[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"skill:01M7CS8S2K2JMZ2WP6HT87ECV1":3,"skill-same:01M7CS8S2K2JMZ2WP6HT87ECV1":84},{"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":31,"commitSha":32,"skillDirectory":33,"forksCount":34,"repositoryHtmlUrl":35,"repositoryHomepageUrl":36,"ownerHtmlUrl":37,"ownerBlogUrl":6,"ownerDescription":38,"updatedAt":39,"install":40,"resources":53},"01M7CS8S2K2JMZ2WP6HT87ECV1","dynamo-router-starter",null,"Start or patch Dynamo router modes and run router endpoint smoke checks. Use for round-robin, KV-aware, least-loaded, or device-aware routing setup; use recipe-runner for recipe deployment and troubleshoot for failure diagnosis.","YYC-Cube\u002FYYC3-Knowledge-Base","YYC-Cube","https:\u002F\u002Favatars.githubusercontent.com\u002Fu\u002F235006543?v=4","01M79J2PH4SWD2X0825X6PN748","yyc3","01M79J2PHVK3F6ZBYT8K2SCZCW",1,"Apache-2.0","https:\u002F\u002Fgithub.com\u002FYYC-Cube\u002FYYC3-Knowledge-Base\u002Fblob\u002Fmain\u002FYYC3-Skills-技能包\u002FYYC3-Skills-技能包-skills\u002Fplugins\u002Fnvidia-skills\u002Fskills\u002Fdynamo-router-starter\u002FSKILL.md",[],[],"2026-11-15 14:19:17",false,"---\nname: dynamo-router-starter\ndescription: Start or patch Dynamo router modes and run router endpoint smoke checks. Use for round-robin, KV-aware, least-loaded, or device-aware routing setup; use recipe-runner for recipe deployment and troubleshoot for failure diagnosis.\nlicense: Apache-2.0\nmetadata:\n  author: Dan Gil \u003Cdagil@nvidia.com>\n  tags:\n    - dynamo\n    - router\n    - smoke-test\n    - bring-up\n---\n\n# Dynamo Router Starter\n\n\u003C!--\nSPDX-FileCopyrightText: Copyright (c) 2026 NVIDIA CORPORATION & AFFILIATES. All rights reserved.\nSPDX-License-Identifier: CC-BY-4.0\n-->\n\n## Purpose\n\nMake Dynamo routing feel easy by getting a baseline router mode running, enabling\nKV-aware routing when appropriate, and proving the endpoint works. Keep the user\nfocused on exact commands and success signals, not router internals.\n\n## Prerequisites\n\n- Python 3.10+ with the `dynamo` package importable (`python3 -m dynamo.frontend --help` works).\n- For Kubernetes runs: `kubectl` configured with access to the target namespace and a deployed Dynamo recipe.\n- Network reachability to the frontend service (port-forward or direct).\n- A model already loaded into at least one worker (`\u002Fv1\u002Fmodels` returns at least one entry).\n\n## Required Inputs\n\nCollect or infer:\n\n- local Python\u002FCLI or Kubernetes recipe path\n- desired mode: `round-robin`, `kv`, `least-loaded`, `device-aware-weighted`, `direct`, or `random`\n- frontend port or Kubernetes frontend service\n- whether workers publish KV events; if not, use approximate KV mode\n- model name for smoke requests, if `\u002Fv1\u002Fmodels` cannot discover it\n\n## Instructions\n\n### 1. Establish A Baseline\n\nFor local bring-up with already registered workers:\n\n```bash\npython3 -m dynamo.frontend --router-mode round-robin --http-port 8000\n```\n\nFor Kubernetes, inspect the selected recipe `deploy.yaml` and locate the\nfrontend service. If the recipe is not already deployed, use\n`dynamo-recipe-runner` first.