[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"skill:01M7DAECK2REDVPT88M65W24EH":3,"skill-same:01M7DAECK2REDVPT88M65W24EH":61},{"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":19,"linkOnly":20,"markdownContent":21,"markdownBody":22,"frontMatter":23,"refName":39,"commitSha":40,"skillDirectory":41,"forksCount":14,"repositoryHtmlUrl":42,"repositoryHomepageUrl":6,"ownerHtmlUrl":43,"ownerBlogUrl":44,"ownerDescription":45,"updatedAt":46,"install":47,"resources":60},"01M7DAECK2REDVPT88M65W24EH","jupyter-live-kernel",null,"Iterative Python via live Jupyter kernel (hamelnb).","GrupoANDevelopment-m\u002Falberto-ai","GrupoANDevelopment-m","https:\u002F\u002Favatars.githubusercontent.com\u002Fu\u002F257455179?v=4","01M7D69X2N2KEVN0SJF6WGM6SH","Antônio  Ndombe","01M7D69X3P5JTT8H8S904N3888",0,"MIT","https:\u002F\u002Fgithub.com\u002FGrupoANDevelopment-m\u002Falberto-ai\u002Fblob\u002Fmain\u002Fupstream\u002Fhermes\u002Fskills\u002Fdata-science\u002Fjupyter-live-kernel\u002FSKILL.md",[],[],"2026-11-15 14:19:17",false,"---\nname: jupyter-live-kernel\ndescription: \"Iterative Python via live Jupyter kernel (hamelnb).\"\nversion: 1.0.0\nauthor: Hermes Agent\nlicense: MIT\nplatforms: [linux, macos, windows]\nmetadata:\n  hermes:\n    tags: [jupyter, notebook, repl, data-science, exploration, iterative]\n    category: data-science\n---\n\n# Jupyter Live Kernel (hamelnb)\n\nGives you a **stateful Python REPL** via a live Jupyter kernel. Variables persist\nacross executions. Use this instead of `execute_code` when you need to build up\nstate incrementally, explore APIs, inspect DataFrames, or iterate on complex code.\n\n## When to Use This vs Other Tools\n\n| Tool | Use When |\n|------|----------|\n| **This skill** | Iterative exploration, state across steps, data science, ML, \"let me try this and check\" |\n| `execute_code` | One-shot scripts needing hermes tool access (web_search, file ops). Stateless. |\n| `terminal` | Shell commands, builds, installs, git, process management |\n\n**Rule of thumb:** If you'd want a Jupyter notebook for the task, use this skill.\n\n## Prerequisites\n\n1. **uv** must be installed (check: `which uv`)\n2. **JupyterLab** must be installed: `uv tool install jupyterlab`\n3. A Jupyter server must be running (see Setup below)\n\n## Setup\n\nThe hamelnb script location:\n```\nSCRIPT=\"$HOME\u002F.agent-skills\u002Fhamelnb\u002Fskills\u002Fjupyter-live-kernel\u002Fscripts\u002Fjupyter_live_kernel.py\"\n```\n\nIf not cloned yet:\n```\ngit clone https:\u002F\u002Fgithub.com\u002Fhamelsmu\u002Fhamelnb.git ~\u002F.agent-skills\u002Fhamelnb\n```\n\n### Starting JupyterLab\n\nCheck if a server is already running:\n```\nuv run \"$SCRIPT\" servers\n```\n\nIf no servers found, start one:\n```\njupyter-lab --no-browser --port=8888 --notebook-dir=$HOME\u002Fnotebooks \\\n  --IdentityProvider.token='' --ServerApp.password='' > \u002Ftmp\u002Fjupyter.log 2>&1 &\nsleep 3\n```\n\nNote: Token\u002Fpassword disabled for local agent access. The server runs headless.\n\n### Creating a Notebook for REPL Use\n\nIf you just need a REPL (no existing notebook), create a minimal notebook file:\n```\nmkdir -p ~\u002Fnotebooks\n```\nWrite a minimal .ipynb JSON file with one empty code cell, then start a kernel\nsession via the Jupyter REST API:\n```\ncurl -s -X POST http:\u002F\u002F127.0.0.1:8888\u002Fapi\u002Fsessions \\\n  -H \"Content-Type: application\u002Fjson\" \\\n  -d '{\"path\":\"scratch.ipynb\",\"type\":\"notebook\",\"name\":\"scratch.ipynb\",\"kernel\":{\"name\":\"python3\"}}'\n```\n\n## Core Workflow\n\nAll commands return structured JSON. Always use `--compact` to save tokens.