SageMaker Production Defaults
huggingface/skills
Deploys SageMaker endpoints with autoscaling, CloudWatch alarms and tags on by default, using scripts for real-time, scale-to-zero and async setups.
Diagnose failed or unhealthy Dynamo deployments. An agent skill from NVIDIA/skills.
Install Dynamo Troubleshoot
$ npx skills add NVIDIA/skills --skill dynamo-troubleshoot -a claude-codeProject install by default; add -g for ~/.claude/skills/.
$ gh skill install NVIDIA/skills dynamo-troubleshoot --agent claude-codeProject scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).
$ git clone --depth 1 https://github.com/NVIDIA/skills.git skills-src && mkdir -p .claude/skills && cp -r skills-src/skills/dynamo-troubleshoot .claude/skills/dynamo-troubleshoot && rm -rf skills-srcUse ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.
Claude Code skills documentation · loads skills from .claude/skills/
Install the "dynamo-troubleshoot" agent skill from https://github.com/NVIDIA/skills/tree/main/skills/dynamo-troubleshoot into .claude/skills/dynamo-troubleshoot/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "dynamo-troubleshoot", then confirm the skill loads.Claude Code copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$skill-installer install https://github.com/NVIDIA/skills/tree/main/skills/dynamo-troubleshootType this inside Codex. $skill-installer <name> installs a curated skill from openai/skills. The installer writes to $CODEX_HOME/skills (default ~/.codex/skills). Restart Codex if the skill does not show up.
$ npx skills add NVIDIA/skills --skill dynamo-troubleshoot -a codexProject install goes to .agents/skills/; add -g for ~/.codex/skills/.
$ gh skill install NVIDIA/skills dynamo-troubleshoot --agent codexProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/NVIDIA/skills.git skills-src && mkdir -p .agents/skills && cp -r skills-src/skills/dynamo-troubleshoot .agents/skills/dynamo-troubleshoot && rm -rf skills-srcUse ~/.agents/skills/ instead of .agents/skills for a personal install.
Codex skills documentation · loads skills from .agents/skills/
Install the "dynamo-troubleshoot" agent skill from https://github.com/NVIDIA/skills/tree/main/skills/dynamo-troubleshoot into .agents/skills/dynamo-troubleshoot/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "dynamo-troubleshoot", then confirm the skill loads.Codex copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ npx skills add NVIDIA/skills --skill dynamo-troubleshoot -a cursorProject install goes to .agents/skills/; add -g for ~/.cursor/skills/.
$ gh skill install NVIDIA/skills dynamo-troubleshoot --agent cursorProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/NVIDIA/skills.git skills-src && mkdir -p .cursor/skills && cp -r skills-src/skills/dynamo-troubleshoot .cursor/skills/dynamo-troubleshoot && rm -rf skills-srcUse ~/.cursor/skills/ instead of .cursor/skills for a personal install.
Cursor skills documentation · loads skills from .cursor/skills/, .agents/skills/, .claude/skills/, .codex/skills/
Install the "dynamo-troubleshoot" agent skill from https://github.com/NVIDIA/skills/tree/main/skills/dynamo-troubleshoot into .cursor/skills/dynamo-troubleshoot/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "dynamo-troubleshoot", then confirm the skill loads.Cursor copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ gemini skills install https://github.com/NVIDIA/skills.git --path skills/dynamo-troubleshoot--scope user (default) or --scope workspace; --path is the subfolder of the repo that holds the skill; --consent skips the security confirmation prompt.
$ npx skills add NVIDIA/skills --skill dynamo-troubleshoot -a gemini-cliProject install goes to .agents/skills/; add -g for ~/.gemini/skills/.
$ gh skill install NVIDIA/skills dynamo-troubleshoot --agent gemini-cliProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/NVIDIA/skills.git skills-src && mkdir -p .gemini/skills && cp -r skills-src/skills/dynamo-troubleshoot .gemini/skills/dynamo-troubleshoot && rm -rf skills-srcUse ~/.gemini/skills/ instead of .gemini/skills for a personal install, then run /skills reload.