\n\n### 2. Enable KV Routing\n\nFor local frontend:\n\n```bash\npython3 -m dynamo.frontend --router-mode kv --http-port 8000\n```\n\nFor Kubernetes, patch only the frontend service env:\n\n```yaml\nenvs:\n  - name: DYN_ROUTER_MODE\n    value: kv\n```\n\nIf backend workers are not publishing KV cache events, set approximate mode\ninstead of leaving the router waiting for events:\n\n```yaml\nenvs:\n  - name: DYN_ROUTER_USE_KV_EVENTS\n    value: \"false\"\n```\n\n### 3. Smoke Test\n\nAfter port-forwarding the frontend service or starting local frontend, run:\n\n```bash\npython3 scripts\u002Fcheck_router_health.py \\\n  --base-url http:\u002F\u002F127.0.0.1:8000\n```\n\nThis must verify `\u002Fv1\u002Fmodels` and, when a model is discoverable, one\n`\u002Fv1\u002Fchat\u002Fcompletions` request.\n\n### 4. Compare Modes Carefully\n\nWhen comparing round-robin vs KV routing:\n\n- use the same model, workers, prompt set, concurrency, and sampling settings\n- send repeated-prefix prompts if demonstrating KV reuse\n- label the result as a smoke comparison unless enough benchmark samples were collected\n- do not claim throughput improvement from a single chat request\n\nIf the endpoint is unhealthy or workers are missing, switch to\n`dynamo-troubleshoot`.\n\n## Available Scripts\n\n| Script | Purpose | Arguments |\n|---|---|---|\n| `scripts\u002Fcheck_router_health.py` | Smoke-test `\u002Fv1\u002Fmodels` and one chat completion against a Dynamo frontend | `--base-url`, `--retries`, `--timeout` |\n\nInvoke via the agentskills.io `run_script()` protocol:\n\n```python\nrun_script(\"scripts\u002Fcheck_router_health.py\", args=[\"--base-url\", \"http:\u002F\u002F127.0.0.1:8000\"])\n```\n\n## Examples\n\nLocal KV-routed frontend on port 8000, then smoke-test it:\n\n```bash\npython3 -m dynamo.frontend --router-mode kv --http-port 8000 &\npython3 scripts\u002Fcheck_router_health.py --base-url http:\u002F\u002F127.0.0.1:8000\n```\n\nKubernetes-deployed frontend reachable via port-forward:\n\n```bash\nkubectl port-forward svc\u002Fqwen-vllm-disagg-frontend 8000:8000 -n dynamo-demo &\npython3 scripts\u002Fcheck_router_health.py --base-url http:\u002F\u002F127.0.0.1:8000 --retries 3\n```\n\nEquivalent through the agent protocol:\n\n```python\nrun_script(\"scripts\u002Fcheck_router_health.py\", args=[\"--base-url\", \"http:\u002F\u002F127.0.0.1:8000\", \"--retries\", \"3\"])\n```\n\n## Output Contract\n\nReturn:\n\n- mode selected and why\n- local command or Kubernetes env patch\n- frontend service or URL\n- smoke-test result\n- any limitation, such as approximate KV mode or missing worker KV events\n- next command to run for a fuller comparison\n\n## Limitations\n\n- Smoke test is one chat completion; it is not a benchmark. Use `dynamo-benchmark` for throughput\u002Flatency numbers.\n- KV-aware mode without worker KV-event publication degrades to approximate mode; this skill flags but does not fix the underlying worker config.\n- Mode comparisons require matched workloads; cross-mode latency claims need separate benchmark runs.\n\n## Troubleshooting\n\n| Symptom | Likely cause | Next step |\n|---|---|---|\n| `\u002Fv1\u002Fmodels` returns empty list | No worker registered with the frontend | Verify worker pods are Ready; confirm they connect to the same etcd\u002FNATS |\n| Smoke chat request times out | Frontend up, workers not serving | Switch to `dynamo-troubleshoot`; inspect worker logs |\n| KV mode hangs | Workers do not publish KV cache events | Set `DYN_ROUTER_USE_KV_EVENTS=false` (approximate mode) |\n| Connection refused on port-forward | Port-forward dropped or wrong service name | Re-run port-forward; verify the frontend service name matches the recipe |\n\n## Benchmark\n\nSee `BENCHMARK.md` for the NVCARPS-EVAL performance report (auto-generated by the NVSkills CI pipeline). To refresh, re-run `\u002Fnvskills-ci` on an upstream PR touching this skill.