\n\n### 1. Discover servers and notebooks\n\n```\nuv run \"$SCRIPT\" servers --compact\nuv run \"$SCRIPT\" notebooks --compact\n```\n\n### 2. Execute code (primary operation)\n\n```\nuv run \"$SCRIPT\" execute --path \u003Cnotebook.ipynb> --code '\u003Cpython code>' --compact\n```\n\nState persists across execute calls. Variables, imports, objects all survive.\n\nMulti-line code works with $'...' quoting:\n```\nuv run \"$SCRIPT\" execute --path scratch.ipynb --code $'import os\\nfiles = os.listdir(\".\")\\nprint(f\"Found {len(files)} files\")' --compact\n```\n\n### 3. Inspect live variables\n\n```\nuv run \"$SCRIPT\" variables --path \u003Cnotebook.ipynb> list --compact\nuv run \"$SCRIPT\" variables --path \u003Cnotebook.ipynb> preview --name \u003Cvarname> --compact\n```\n\n### 4. Edit notebook cells\n\n```\n# View current cells\nuv run \"$SCRIPT\" contents --path \u003Cnotebook.ipynb> --compact\n\n# Insert a new cell\nuv run \"$SCRIPT\" edit --path \u003Cnotebook.ipynb> insert \\\n  --at-index \u003CN> --cell-type code --source '\u003Ccode>' --compact\n\n# Replace cell source (use cell-id from contents output)\nuv run \"$SCRIPT\" edit --path \u003Cnotebook.ipynb> replace-source \\\n  --cell-id \u003Cid> --source '\u003Cnew code>' --compact\n\n# Delete a cell\nuv run \"$SCRIPT\" edit --path \u003Cnotebook.ipynb> delete --cell-id \u003Cid> --compact\n```\n\n### 5. Verification (restart + run all)\n\nOnly use when the user asks for a clean verification or you need to confirm\nthe notebook runs top-to-bottom:\n\n```\nuv run \"$SCRIPT\" restart-run-all --path \u003Cnotebook.ipynb> --save-outputs --compact\n```\n\n## Practical Tips from Experience\n\n1. **First execution after server start may timeout** — the kernel needs a moment\n   to initialize. If you get a timeout, just retry.\n\n2. **The kernel Python is JupyterLab's Python** — packages must be installed in\n   that environment. If you need additional packages, install them into the\n   JupyterLab tool environment first.\n\n3. **--compact flag saves significant tokens** — always use it. JSON output can\n   be very verbose without it.\n\n4. **For pure REPL use**, create a scratch.ipynb and don't bother with cell editing.\n   Just use `execute` repeatedly.\n\n5. **Argument order matters** — subcommand flags like `--path` go BEFORE the\n   sub-subcommand. E.g.: `variables --path nb.ipynb list` not `variables list --path nb.ipynb`.\n\n6. **If a session doesn't exist yet**, you need to start one via the REST API\n   (see Setup section). The tool can't execute without a live kernel session.\n\n7. **Errors are returned as JSON** with traceback — read the `ename` and `evalue`\n   fields to understand what went wrong.\n\n8. **Occasional websocket timeouts** — some operations may timeout on first try,\n   especially after a kernel restart. Retry once before escalating.\n\n## Timeout Defaults\n\nThe script has a 30-second default timeout per execution. For long-running\noperations, pass `--timeout 120`. Use generous timeouts (60+) for initial\nsetup or heavy computation.\n","# Jupyter Live Kernel (hamelnb)\n\nGives you a **stateful Python REPL** via a live Jupyter kernel. Variables persist\nacross executions. Use this instead of `execute_code` when you need to build up\nstate incrementally, explore APIs, inspect DataFrames, or iterate on complex code.\n\n## When to Use This vs Other Tools\n\n| Tool | Use When |\n|------|----------|\n| **This skill** | Iterative exploration, state across steps, data science, ML, \"let me try this and check\" |\n| `execute_code` | One-shot scripts needing hermes tool access (web_search, file ops). Stateless. |\n| `terminal` | Shell commands, builds, installs, git, process management |\n\n**Rule of thumb:** If you'd want a Jupyter notebook for the task, use this skill.