Gemini CLI skills documentation · loads skills from .gemini/skills/, .agents/skills/
Install the "dynamo-troubleshoot" agent skill from https://github.com/NVIDIA/skills/tree/main/skills/dynamo-troubleshoot into .gemini/skills/dynamo-troubleshoot/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "dynamo-troubleshoot", then confirm the skill loads.Gemini CLI copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ gh skill install NVIDIA/skills dynamo-troubleshootInstalls for Copilot at project scope by default; add --scope user for a personal install. Preview a skill first with gh skill preview. Needs GitHub CLI 2.90.0 or later (public preview).
$ npx skills add NVIDIA/skills --skill dynamo-troubleshoot -a github-copilotProject install goes to .agents/skills/; add -g for ~/.copilot/skills/.
$ git clone --depth 1 https://github.com/NVIDIA/skills.git skills-src && mkdir -p .github/skills && cp -r skills-src/skills/dynamo-troubleshoot .github/skills/dynamo-troubleshoot && rm -rf skills-srcUse ~/.copilot/skills/ instead of .github/skills for a personal install. Commit .github/skills so cloud agent and code review can use it.
GitHub Copilot skills documentation · loads skills from .github/skills/, .claude/skills/, .agents/skills/
Install the "dynamo-troubleshoot" agent skill from https://github.com/NVIDIA/skills/tree/main/skills/dynamo-troubleshoot into .github/skills/dynamo-troubleshoot/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "dynamo-troubleshoot", then confirm the skill loads.GitHub Copilot copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ npx skills add NVIDIA/skills --skill dynamo-troubleshoot -a opencodeOpenCode documents no install command of its own. Project install goes to .agents/skills/; add -g for ~/.config/opencode/skills/.
$ gh skill install NVIDIA/skills dynamo-troubleshoot --agent opencodeProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/NVIDIA/skills.git skills-src && mkdir -p .opencode/skills && cp -r skills-src/skills/dynamo-troubleshoot .opencode/skills/dynamo-troubleshoot && rm -rf skills-srcUse ~/.config/opencode/skills/ instead of .opencode/skills for a personal install.
OpenCode skills documentation · loads skills from .opencode/skills/, .claude/skills/, .agents/skills/
Install the "dynamo-troubleshoot" agent skill from https://github.com/NVIDIA/skills/tree/main/skills/dynamo-troubleshoot into .opencode/skills/dynamo-troubleshoot/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "dynamo-troubleshoot", then confirm the skill loads.OpenCode copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
Facts
- Skill name
dynamo-troubleshoot- GitHub stars
- 3.5k
- Used in
- 1 other repo
- Token cost
- ~1.3k tokens
- SKILL.md length
- 489 words
- Files
- 7 (incl. scripts, references)
- Skills in repo
- 386
- Repo updated
- First seen
- Licence
- Apache-2.0
At a glance
Diagnose failed or unhealthy Dynamo deployments. An agent skill from NVIDIA/skills.
- Works in 4 steps: Collect A Read-Only Bundle → Classify The Failure → Debug Top Down → …
- Model-cache jobs
- SKILL.md covers Purpose, Prerequisites, Instructions and Available Scripts, plus 6 more sections
- Runs Python scripts from its folder; calls python3
What it does
Dynamo Troubleshoot is an agent skill from NVIDIA/skills, published by the product's own GitHub organization. Diagnose failed or unhealthy Dynamo deployments. Use when pods, model-cache jobs, PVCs, workers, frontend/router health, endpoints, or benchmark jobs fail; use recipe-runner/router-starter before this for normal bring-up.
Its SKILL.md is about 1.3k tokens, which your agent loads only when the skill is triggered. The skill folder holds 9 other files, including scripts and reference files (for example `BENCHMARK.md`, `evals/evals.json` and `references/failure-decision-tree.md`).
