads the official Docker convenience script, asks for `sudo`, installs Docker, and starts the Docker service when systemd is available.\nIf Docker is installed but your current shell cannot use the Docker socket yet, the installer adds your user to the `docker` group when needed and exits with a recovery command.\n\nOn macOS, the installer uses the Docker-driver OpenShell gateway path with Docker Desktop or Colima.\n\n```console\n$ newgrp docker\n$ curl -fsSL https:\u002F\u002Fwww.nvidia.com\u002Fnemoclaw.sh | bash\n```\n\nOn DGX Spark, DGX Station, and Windows WSL, an interactive installer offers express install after you accept the third-party software notice.\nExpress install switches onboarding to non-interactive mode, allows `sudo` password prompts for required host changes, and selects the managed local inference path for that platform.\nUnless `NEMOCLAW_POLICY_TIER` is set, it applies sandbox policy in `suggested` mode with the `balanced` tier by default, using the base sandbox policy plus supported package, model, web-search, and local-inference presets.\nOn WSL, express install selects the Windows-host Ollama setup path.\nSet `NEMOCLAW_NO_EXPRESS=1` to skip the express prompt, or set `NEMOCLAW_PROVIDER` before launching the installer when you want to choose a provider yourself.\n\nThe installer auto-launches `nemoclaw onboard` when it can locate the freshly-installed binary.\nIf it cannot locate the binary, or if blocking host preflight checks fail, it does not launch the wizard automatically.\nIn that case, the installer prints the relevant diagnostics and a `To finish setup, run:` block with the explicit `nemoclaw onboard` command.\n\n**Note:**\n\nThe onboard flow builds the sandbox image with `NEMOCLAW_DISABLE_DEVICE_AUTH=1` so the dashboard is immediately usable during setup.\nThis is a build-time setting baked into the sandbox image, not a runtime knob.\nIf you export `NEMOCLAW_DISABLE_DEVICE_AUTH` after onboarding finishes, it has no effect on an existing sandbox.\n\n### Review the Configuration Before the Sandbox Build\n\nAfter you enter the sandbox name, the wizard prints a review summary and asks for final confirmation before registering the provider, prompting for optional integrations, and building the sandbox image.\nFor example, if you picked an OpenAI-compatible endpoint, the summary looks like the following:\n\n```text\n  ──────────────────────────────────────────────────\n  Review configuration\n  ──────────────────────────────────────────────────\n  Provider:      compatible-endpoint\n  Model:         openai\u002Fopenai\u002Fgpt-5.5\n  API key:       COMPATIBLE_API_KEY (staged for OpenShell gateway registration)\n  Web search:    disabled\n  Messaging:     none\n  Sandbox name:  my-gpt-claw\n  Note:          Sandbox build typically takes 5–15 minutes on this host.\n  ──────────────────────────────────────────────────\n  Web search and messaging channels will be prompted next.\n  Apply this configuration? [Y\u002Fn]:\n```\n\nThe default is `Y`, so you can press Enter once to continue. Answer `n` to abort cleanly, fix the entries, and re-run `nemoclaw onboard`.\n\nNon-interactive runs (`NEMOCLAW_NON_INTERACTIVE=1`) print the summary for log clarity but skip the prompt.\n\n### Configure Web Search and Messaging\n\nAfter you confirm the summary, NemoClaw registers the selected provider with the OpenShell gateway and sets the `inference.local` route.\nThe wizard then asks whether to enable Brave Web Search.\nIf you enable it, enter a Brave Search API key when prompted.\n\nThe wizard also offers messaging channels such as Telegram, Discord, Slack, WeChat, and WhatsApp.\nPress a channel number to toggle it, then press Enter to continue.\nIf you select a channel, NemoClaw validates the token format before it bakes the channel configuration into the sandbox.\nFor example, Slack bot tokens must start with `xoxb-`.\nWeChat and WhatsApp are experimental.\nReview Messaging Channels (use the `nemoclaw-user-manage-sandboxes` skill) before enabling them.\n\n### Choose Network Policy Presets\n\nAfter the sandbox image builds and OpenClaw starts inside the sandbox, NemoClaw asks which network policy tier to apply.\nThe default **Balanced** tier includes common development presets such as npm, PyPI, Hugging Face, Homebrew, and Brave Search when the selected agent supports web search.\nUse the arrow keys or `j` and `k` to move, Space to select, and Enter to confirm.\n\nThe preset selector lets you include more destinations, such as GitHub, Jira, Slack, Telegram, or local inference.\nPress `r` to toggle a selected preset between read-only and read-write when the preset supports both modes.\n\nWhen the install completes, a summary confirms the running environment.