\n\n## Prerequisites\n\n1. **uv** must be installed (check: `which uv`)\n2. **JupyterLab** must be installed: `uv tool install jupyterlab`\n3. A Jupyter server must be running (see Setup below)\n\n## Setup\n\nThe hamelnb script location:\n```\nSCRIPT=\"$HOME\u002F.agent-skills\u002Fhamelnb\u002Fskills\u002Fjupyter-live-kernel\u002Fscripts\u002Fjupyter_live_kernel.py\"\n```\n\nIf not cloned yet:\n```\ngit clone https:\u002F\u002Fgithub.com\u002Fhamelsmu\u002Fhamelnb.git ~\u002F.agent-skills\u002Fhamelnb\n```\n\n### Starting JupyterLab\n\nCheck if a server is already running:\n```\nuv run \"$SCRIPT\" servers\n```\n\nIf no servers found, start one:\n```\njupyter-lab --no-browser --port=8888 --notebook-dir=$HOME\u002Fnotebooks \\\n  --IdentityProvider.token='' --ServerApp.password='' > \u002Ftmp\u002Fjupyter.log 2>&1 &\nsleep 3\n```\n\nNote: Token\u002Fpassword disabled for local agent access. The server runs headless.\n\n### Creating a Notebook for REPL Use\n\nIf you just need a REPL (no existing notebook), create a minimal notebook file:\n```\nmkdir -p ~\u002Fnotebooks\n```\nWrite a minimal .ipynb JSON file with one empty code cell, then start a kernel\nsession via the Jupyter REST API:\n```\ncurl -s -X POST http:\u002F\u002F127.0.0.1:8888\u002Fapi\u002Fsessions \\\n  -H \"Content-Type: application\u002Fjson\" \\\n  -d '{\"path\":\"scratch.ipynb\",\"type\":\"notebook\",\"name\":\"scratch.ipynb\",\"kernel\":{\"name\":\"python3\"}}'\n```\n\n## Core Workflow\n\nAll commands return structured JSON. Always use `--compact` to save tokens.\n\n### 1. Discover servers and notebooks\n\n```\nuv run \"$SCRIPT\" servers --compact\nuv run \"$SCRIPT\" notebooks --compact\n```\n\n### 2. Execute code (primary operation)\n\n```\nuv run \"$SCRIPT\" execute --path \u003Cnotebook.ipynb> --code '\u003Cpython code>' --compact\n```\n\nState persists across execute calls. Variables, imports, objects all survive.\n\nMulti-line code works with $'...' quoting:\n```\nuv run \"$SCRIPT\" execute --path scratch.ipynb --code $'import os\\nfiles = os.listdir(\".\")\\nprint(f\"Found {len(files)} files\")' --compact\n```\n\n### 3. Inspect live variables\n\n```\nuv run \"$SCRIPT\" variables --path \u003Cnotebook.ipynb> list --compact\nuv run \"$SCRIPT\" variables --path \u003Cnotebook.ipynb> preview --name \u003Cvarname> --compact\n```\n\n### 4. Edit notebook cells\n\n```\n# View current cells\nuv run \"$SCRIPT\" contents --path \u003Cnotebook.ipynb> --compact\n\n# Insert a new cell\nuv run \"$SCRIPT\" edit --path \u003Cnotebook.ipynb> insert \\\n  --at-index \u003CN> --cell-type code --source '\u003Ccode>' --compact\n\n# Replace cell source (use cell-id from contents output)\nuv run \"$SCRIPT\" edit --path \u003Cnotebook.ipynb> replace-source \\\n  --cell-id \u003Cid> --source '\u003Cnew code>' --compact\n\n# Delete a cell\nuv run \"$SCRIPT\" edit --path \u003Cnotebook.ipynb> delete --cell-id \u003Cid> --compact\n```\n\n### 5. Verification (restart + run all)\n\nOnly use when the user asks for a clean verification or you need to confirm\nthe notebook runs top-to-bottom:\n\n```\nuv run \"$SCRIPT\" restart-run-all --path \u003Cnotebook.ipynb> --save-outputs --compact\n```\n\n## Practical Tips from Experience\n\n1. **First execution after server start may timeout** — the kernel needs a moment\n   to initialize. If you get a timeout, just retry.\n\n2. **The kernel Python is JupyterLab's Python** — packages must be installed in\n   that environment. If you need additional packages, install them into the\n   JupyterLab tool environment first.\n\n3. **--compact flag saves significant tokens** — always use it. JSON output can\n   be very verbose without it.\n\n4. **For pure REPL use**, create a scratch.ipynb and don't bother with cell editing.\n   Just use `execute` repeatedly.