nvidia-skill-finder
Use for NVIDIA-related requests where an NVIDIA skill might help, even if the user did not ask for a skill. Trigger on NVIDIA products, hardware, software,…
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.
$ npx -y skills add NVIDIA/skills --skill dynamo-router-starter --agent claude-codeHow it fires
How this skill gets triggered: by you, by Claude, or both.
/dynamo-router-starterContext preview
The summary Claude sees to decide when to auto-load this skill.
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.
name: dynamo-router-starter
description: 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.
license: Apache-2.0
metadata:
author: Dan Gil <dagil@nvidia.com>
tags:
- dynamo
- router
- smoke-test
- bring-up<!-- SPDX-FileCopyrightText: Copyright (c) 2026 NVIDIA CORPORATION & AFFILIATES. All rights reserved. SPDX-License-Identifier: CC-BY-4.0 -->
Make Dynamo routing feel easy by getting a baseline router mode running, enabling KV-aware routing when appropriate, and proving the endpoint works. Keep the user focused on exact commands and success signals, not router internals.
Collect or infer:
For local bring-up with already registered workers:
python3 -m dynamo.frontend --router-mode round-robin --http-port 8000
For Kubernetes, inspect the selected recipe `deploy.yaml` and locate the frontend service. If the recipe is not already deployed, use `dynamo-recipe-runner` first.
For local frontend:
python3 -m dynamo.frontend --router-mode kv --http-port 8000
For Kubernetes, patch only the frontend service env:
envs:
- name: DYN_ROUTER_MODE
value: kvIf backend workers are not publishing KV cache events, set approximate mode instead of leaving the router waiting for events:
envs:
- name: DYN_ROUTER_USE_KV_EVENTS
value: "false"After port-forwarding the frontend service or starting local frontend, run:
python3 scripts/check_router_health.py \ --base-url http://127.0.0.1:8000
This must verify `/v1/models` and, when a model is discoverable, one `/v1/chat/completions` request.
When comparing round-robin vs KV routing:
If the endpoint is unhealthy or workers are missing, switch to `dynamo-troubleshoot`.
| Script | Purpose | Arguments | |---|---|---| | `scripts/check_router_health.py` | Smoke-test `/v1/models` and one chat completion against a Dynamo frontend | `--base-url`, `--retries`, `--timeout` |
Invoke via the agentskills.io `run_script()` protocol:
run_script("scripts/check_router_health.py", args=["--base-url", "http://127.0.0.1:8000"])Local KV-routed frontend on port 8000, then smoke-test it:
python3 -m dynamo.frontend --router-mode kv --http-port 8000 & python3 scripts/check_router_health.py --base-url http://127.0.0.1:8000
Kubernetes-deployed frontend reachable via port-forward:
kubectl port-forward svc/qwen-vllm-disagg-frontend 8000:8000 -n dynamo-demo & python3 scripts/check_router_health.py --base-url http://127.0.0.1:8000 --retries 3
Equivalent through the agent protocol:
run_script("scripts/check_router_health.py", args=["--base-url", "http://127.0.0.1:8000", "--retries", "3"])Return:
| Symptom | Likely cause | Next step | |---|---|---| | `/v1/models` returns empty list | No worker registered with the frontend | Verify worker pods are Ready; confirm they connect to the same etcd/NATS | | Smoke chat request times out | Frontend up, workers not serving | Switch to `dynamo-troubleshoot`; inspect worker logs | | KV mode hangs | Workers do not publish KV cache events | Set `DYN_ROUTER_USE_KV_EVENTS=false` (approximate mode) | | Connection refused on port-forward | Port-forward dropped or wrong service name | Re-run port-forward; verify the frontend service name matches the recipe |
See `BENCHMARK.md` for the NVCARPS-EVAL performance report (auto-generated by the NVSkills CI pipeline). To refresh, re-run `/nvskills-ci` on an upstream PR touching this skill.
Official, NVIDIA-verified Agent Skills for Claude Code, Codex, and other coding agents.
Use for NVIDIA-related requests where an NVIDIA skill might help, even if the user did not ask for a skill. Trigger on NVIDIA products, hardware, software,…
Official NVIDIA-authored guidance for NVIDIA cuDF GPU DataFrames, pandas acceleration, dask-cuDF, ETL, joins, groupby, CSV/Parquet I/O, nullable semantics, and…
Use when asked to install, deploy, run, validate, troubleshoot, or stop NVIDIA AI-Q Blueprint infrastructure.
Use when asked to run deep research or AI-Q research through a reachable NVIDIA AI-Q Blueprint backend.
Calibrate a new dataset from live RTSP camera streams via the AutoMagicCalib REST API. Use when the user provides RTSP URLs or asks to calibrate live cameras;…
Run end-to-end calibration on the shipped sample dataset (sdg_08_2_sample_data_010926.zip) against a running AMC microservice. Use when user says 'test sample…