\n\n## References\n\n- Read `references\u002Frouter-modes.md` for the compact mode\u002Fenv map.\n- Use `scripts\u002Fcheck_router_health.py` for endpoint smoke tests.\n","# Dynamo Router Starter\n\n\u003C!--\nSPDX-FileCopyrightText: Copyright (c) 2026 NVIDIA CORPORATION & AFFILIATES. All rights reserved.\nSPDX-License-Identifier: CC-BY-4.0\n-->\n\n## Purpose\n\nMake Dynamo routing feel easy by getting a baseline router mode running, enabling\nKV-aware routing when appropriate, and proving the endpoint works. Keep the user\nfocused on exact commands and success signals, not router internals.\n\n## Prerequisites\n\n- Python 3.10+ with the `dynamo` package importable (`python3 -m dynamo.frontend --help` works).\n- For Kubernetes runs: `kubectl` configured with access to the target namespace and a deployed Dynamo recipe.\n- Network reachability to the frontend service (port-forward or direct).\n- A model already loaded into at least one worker (`\u002Fv1\u002Fmodels` returns at least one entry).\n\n## Required Inputs\n\nCollect or infer:\n\n- local Python\u002FCLI or Kubernetes recipe path\n- desired mode: `round-robin`, `kv`, `least-loaded`, `device-aware-weighted`, `direct`, or `random`\n- frontend port or Kubernetes frontend service\n- whether workers publish KV events; if not, use approximate KV mode\n- model name for smoke requests, if `\u002Fv1\u002Fmodels` cannot discover it\n\n## Instructions\n\n### 1. Establish A Baseline\n\nFor local bring-up with already registered workers:\n\n```bash\npython3 -m dynamo.frontend --router-mode round-robin --http-port 8000\n```\n\nFor Kubernetes, inspect the selected recipe `deploy.yaml` and locate the\nfrontend service. If the recipe is not already deployed, use\n`dynamo-recipe-runner` first.\n\n### 2. Enable KV Routing\n\nFor local frontend:\n\n```bash\npython3 -m dynamo.frontend --router-mode kv --http-port 8000\n```\n\nFor Kubernetes, patch only the frontend service env:\n\n```yaml\nenvs:\n  - name: DYN_ROUTER_MODE\n    value: kv\n```\n\nIf backend workers are not publishing KV cache events, set approximate mode\ninstead of leaving the router waiting for events:\n\n```yaml\nenvs:\n  - name: DYN_ROUTER_USE_KV_EVENTS\n    value: \"false\"\n```\n\n### 3. Smoke Test\n\nAfter port-forwarding the frontend service or starting local frontend, run:\n\n```bash\npython3 scripts\u002Fcheck_router_health.py \\\n  --base-url http:\u002F\u002F127.0.0.1:8000\n```\n\nThis must verify `\u002Fv1\u002Fmodels` and, when a model is discoverable, one\n`\u002Fv1\u002Fchat\u002Fcompletions` request.\n\n### 4. Compare Modes Carefully\n\nWhen comparing round-robin vs KV routing:\n\n- use the same model, workers, prompt set, concurrency, and sampling settings\n- send repeated-prefix prompts if demonstrating KV reuse\n- label the result as a smoke comparison unless enough benchmark samples were collected\n- do not claim throughput improvement from a single chat request\n\nIf the endpoint is unhealthy or workers are missing, switch to\n`dynamo-troubleshoot`.