\n\n5. **Argument order matters** — subcommand flags like `--path` go BEFORE the\n   sub-subcommand. E.g.: `variables --path nb.ipynb list` not `variables list --path nb.ipynb`.\n\n6. **If a session doesn't exist yet**, you need to start one via the REST API\n   (see Setup section). The tool can't execute without a live kernel session.\n\n7. **Errors are returned as JSON** with traceback — read the `ename` and `evalue`\n   fields to understand what went wrong.\n\n8. **Occasional websocket timeouts** — some operations may timeout on first try,\n   especially after a kernel restart. Retry once before escalating.\n\n## Timeout Defaults\n\nThe script has a 30-second default timeout per execution. For long-running\noperations, pass `--timeout 120`. Use generous timeouts (60+) for initial\nsetup or heavy computation.\n",{"name":5,"author":24,"license":15,"version":25,"metadata":26,"platforms":35,"description":7},"Hermes Agent","1.0.0",{"hermes":27},{"tags":28,"category":32},[29,30,31,32,33,34],"jupyter","notebook","repl","data-science","exploration","iterative",[36,37,38],"linux","macos","windows","main","eac438ea9216a7cb8a570cab803eb01eeafc6793","upstream\u002Fhermes\u002Fskills\u002Fdata-science\u002Fjupyter-live-kernel","https:\u002F\u002Fgithub.com\u002FGrupoANDevelopment-m\u002Falberto-ai","https:\u002F\u002Fgithub.com\u002FGrupoANDevelopment-m","https:\u002F\u002Fid-preview--d5bef06d-6c9e-4563-a3d4-a855b9d61610.lovable.app\u002F","Eu sou Antonio B. B. Ndombe \r\nEu sou um Pesquisador e desenvolvedor de sistema autonomia cognitivos, fundador de sistemas ODCs ( organismos digital conscientes)","2026-11-04 06:53:39",{"source":8,"skillName":5,"commands":48,"prompt":58,"zipAvailable":59},[49,52,55],{"tool":50,"command":51},"npx","npx skills add GrupoANDevelopment-m\u002Falberto-ai --skill jupyter-live-kernel",{"tool":53,"command":54},"bunx","bunx skills add GrupoANDevelopment-m\u002Falberto-ai --skill jupyter-live-kernel",{"tool":56,"command":57},"pnpm","pnpm dlx skills add GrupoANDevelopment-m\u002Falberto-ai --skill jupyter-live-kernel","安装技能，技能地址：https:\u002F\u002Fgithub.com\u002FGrupoANDevelopment-m\u002Falberto-ai\u002Fblob\u002Fmain\u002Fupstream\u002Fhermes\u002Fskills\u002Fdata-science\u002Fjupyter-live-kernel\u002FSKILL.md",true,[],[62,70,77,84,91,98],{"skillNo":63,"name":64,"nameZh":6,"description":65,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":66,"licenseFileUrl":6,"sourceHtmlUrl":67,"categories":68,"keywords":69,"publishedAt":19},"01M7DASC6FSCJP49JZBSK0NY1Z","nemoclaw-user-reference","Describes the NemoClaw integration layer and blueprint architecture and how they orchestrate compatible agent sandboxes. Use when looking up architecture, agent integration, plugin structure, or blueprint design. Trigger keywords - nemoclaw architecture, nemoclaw agent architecture, nemoclaw plugin blueprint structure, nemoclaw vs openshell, which cli, nemoclaw cli, openshell cli, sandbox commands, nemoclaw cli commands, nemoclaw command reference, nemoclaw network policy, sandbox egress control operator approval, nemoclaw troubleshooting, nemoclaw debug sandbox issues.","Apache-2.0","https:\u002F\u002Fgithub.com\u002FGrupoANDevelopment-m\u002Falberto-ai\u002Fblob\u002Fmain\u002Fupstream\u002Fnemoclaw\u002Fskills\u002Fnemoclaw-user-reference\u002FSKILL.md",[],[],{"skillNo":71,"name":72,"nameZh":6,"description":73,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":66,"licenseFileUrl":6,"sourceHtmlUrl":74,"categories":75,"keywords":76,"publishedAt":19},"01M7DAS5S79VK33XFGVAM2TFWF","nemoclaw-user-overview","Explains how OpenClaw, OpenShell, and NemoClaw form the ecosystem, NemoClaw's position in the stack, what NemoClaw adds beyond the community sandbox, and when to prefer NemoClaw versus integrating OpenShell and OpenClaw directly. Use