\nBefore printing the summary, NemoClaw verifies that the sandbox gateway and dashboard port forward are reachable.\nInference route and messaging bridge checks are reported as warnings when they need more time or additional configuration.\nThe `Model` and provider line reflects the inference option you picked during onboarding.\nThe example below shows the result if you picked an OpenAI-compatible endpoint during onboarding.\n\n```text\n──────────────────────────────────────────────────\nNemoClaw is ready\n\nSandbox:  my-gpt-claw\nModel:    openai\u002Fopenai\u002Fgpt-5.5 (Other OpenAI-compatible endpoint)\n\nStart chatting\n\n  Browser:\n    http:\u002F\u002F127.0.0.1:18789\u002F\n\n  Terminal:\n    nemoclaw my-gpt-claw connect\n    then run: openclaw tui\n\nAuthenticated dashboard URL, if needed:\n  nemoclaw my-gpt-claw dashboard-url --quiet\n\nManage later\n\n  Status:      nemoclaw my-gpt-claw status\n  Logs:        nemoclaw my-gpt-claw logs --follow\n  Model:       nemoclaw inference set --model \u003Cmodel> --provider \u003Cprovider> --sandbox my-gpt-claw\n  Policies:    nemoclaw my-gpt-claw policy-add\n  Credentials: nemoclaw credentials reset \u003CKEY> && nemoclaw onboard\n──────────────────────────────────────────────────\n\n[INFO]  === Installation complete ===\n```\n\nIf you picked a different option, the `Model` line shows that provider's model and label instead. For example, you might see `gpt-5.4 (OpenAI)`, `claude-sonnet-4-6 (Anthropic)`, `gemini-2.5-flash (Google Gemini)`, `llama3.1:8b (Local Ollama)`, `nvidia-routed (Model Router)`, or `\u003Cyour-model> (Other OpenAI-compatible endpoint)`.\n\nLoad [references\u002Fquickstart-details.md](references\u002Fquickstart-details.md) for detailed steps on Respond to the Onboard Wizard.\n\n## Run Your First Agent Prompt\n\nYou can chat with the agent from the terminal or the browser.\n\n### Open the OpenClaw UI in a Browser to Chat with the Agent\n\nThe onboard wizard starts a background port forward to the sandbox dashboard, then prints the dashboard URL in the install summary.\nThe default host port is `18789`.\nIf that port is already taken, NemoClaw uses the next free dashboard port, such as `18790`, and prints that port in the final URL.\nIf the chosen port becomes occupied after the sandbox build starts, onboarding rolls back the newly-created sandbox and asks you to retry instead of printing an unreachable dashboard URL.\nThe install transcript does not print the gateway token.\nIf the browser requires authentication, use the `dashboard-url --quiet` command to print a complete URL explicitly.\n\n```text\nnemoclaw my-gpt-claw dashboard-url --quiet\n```\n\nOpen the dashboard URL in your browser.\nIf the browser asks for authentication, run `nemoclaw my-gpt-claw dashboard-url --quiet` and open the returned URL.\nTreat the authenticated URL like a password.\n\n### Chat with the Agent from the Terminal\n\nConnect to the sandbox and use the OpenClaw CLI.\n\n```bash\nnemoclaw my-assistant connect\n# inside the sandbox:\nopenclaw tui\n```\n\n## References\n\n- **Load [references\u002Fquickstart-hermes.md](references\u002Fquickstart-hermes.md)** when users ask for Hermes setup, NemoHermes onboarding, or running Hermes inside OpenShell. Installs NemoClaw, selects the Hermes agent, and launches a sandboxed Hermes API endpoint.\n- **Load [references\u002Fprerequisites.md](references\u002Fprerequisites.md)** when verifying prerequisites before installation. Lists the hardware, software, and container runtime requirements for running NemoClaw.\n- **Load [references\u002Fwindows-preparation.md](references\u002Fwindows-preparation.md)** when preparing a Windows machine for NemoClaw, enabling WSL 2, configuring Docker Desktop for Windows, or troubleshooting a Windows-specific install error. Covers Windows-only preparation steps required before the Quickstart.\n- **Load [references\u002Fquickstart-details.md](references\u002Fquickstart-details.md)** when you need detailed steps for Respond to the Onboard Wizard.