It sits in DevOps & Cloud, covering Deployment. The repository describes itself as: Agent Skills for NVIDIA products — install into Claude Code, Codex, and other coding agents to run Physical AI, robotics, simulation, CUDA, and RAG workflows end to end. The licence is Apache-2.0.
When your agent uses it
- Model-cache jobs
- Frontend/router health
- Benchmark jobs fail
- Use recipe-runner/router-starter before this for normal bring-up
Example prompts
- “/dynamo-troubleshoot”
Requirements
- Python 3
Workflow steps
4 steps, taken from the step headings in SKILL.md.
What it can do on your machine
Read from SKILL.md and the folder at commit dfdd080. It shows what the files ask for, not the result of running them.
Tool permissions
Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.
From allowed-tools in the SKILL.md frontmatter.
Runs code
Ships 1 file in scripts/ (Python), which the agent can run.
Shell commands in SKILL.md call:
python3
From the folder's file list and the shell code blocks in SKILL.md.
Network
No URLs in SKILL.md.
From URLs in SKILL.md, links to its own repository left out.
Credentials
Names no API keys, tokens, secrets or passwords.
From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.
Context cost
Dynamo Troubleshoot loads about 1.3k tokens when it runs, and up to ~2.2k if it reads all its reference files. Until then it costs about 60 tokens; SKILL.md has 489 words of instructions outside code blocks.
Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.
Safety
Auto-check passed
The automated check found no risky patterns in SKILL.md.
Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); the scripts in this folder are not scanned.
SKILL.md
The full file from NVIDIA/skills at commit dfdd080, republished under its Apache-2.0 licence (© NVIDIA). 489 words, ~1,282 tokens.
Download SKILL.mdSave it as
.claude/skills/dynamo-troubleshoot/SKILL.md (or your agent's skills folder). This skill also uses 6 other files; get the full folder from GitHub.- name
- dynamo-troubleshoot
- description
- Diagnose failed or unhealthy Dynamo deployments. Use when pods, model-cache jobs, PVCs, workers, frontend/router health, endpoints, or benchmark jobs fail; use recipe-runner/router-starter before this for normal bring-up.
- license
- Apache-2.0
- metadata.author
- Dan Gil <dagil@nvidia.com>
- metadata.tags
- dynamo, kubernetes, troubleshooting, day-2
Dynamo Troubleshoot
<!--
SPDX-FileCopyrightText: Copyright (c) 2026 NVIDIA CORPORATION & AFFILIATES. All rights reserved.
SPDX-License-Identifier: CC-BY-4.0
-->Purpose
Turn a Dynamo failure into a clear problem class, strongest signal, and next action. Start with read-only evidence, avoid secrets, and fix one layer at a time.
Prerequisites
- Python 3.10+ on the operator machine.
kubectlconfigured with read access to the target namespace.- Permission to read pods, events, jobs, PVCs, and
DynamoGraphDeploymentresources (NOT secrets). - Network reachability to the cluster API server.
Instructions
1. Collect A Read-Only Bundle
Run:
python3 scripts/collect_dynamo_debug_bundle.py \
--namespace "${NAMESPACE}"If the user names a deployment, include it:
python3 scripts/collect_dynamo_debug_bundle.py \
--namespace "${NAMESPACE}" \
--deployment-name <deployment-name>Do not collect Kubernetes secrets. Do not print Hugging Face tokens.
