本文へ移動
cccskills
無料GitHub で公開

dynamo-router-starter

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.

インストール方法を見る

含まれるファイル(8)

  • SKILL.md5.6 KB
  • agents/openai.yaml303 B
  • BENCHMARK.md2.6 KB
  • evals/evals.json3.0 KB
  • references/router-modes.md2.1 KB
  • scripts/check_router_health.py4.7 KB
  • skill-card.md2.4 KB
  • skill.oms.sig5.0 KB

SKILL.md(原文)

インストールする前に、エージェントに与えられる指示の中身を確認できます。

Dynamo Router Starter

<!-- SPDX-FileCopyrightText: Copyright (c) 2026 NVIDIA CORPORATION & AFFILIATES. All rights reserved. SPDX-License-Identifier: CC-BY-4.0 -->

Purpose

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.

Prerequisites

  • Python 3.10+ with the dynamo package importable (python3 -m dynamo.frontend --help works).
  • For Kubernetes runs: kubectl configured with access to the target namespace and a deployed Dynamo recipe.
  • Network reachability to the frontend service (port-forward or direct).
  • A model already loaded into at least one worker (/v1/models returns at least one entry).

Required Inputs

Collect or infer:

  • local Python/CLI or Kubernetes recipe path
  • desired mode: round-robin, kv, least-loaded, device-aware-weighted, direct, or random
  • frontend port or Kubernetes frontend service
  • whether workers publish KV events; if not, use approximate KV mode
  • model name for smoke requests, if /v1/models cannot discover it

Instructions

1. Establish A Baseline

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.

2. Enable KV Routing

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: kv

If 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"

3. Smoke Test

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.

4. Compare Modes Carefully

When comparing round-robin vs KV routing:

  • use the same model, workers, prompt set, concurrency, and sampling settings
  • send repeated-prefix prompts if demonstrating KV reuse
  • label the result as a smoke comparison unless enough benchmark samples were collected
  • do not claim throughput improvement from a single chat request

If the endpoint is unhealthy or workers are missing, switch to dynamo-troubleshoot.

Available Scripts

ScriptPurposeArguments
scripts/check_router_health.pySmoke-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"])

Examples

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"])

Output Contract

Return:

  • mode selected and why
  • local command or Kubernetes env patch
  • frontend service or URL
  • smoke-test result
  • any limitation, such as approximate KV mode or missing worker KV events
  • next command to run for a fuller comparison

Limitations

  • Smoke test is one chat completion; it is not a benchmark. Use dynamo-benchmark for throughput/latency numbers.
  • KV-aware mode without worker KV-event publication degrades to approximate mode; this skill flags but does not fix the underlying worker config.
  • Mode comparisons require matched workloads; cross-mode latency claims need separate benchmark runs.

Troubleshooting

SymptomLikely causeNext step
/v1/models returns empty listNo worker registered with the frontendVerify worker pods are Ready; confirm they connect to the same etcd/NATS
Smoke chat request times outFrontend up, workers not servingSwitch to dynamo-troubleshoot; inspect worker logs
KV mode hangsWorkers do not publish KV cache eventsSet DYN_ROUTER_USE_KV_EVENTS=false (approximate mode)
Connection refused on port-forwardPort-forward dropped or wrong service nameRe-run port-forward; verify the frontend service name matches the recipe

Benchmark

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.

References

  • Read references/router-modes.md for the compact mode/env map.
  • Use scripts/check_router_health.py for endpoint smoke tests.

レビュー

まだレビューはありません。使ってみた感想をお寄せください。

同じリポジトリのスキル

概要と使いどころ

Make data visualizations accessible and inclusive. Use when the user needs chart or diagram accessibility guidance, text alternatives for complex visuals, color and contrast review, keyboard support, reduced-motion behavior for animation or parallax, or an accessibility QA workflow for exported figures, UML-like diagrams, and dashboards.

日本語の概要は準備中です。原文の説明を表示しています。

openai/plugins7,3922026年10月8日 更新

Apply consistent photo adjustments across a set of images so they look like they were edited together. Use this skill whenever the user says "make my photos look cohesive", "give all these the same style", "apply a warm and golden feel to all of these", "make this cinematic", "match the look across my photos", "edit all my travel photos the same way", "batch edit these", "make these consistent", "fix my phone photos", or uploads a folder of photos and wants a unified, polished result. Also triggers for requests like "apply a preset to all of these", "make these look professional", or "they were shot in mixed lighting — can you fix them all". Outputs direct final image URLs plus an in-chat preview grid and optional Firefly Board link. Access: 🔐 Signed-In required | Gen AI: ❌

日本語の概要は準備中です。原文の説明を表示しています。

openai/plugins7,3922026年10月8日 更新

Use when a user wants to see their logo, design, or sketch on a product or scene mockup — mugs, t-shirts, business cards, hats, phone screens, posters, billboards, or similar. Triggers on "create mockups", "show my logo on products", or any logo upload with a request to visualize it on items. Access: 🔐 Signed-In required | Gen AI: ✅ Adobe Firefly via `image_generate` used for design creation, sketch polishing, and mockup scene generation

日本語の概要は準備中です。原文の説明を表示しています。

openai/plugins7,3922026年10月8日 更新

Resize, crop, or export any image or video into platform-ready social media assets using Adobe Creative Cloud tools. Use this skill when a user wants to prepare a photo, image, or video for one or more social platforms — Instagram, TikTok, LinkedIn, Facebook, YouTube, Snapchat, Pinterest, Threads, or X/Twitter. Triggers on: "prepare my image for Instagram", "resize for TikTok", "get this ready to post", "make versions for all platforms", "social media sizes", "crop for stories", "export for LinkedIn", "resize my video for social", "make social media assets", or any request to adapt a photo or video for specific platforms. Handles subject-aware cropping, AI canvas expansion, test previews before full runs, and same-ratio video resizing.

日本語の概要は準備中です。原文の説明を表示しています。

openai/plugins7,3922026年10月8日 更新

Create any visual design using Adobe Express templates — flyers, posters, social media posts (Instagram, Facebook, LinkedIn), business cards, invitations, greeting cards, resumes, cover letters, brochures, newsletters, certificates, presentations, YouTube thumbnails, email headers, logos, menus, and labels. Use this skill whenever the user wants to make, design, or build any visual — even if they just say "make me a flyer", "design a poster", "I need something for Instagram", "create an event invite", or "make a business card". Also handles browsing templates, editing text, replacing images, changing backgrounds, animating, and exporting designs. Access: 🔐 Signed-In required | Gen AI: ❌ by default — image replacement only where the surface permits generative AI (e.g. Codex); none on Claude

日本語の概要は準備中です。原文の説明を表示しています。

openai/plugins7,3922026年10月8日 更新

Create a punchy sizzle reel from a video using Adobe Quick Cut. Use this skill whenever a user wants to cut, trim, or shorten a video into highlights — including phrases like "make a sizzle reel", "make a highlight reel", "quick cut this", "cut the best parts", "shorten this video", "make a highlight clip", "summarize this video visually", or any request to produce a shorter edited version of a video. Use this skill for Quick Cut requests before suggesting manual editing in Premiere. Requires the user to upload a video file.

日本語の概要は準備中です。原文の説明を表示しています。

openai/plugins7,3922026年10月8日 更新

openai のスキルをすべて見る

このスキルの問題を報告する