\n\n## Available Scripts\n\n| Script | Purpose | Arguments |\n|---|---|---|\n| `scripts\u002Fcheck_router_health.py` | Smoke-test `\u002Fv1\u002Fmodels` and one chat completion against a Dynamo frontend | `--base-url`, `--retries`, `--timeout` |\n\nInvoke via the agentskills.io `run_script()` protocol:\n\n```python\nrun_script(\"scripts\u002Fcheck_router_health.py\", args=[\"--base-url\", \"http:\u002F\u002F127.0.0.1:8000\"])\n```\n\n## Examples\n\nLocal KV-routed frontend on port 8000, then smoke-test it:\n\n```bash\npython3 -m dynamo.frontend --router-mode kv --http-port 8000 &\npython3 scripts\u002Fcheck_router_health.py --base-url http:\u002F\u002F127.0.0.1:8000\n```\n\nKubernetes-deployed frontend reachable via port-forward:\n\n```bash\nkubectl port-forward svc\u002Fqwen-vllm-disagg-frontend 8000:8000 -n dynamo-demo &\npython3 scripts\u002Fcheck_router_health.py --base-url http:\u002F\u002F127.0.0.1:8000 --retries 3\n```\n\nEquivalent through the agent protocol:\n\n```python\nrun_script(\"scripts\u002Fcheck_router_health.py\", args=[\"--base-url\", \"http:\u002F\u002F127.0.0.1:8000\", \"--retries\", \"3\"])\n```\n\n## Output Contract\n\nReturn:\n\n- mode selected and why\n- local command or Kubernetes env patch\n- frontend service or URL\n- smoke-test result\n- any limitation, such as approximate KV mode or missing worker KV events\n- next command to run for a fuller comparison\n\n## Limitations\n\n- Smoke test is one chat completion; it is not a benchmark. Use `dynamo-benchmark` for throughput\u002Flatency numbers.\n- KV-aware mode without worker KV-event publication degrades to approximate mode; this skill flags but does not fix the underlying worker config.\n- Mode comparisons require matched workloads; cross-mode latency claims need separate benchmark runs.\n\n## Troubleshooting\n\n| Symptom | Likely cause | Next step |\n|---|---|---|\n| `\u002Fv1\u002Fmodels` returns empty list | No worker registered with the frontend | Verify worker pods are Ready; confirm they connect to the same etcd\u002FNATS |\n| Smoke chat request times out | Frontend up, workers not serving | Switch to `dynamo-troubleshoot`; inspect worker logs |\n| KV mode hangs | Workers do not publish KV cache events | Set `DYN_ROUTER_USE_KV_EVENTS=false` (approximate mode) |\n| Connection refused on port-forward | Port-forward dropped or wrong service name | Re-run port-forward; verify the frontend service name matches the recipe |\n\n## Benchmark\n\nSee `BENCHMARK.md` for the NVCARPS-EVAL performance report (auto-generated by the NVSkills CI pipeline). To refresh, re-run `\u002Fnvskills-ci` on an upstream PR touching this skill.\n\n## References\n\n- Read `references\u002Frouter-modes.md` for the compact mode\u002Fenv map.\n- Use `scripts\u002Fcheck_router_health.py` for endpoint smoke tests.\n",{"name":5,"license":15,"metadata":24,"description":7},{"tags":25,"author":30},[26,27,28,29],"dynamo","router","smoke-test","bring-up","Dan Gil \u003Cdagil@nvidia.com>","main","87afe6ce96220accf50a345dea46784c8c9f210e","YYC3-Skills-技能包\u002FYYC3-Skills-技能包-skills\u002Fplugins\u002Fnvidia-skills\u002Fskills\u002Fdynamo-router-starter",0,"https:\u002F\u002Fgithub.com\u002FYYC-Cube\u002FYYC3-Knowledge-Base","https:\u002F\u002Fkb.yyc3.top\u002F","https:\u002F\u002Fgithub.com\u002FYYC-Cube","万象归元于云枢 | 深栈智启新纪元","2026-11-10 10:37:32",{"source":8,"skillName":5,"commands":41,"prompt":51,"zipAvailable":52},[42,45,48],{"tool":43,"command":44},"npx","npx skills add