2. Classify The Failure
Use references/failure-decision-tree.md and classify into one primary bucket:
- cluster/platform
- namespace/secret
- model cache/PVC/download
- image pull/runtime image
- GPU scheduling/resources
- operator/DynamoGraphDeployment reconciliation
- frontend/router
- worker/backend
- endpoint/API
- benchmark/perf job
3. Debug Top Down
Check in this order:
- namespace, storage class, GPU nodes, and HF secret existence
- PVC and model-download job
DynamoGraphDeploymentstatus and events- pod status,
describe pod, and container logs - frontend service and port-forward
/v1/models/v1/chat/completions- benchmark job only after endpoint smoke test passes
4. Fix One Layer At A Time
Prefer the smallest reversible change:
- create missing namespace or HF secret
- patch
storageClassName - patch image tag or image pull secret
- reduce GPU request only if the recipe can still be valid
- switch KV router to approximate mode only if workers do not publish events
- restart failed jobs after fixing the underlying config
After each fix, rerun the relevant readiness check before moving deeper.
Available Scripts
| Script | Purpose | Arguments |
|---|---|---|
scripts/collect_dynamo_debug_bundle.py | Collect a read-only debug bundle (pods, events, jobs, PVCs, CR status) | --namespace, --deployment-name, --output-dir |
Invoke via the agentskills.io run_script() protocol:
run_script("scripts/collect_dynamo_debug_bundle.py", args=["--namespace", "dynamo-demo"])Examples
Collect everything in a namespace for triage:
python3 scripts/collect_dynamo_debug_bundle.py --namespace dynamo-demoScope to a single failing deployment:
python3 scripts/collect_dynamo_debug_bundle.py \
--namespace dynamo-demo \
--deployment-name qwen-vllm-disaggEquivalent through the agent protocol:
run_script("scripts/collect_dynamo_debug_bundle.py", args=["--namespace", "dynamo-demo", "--deployment-name", "qwen-vllm-disagg"])Show full SKILL.md (201 more words)Show less
Output Contract
Return:
- problem class
- evidence checked
- strongest signal
- likely cause
- exact next command or patch
- what was ruled out
- whether it is safe to continue deployment or benchmarking
Limitations
- Read-only. Never mutates the cluster; remediation commands are returned, not executed.
- Will not collect secrets or print Hugging Face tokens; some failure modes (auth) may need user-side inspection.
- Bundle size grows with deployment size; on very large namespaces, scope with
--deployment-name. - Does not validate disagg transport — use
dynamo-interconnect-checkfor that.
Troubleshooting
| Symptom | Likely cause | Next step |
|---|---|---|
kubectl returns Forbidden on events/pods | Service account lacks read RBAC | Ask operator for read-only role binding on the namespace |
Bundle missing DynamoGraphDeployment status | Operator not installed or different namespace | Verify dynamo-platform operator is installed and watching the namespace |
Model-download job in Pending | PVC unbound or HF secret missing | Fix PVC binding or create the named HF secret, then rerun the job |
Worker pods CrashLoopBackOff | Image/runtime mismatch or GPU not available | Inspect container logs; check nvidia.com/gpu allocatable on nodes |
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/failure-decision-tree.mdfor bucket-specific checks. - Use
scripts/collect_dynamo_debug_bundle.pyfor read-only bundle collection.
© NVIDIA, Apache-2.0. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file
Files
SKILL.md and 6 other files (scripts, references) in skills/dynamo-troubleshoot of NVIDIA/skills.
- SKILL.md
- BENCHMARK.md
- evals/evals.json
- references/failure-decision-tree.md
- scripts/collect_dynamo_debug_bundle.py
- skill-card.md
- skill.oms.sig
Open the folder on GitHubat commit dfdd080
Used in 1 other repository
We found 1 copy of this SKILL.md (exact, near-identical or edited) in other folders, from 1 other GitHub owner. This page covers the copy in NVIDIA/skills, which our catalogue first saw on October 7, 2026.