\n\n## Related Skills\n\n- `nemoclaw-user-overview` — NemoClaw Overview (use the `nemoclaw-user-overview` skill) to learn what NemoClaw is and its capabilities\n",{"name":5,"license":15,"description":7},"main","0d1434f89f4bc6b07e9d272accd8c1013768820f","archive\u002Fskill-md-reviewed\u002Fsha256\u002Ff0\u002Ff0be3e455e3447a0bc1d253ce0f4eda45d8a42ffb4220188b00745be8fce2edd",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":58,"prompt":68,"zipAvailable":69},[59,62,65],{"tool":60,"command":61},"npx","npx skills add zapabob\u002FSkills --skill nemoclaw-user-get-started",{"tool":63,"command":64},"bunx","bunx skills add zapabob\u002FSkills --skill nemoclaw-user-get-started",{"tool":66,"command":67},"pnpm","pnpm dlx skills add zapabob\u002FSkills --skill nemoclaw-user-get-started","安装技能，技能地址：https:\u002F\u002Fgithub.com\u002Fzapabob\u002FSkills\u002Fblob\u002Fmain\u002Farchive\u002Fskill-md-reviewed\u002Fsha256\u002Ff0\u002Ff0be3e455e3447a0bc1d253ce0f4eda45d8a42ffb4220188b00745be8fce2edd\u002FSKILL.md",true,[],[72,104,139,165,191,208],{"skillNo":73,"name":74,"nameZh":6,"description":75,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":76,"licenseFileUrl":6,"sourceHtmlUrl":77,"categories":78,"keywords":88,"publishedAt":44},"01M6GJTE1GESGGF9K028Y7753E","xurl","X\u002FTwitter via xurl CLI: post, search, DM, media, v2 API.","MIT","https:\u002F\u002Fgithub.com\u002Fzapabob\u002FSkills\u002Fblob\u002Fmain\u002Fregistry\u002Fskills\u002Fxurl\u002Fvariants\u002Fhermes-agent\u002FSKILL.md",[79,82,83],{"categoryNo":80,"categoryName":81,"taxonomyType":21,"taxonomyTypeDesc":22},"01JBSEEDCAT000000000000010","后端与接口",{"categoryNo":19,"categoryName":20,"taxonomyType":21,"taxonomyTypeDesc":22},{"categoryNo":84,"categoryName":85,"taxonomyType":86,"taxonomyTypeDesc":87},"01JBSEEDCAT000000000000030","开发工程师","PROFESSION","适用职业",[74,89,90,91,92,93,42,94,95,96,97,98,99,37,36,100,49,101,102,103],"openclaw","macos","cli","github","linux","official","search","https","social-media","api","Media","twitter","social","via","post",{"skillNo":105,"name":106,"nameZh":6,"description":107,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":76,"licenseFileUrl":6,"sourceHtmlUrl":108,"categories":109,"keywords":121,"publishedAt":44},"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",[110,113,116,117,118],{"categoryNo":111,"categoryName":112,"taxonomyType":21,"taxonomyTypeDesc":22},"01JBSEEDCAT000000000000015","视觉设计",{"categoryNo":114,"categoryName":115,"taxonomyType":21,"taxonomyTypeDesc":22},"01JBSEEDCAT000000000000018","写作与文案",{"categoryNo":19,"categoryName":20,"taxonomyType":21,"taxonomyTypeDesc":22},{"categoryNo":84,"categoryName":85,"taxonomyType":86,"taxonomyTypeDesc":87},{"categoryNo":119,"categoryName":120,"taxonomyType":86,"taxonomyTypeDesc":87},"01JBSEEDCAT000000000000036","内容创作者",[122,123,124,125,90,126,93,127,42,128,129,130,131,132,133,134,135,136,137,138],"writing","writing plans","plans","design","review","workflow","documentation","tasks","development","code","planning","code-review","subagent","write","superpowers","paths","test-driven-development",{"skillNo":140,"name":141,"nameZh":6,"description":142,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":76,"licenseFileUrl":6,"sourceHtmlUrl":143,"categories":144,"keywords":148,"publishedAt":44},"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",[145],{"categoryNo":146,"categoryName":147,"taxonomyType":21,"taxonomyTypeDesc":22},"01JBSEEDCAT000000000000016","图像与多媒体",[141,90,93,149,150,151,152,153,154,155,156,157,33,158,159,160,161,162,163,164],"openai","speech","multimodal","Transformers","ASR","Audio","text","model","speech recognition","general","multilingual","translation","english","identification","processing","Audio Processing",{"skillNo":166,"name":167,"nameZh":6,"description":168,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":76,"licenseFileUrl":6,"sourceHtmlUrl":169,"categories":170,"keywords":174,"publishedAt":44},"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",[171],{"categoryNo":172,"categoryName":173,"taxonomyType":21,"taxonomyTypeDesc":22},"01JBSEEDCAT000000000000013","分析与可视化",[175,90,176,177,42,178,179,180,181,182,183,156,184,185,32,186,187,188,189,190],"weights and biases","tensorflow","experiments","pytorch","visualization","registry","real-time","tuning","dashboards","experiment","log","Experiment Tracking","Model Registry","Hyperparameter Tuning","WandB","Real-Time Visualization",{"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":76,"licenseFileUrl":6,"sourceHtmlUrl":195,"categories":196,"keywords":198,"publishedAt":44},"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",[197],{"categoryNo":19,"categoryName":20,"taxonomyType":21,"taxonomyTypeDesc":22},[193,90,199,92,93,200,201,202,203,204,205,37,36,206,207],"terminal","automation","http","monitoring","cron","json","rss","devops","with",{"skillNo":209,"name":210,"nameZh":6,"description":211,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":76,"licenseFileUrl":6,"sourceHtmlUrl":212,"categories":213,"keywords":216,"publishedAt":44},"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",[214,215],{"categoryNo":80,"categoryName":81,"taxonomyType":21,"taxonomyTypeDesc":22},{"categoryNo":84,"categoryName":85,"taxonomyType":86,"taxonomyTypeDesc":87},[217,218,219,93,220,149,221,222,223,152,224,98,225,226,227,228,229,230,231,232],"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"]