when users ask about the relationship between OpenClaw, OpenShell, and NemoClaw, or when to use NemoClaw versus OpenShell. Trigger keywords - nemoclaw ecosystem, openclaw openshell, nemoclaw vs openshell, sandboxed openclaw, how nemoclaw works, nemoclaw sandbox lifecycle blueprint, nemoclaw overview, openclaw always-on assistants, nvidia openshell, nvidia nemotron, nemoclaw release notes, nemoclaw changelog.","https:\u002F\u002Fgithub.com\u002FGrupoANDevelopment-m\u002Falberto-ai\u002Fblob\u002Fmain\u002Fupstream\u002Fnemoclaw\u002Fskills\u002Fnemoclaw-user-overview\u002FSKILL.md",[],[],{"skillNo":78,"name":79,"nameZh":6,"description":80,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":66,"licenseFileUrl":6,"sourceHtmlUrl":81,"categories":82,"keywords":83,"publishedAt":19},"01M7DAS0PQEMET5MNGZ1ABSZVS","nemoclaw-user-monitor-sandbox","Inspects sandbox health, traces agent behavior, and diagnoses problems. Use when monitoring a running sandbox, debugging agent issues, or checking sandbox logs. Trigger keywords - monitor nemoclaw sandbox, debug nemoclaw agent issues.","https:\u002F\u002Fgithub.com\u002FGrupoANDevelopment-m\u002Falberto-ai\u002Fblob\u002Fmain\u002Fupstream\u002Fnemoclaw\u002Fskills\u002Fnemoclaw-user-monitor-sandbox\u002FSKILL.md",[],[],{"skillNo":85,"name":86,"nameZh":6,"description":87,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":66,"licenseFileUrl":6,"sourceHtmlUrl":88,"categories":89,"keywords":90,"publishedAt":19},"01M7DARQYGF7E9A69VH6S3CGN9","nemoclaw-user-manage-sandboxes","Explains operational tasks after the quickstart: listing sandboxes, status and health checks, logs, diagnostics, port forwards, multiple sandboxes, credential reset, rebuilds, network presets, upgrades, and uninstall. Trigger keywords - manage nemoclaw sandboxes, nemoclaw status, nemoclaw list, nemoclaw dashboard port, nemoclaw rebuild, nemoclaw upgrade sandboxes, nemoclaw uninstall, sandbox mutability, sandbox runtime configuration, sandbox rebuild, nemoclaw backup, nemoclaw restore, workspace backup, openshell sandbox download upload, nemoclaw messaging channels, nemoclaw telegram, nemoclaw discord, nemoclaw slack, nemoclaw wechat, nemoclaw whatsapp, openshell channel messaging, nemoclaw workspace files, soul.md, user.md, identity.md, agents.md, sandbox persistence.","https:\u002F\u002Fgithub.com\u002FGrupoANDevelopment-m\u002Falberto-ai\u002Fblob\u002Fmain\u002Fupstream\u002Fnemoclaw\u002Fskills\u002Fnemoclaw-user-manage-sandboxes\u002FSKILL.md",[],[],{"skillNo":92,"name":93,"nameZh":6,"description":94,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":66,"licenseFileUrl":6,"sourceHtmlUrl":95,"categories":96,"keywords":97,"publishedAt":19},"01M7DARH8BRTG51TRCAB7YWDJ4","nemoclaw-user-manage-policy","Adds, removes, or modifies allowed endpoints in the sandbox policy. Use when customizing network policy, changing egress rules, or configuring sandbox endpoint access. Trigger keywords - customize nemoclaw network policy, sandbox egress policy configuration, nemoclaw integration policy examples, post-install policy setup, openshell approval workflow, policy preset, nemoclaw approve network requests, sandbox egress approval tui.","https:\u002F\u002Fgithub.com\u002FGrupoANDevelopment-m\u002Falberto-ai\u002Fblob\u002Fmain\u002Fupstream\u002Fnemoclaw\u002Fskills\u002Fnemoclaw-user-manage-policy\u002FSKILL.md",[],[],{"skillNo":99,"name":100,"nameZh":6,"description":101,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":66,"licenseFileUrl":6,"sourceHtmlUrl":102,"categories":103,"keywords":104,"publishedAt":19},"01M7DARAT62M2VR37590VCZ5NS","nemoclaw-user-get-started","Installs NemoClaw, launches a sandbox, and runs the first agent prompt. 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