Compare with similar skills
Dynamo Troubleshoot next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.
| Skill | Stars | Used in | Tokens | Auto-check | Licence | Repo updated |
|---|---|---|---|---|---|---|
| Dynamo Troubleshoot this skillNVIDIA/skills | 3.5k | 1 repos | ~1.3k | Automated safety check: Pass | Apache-2.0 | |
| SageMaker Production Defaultshuggingface/skills | 11k | 1 repos | ~6.9k | Automated safety check: Pass | Apache-2.0 | |
| Convex Self Hostingwaynesutton/markdown-site | 628 | — | ~1.4k | Automated safety check: Pass | MIT | |
| Azure AI Agent App DeploymentAzure-Samples/get-started-with-ai-agents | 374 | — | ~4.7k | Automated safety check: Notes | MIT | |
| Setup Workshopbrevdev/workshop-build-an-agent | 146 | — | ~2.3k | Automated safety check: Notes | Apache-2.0 | |
| Byteplus Edge Pages Deploy5zjk5/prompt-engineering | 127 | — | ~3.9k | Automated safety check: Pass | None |
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Related
Questions about Dynamo Troubleshoot
What does Dynamo Troubleshoot do?
Diagnose failed or unhealthy Dynamo deployments. An agent skill from NVIDIA/skills. Dynamo Troubleshoot is an agent skill from NVIDIA/skills, published by the product's own GitHub organization. Diagnose failed or unhealthy Dynamo deployments.
When should I use Dynamo Troubleshoot?
Dynamo Troubleshoot fits situations like: model-cache jobs; frontend/router health; benchmark jobs fail; use recipe-runner/router-starter before this for normal bring-up.
How do I install Dynamo Troubleshoot in Claude Code?
Run `npx skills add NVIDIA/skills --skill dynamo-troubleshoot -a claude-code`. Or copy the skill folder (skills/dynamo-troubleshoot in NVIDIA/skills) into .claude/skills/dynamo-troubleshoot in your project. Claude Code loads it when a task matches its description.
How do I install Dynamo Troubleshoot in Codex?
Run `npx skills add NVIDIA/skills --skill dynamo-troubleshoot -a codex`. Or copy the skill folder (skills/dynamo-troubleshoot in NVIDIA/skills) into .agents/skills/dynamo-troubleshoot in your project. Codex loads it when a task matches its description.
Can I use Dynamo Troubleshoot in Cursor, Gemini CLI or GitHub Copilot?
Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add NVIDIA/skills --skill dynamo-troubleshoot -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/dynamo-troubleshoot, .gemini/skills/dynamo-troubleshoot, .github/skills/dynamo-troubleshoot and .opencode/skills/dynamo-troubleshoot in your project.
What does Dynamo Troubleshoot need to run?
Going by SKILL.md and its folder, Dynamo Troubleshoot needs Python for the scripts in its folder and the command-line tools its instructions call (python3). Our summary lists: Python 3.
Does Dynamo Troubleshoot access the network?
SKILL.md contains no URLs. Any network use would come from the scripts or tools the agent runs. This is read from the text; nothing was executed.
Is Dynamo Troubleshoot safe to install?
Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. The check reads SKILL.md only: the scripts in the folder are not scanned, so read them before running anything.
What licence does Dynamo Troubleshoot use?
Dynamo Troubleshoot is published under the Apache-2.0 licence (declared in SKILL.md). It allows redistribution, so the full SKILL.md is shown on this page.
How many tokens does Dynamo Troubleshoot use?
About 1.3k tokens (SKILL.md is roughly 5.1k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full. Its references folder adds about 959 tokens, read only when the agent opens those files.
What are the alternatives to Dynamo Troubleshoot?
Skills that share tags, products or a category with Dynamo Troubleshoot: SageMaker Production Defaults (huggingface/skills, 11k stars), Convex Self Hosting (waynesutton/markdown-site, 628 stars), Azure AI Agent App Deployment (Azure-Samples/get-started-with-ai-agents, 374 stars) and Setup Workshop (brevdev/workshop-build-an-agent, 146 stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.
Who maintains Dynamo Troubleshoot?
NVIDIA (a GitHub organization, an official publisher) maintains it in NVIDIA/skills, which has 3,546 GitHub stars. The repository holds 386 skills in this directory. The repository was last updated on October 9, 2026.
Source: NVIDIA/skills on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.