YYC-Cube\u002FYYC3-Knowledge-Base --skill dynamo-router-starter",{"tool":46,"command":47},"bunx","bunx skills add YYC-Cube\u002FYYC3-Knowledge-Base --skill dynamo-router-starter",{"tool":49,"command":50},"pnpm","pnpm dlx skills add YYC-Cube\u002FYYC3-Knowledge-Base --skill dynamo-router-starter","安装技能，技能地址：https:\u002F\u002Fgithub.com\u002FYYC-Cube\u002FYYC3-Knowledge-Base\u002Fblob\u002Fmain\u002FYYC3-Skills-技能包\u002FYYC3-Skills-技能包-skills\u002Fplugins\u002Fnvidia-skills\u002Fskills\u002Fdynamo-router-starter\u002FSKILL.md",true,[54,60,64,68,74,78],{"path":55,"resourceType":56,"resourceTypeDesc":57,"sizeBytes":58,"sourceHtmlUrl":59},"BENCHMARK.md","REFERENCE","参考文档",2708,"https:\u002F\u002Fgithub.com\u002FYYC-Cube\u002FYYC3-Knowledge-Base\u002Fblob\u002Fmain\u002FYYC3-Skills-技能包\u002FYYC3-Skills-技能包-skills\u002Fplugins\u002Fnvidia-skills\u002Fskills\u002Fdynamo-router-starter\u002FBENCHMARK.md",{"path":61,"resourceType":56,"resourceTypeDesc":57,"sizeBytes":62,"sourceHtmlUrl":63},"evals\u002Fevals.json",3115,"https:\u002F\u002Fgithub.com\u002FYYC-Cube\u002FYYC3-Knowledge-Base\u002Fblob\u002Fmain\u002FYYC3-Skills-技能包\u002FYYC3-Skills-技能包-skills\u002Fplugins\u002Fnvidia-skills\u002Fskills\u002Fdynamo-router-starter\u002Fevals\u002Fevals.json",{"path":65,"resourceType":56,"resourceTypeDesc":57,"sizeBytes":66,"sourceHtmlUrl":67},"references\u002Frouter-modes.md",2132,"https:\u002F\u002Fgithub.com\u002FYYC-Cube\u002FYYC3-Knowledge-Base\u002Fblob\u002Fmain\u002FYYC3-Skills-技能包\u002FYYC3-Skills-技能包-skills\u002Fplugins\u002Fnvidia-skills\u002Fskills\u002Fdynamo-router-starter\u002Freferences\u002Frouter-modes.md",{"path":69,"resourceType":70,"resourceTypeDesc":71,"sizeBytes":72,"sourceHtmlUrl":73},"scripts\u002Fcheck_router_health.py","SCRIPT","脚本",4860,"https:\u002F\u002Fgithub.com\u002FYYC-Cube\u002FYYC3-Knowledge-Base\u002Fblob\u002Fmain\u002FYYC3-Skills-技能包\u002FYYC3-Skills-技能包-skills\u002Fplugins\u002Fnvidia-skills\u002Fskills\u002Fdynamo-router-starter\u002Fscripts\u002Fcheck_router_health.py",{"path":75,"resourceType":56,"resourceTypeDesc":57,"sizeBytes":76,"sourceHtmlUrl":77},"skill-card.md",2414,"https:\u002F\u002Fgithub.com\u002FYYC-Cube\u002FYYC3-Knowledge-Base\u002Fblob\u002Fmain\u002FYYC3-Skills-技能包\u002FYYC3-Skills-技能包-skills\u002Fplugins\u002Fnvidia-skills\u002Fskills\u002Fdynamo-router-starter\u002Fskill-card.md",{"path":79,"resourceType":80,"resourceTypeDesc":81,"sizeBytes":82,"sourceHtmlUrl":83},"skill.oms.sig","OTHER","其他",5077,"https:\u002F\u002Fgithub.com\u002FYYC-Cube\u002FYYC3-Knowledge-Base\u002Fblob\u002Fmain\u002FYYC3-Skills-技能包\u002FYYC3-Skills-技能包-skills\u002Fplugins\u002Fnvidia-skills\u002Fskills\u002Fdynamo-router-starter\u002Fskill.oms.sig",[85,93,100,107,114,121],{"skillNo":86,"name":87,"nameZh":6,"description":88,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":89,"licenseFileUrl":6,"sourceHtmlUrl":90,"categories":91,"keywords":92,"publishedAt":19},"01M7CTDWHERCXPQCP0K03A86AS","vercel-sandbox","Run agent-browser + Chrome inside Vercel Sandbox microVMs for browser automation from any Vercel-deployed app. Use when the user needs browser automation in a Vercel app (Next.js, SvelteKit, Nuxt, Remix, Astro, etc.), wants to run headless Chrome without binary size limits, needs persistent browser sessions across commands, or wants ephemeral isolated browser environments. 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