teardown-llm-d-stack

teardown-llm-d-stack is a skill for Claude Code, Codex from llm-d-incubation/llm-d-skills. It costs 114 tokens per session (1,927 once invoked), scanned A, original, Apache-2.0.

A cleanup procedure for removing an llm-d language-model serving deployment from a Kubernetes namespace. It supports Helm and Kustomize deployments and asks for confirmation before deleting resources.

In plain words
What is it for?
Inspecting an llm-d deployment, uninstalling Helm releases, removing Kustomize-managed resources when their files are available, and freeing the namespace's cluster resources.
Why use it?
Leaving unused model-serving resources running consumes cluster capacity. Removing them safely requires first identifying what is installed and which namespace it belongs to.

Skill for Claude CodeCodex

Written for no agent in particular: nothing here depends on one.

Good fit Inspecting an llm-d deployment, uninstalling Helm releases, removing Kustomize-managed resources when their files are available, and freeing the namespace's cluster resources.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/llm-d-incubation/llm-d-skills/teardown-llm-d
Install

Getting it into your agent

One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.

Any agent
npx skills add llm-d-incubation/llm-d-skills --skill teardown-llm-d
Clone the repo
git clone --depth 1 https://github.com/llm-d-incubation/llm-d-skills

Made for: Claude Code, Codex.

Its marketplace also offers this one on its own, as the plugin teardown-llm-d/plugin install teardown-llm-d after adding the marketplace above.

Wrote this? Show the measurements

A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.

agentmods badge for teardown-llm-d-stack

README.md
[![agentmods](https://agentmods.dev/badge/skills/llm-d-incubation/llm-d-skills/teardown-llm-d/github.svg)](https://agentmods.dev/skills/llm-d-incubation/llm-d-skills/teardown-llm-d)
Your own site
<a href="https://agentmods.dev/skills/llm-d-incubation/llm-d-skills/teardown-llm-d"><img src="https://agentmods.dev/badge/skills/llm-d-incubation/llm-d-skills/teardown-llm-d/github.svg" alt="Measured on agentmods" height="20"></a>

Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.

agentmods 80×15 button for teardown-llm-d-stack

Your own site · 80×15
<a href="https://agentmods.dev/skills/llm-d-incubation/llm-d-skills/teardown-llm-d"><img src="https://agentmods.dev/badge/skills/llm-d-incubation/llm-d-skills/teardown-llm-d.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 114 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 1,927 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe.
Origin original No closer match found in the catalogue.
Token cost

What it costs to keep this loaded

Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.

ModelPer sessionOnce invoked
Fable 5.1 $0.00114 $0.01927
Opus 5 $0.00057 $0.00963
Sonnet 5 $0.00023 $0.00385
Haiku 4.5 $0.00011 $0.00193

Measured 12d ago against content hash b97b213911d8, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-12, from the pricing page.

Security

Grade A, and why

teardown-llm-d-stack scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 12d ago.

A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.

Nothing flagged

None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.

skills/teardown-llm-d/SKILL.md · 238 lines

How it starts

The opening of the file, as written. The whole thing — 238 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Teardown llm-d Stack

Purpose

Cleanly remove a deployed llm-d stack from a Kubernetes namespace. Works with both Helm-based deployments (using helmfile or helm) and Kustomize-based deployments (using kubectl apply -k). No local repo is needed for Helm-only teardown, but Kustomize-based resources require access to the kustomization directory. Always confirms with the user before deleting anything.


Step 1: Locate the Stack and Set NAMESPACE

Use the same detection logic as the deploy and benchmark skills:

  1. If the NAMESPACE environment variable is set, use it.
  2. Otherwise check for an active oc project:
    oc project -q 2>/dev/null
    
  3. If neither, ask the user for the namespace.

Verify the stack is present:

kubectl get pods -n $NAMESPACE
helm list -n $NAMESPACE

If no llm-d resources are found, tell the user and stop.


Step 2: Inspect What Is Deployed

Gather a full picture before proposing any changes:

# All Helm releases in the namespace
helm list -n $NAMESPACE

# HTTPRoutes and Gateways
kubectl get httproute,gateway -n $NAMESPACE 2>/dev/null

# All deployments (including those created by Kustomize)
kubectl get deployments -n $NAMESPACE

# All services
kubectl get services -n $NAMESPACE

# All pods
kubectl get pods -n $NAMESPACE

# Check for llm-d labels to identify Kustomize-deployed resources
kubectl get deployments,services,serviceaccounts,podmonitors -n $NAMESPACE -l llm-d.ai/guide 2>/dev/null

Identify deployment method:

  • If Helm releases exist: Helm-based deployment
  • If resources with llm-d.ai/guide labels exist but no Helm releases: Kustomize-based deployment
  • If both exist: Hybrid deployment (common pattern)

Step 3: Present Teardown Plan and Confirm

Before touching anything, show the user exactly what will be removed and ask for confirmation:

Teardown plan for namespace: <NAMESPACE>

Deployment Method: <Helm-based | Kustomize-based | Hybrid>

Helm releases to uninstall:
  - <release-1>
  - <release-2>
  - <release-3>

Kustomize-deployed resources (if applicable):
  - Deployments: <list>
  - Services: <list>
  - ServiceAccounts: <list>
  - PodMonitors: <list>

Not removed unless you choose below:
  HTTPRoutes: <list or "none found">
  Gateways: <list or "none found">

Shall I proceed with the teardown?

Read the full file on GitHub · 238 lines

Files

What ships with it

1 file beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.

Changes

What this file has done since we first saw it

Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.

  1. 12d ago First seen · 238 lines · 114 tokens per session scan A b97b213911d8

Subscribe to this mod's changes

teardown-llm-d-stack is a skill published in the GitHub repository llm-d-incubation/llm-d-skills (6 stars, last pushed 1mo ago), licensed Apache-2.0. It adds 114 tokens to every session and 1,927 once invoked, about $0.0006 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-31.

Related

Other skills, from other repositories

azd-deployment

Deploy containerized frontend + backend applications to Azure Container Apps with remote builds, managed identity, and idempotent infrastructure.

sickn33/agentic-awesome-skills · 29 tokens

openshell-cli

Guide agents through using the OpenShell CLI (openshell) for sandbox management, gateway registration, provider configuration and refresh, policy iteration, settings, service exposure, BYOC workflows, and attached-provider inference. Covers basic through advanced multi-step workflows. Trigger keywords - openshell…

NVIDIA/OpenShell · 128 tokens

langbot-deploy

Deploy and configure a LangBot instance — Docker / Docker Compose, Kubernetes, the config.yaml model, the Box sandbox runtime, the plugin runtime, and the global API key. Use when installing, deploying, upgrading, or configuring LangBot in production or self-hosted environments. Triggers on "deploy langbot", "langbot…

langbot-app/LangBot · 104 tokens

compute-env-setup

Set up a compute environment on a remote provider so Claude Science jobs can run there. Covers direct SSH/conda hosts, Slurm clusters, container-via-bridge runners, and managed-API providers (Modal, GCP, RunPod). Use when standing up a new provider, porting an env to a different backend, adding a tool that needs its…

UnicomAI/wanwu · 134 tokens

azure-cloud-migrate

Assess and migrate cross-cloud workloads to Azure with reports and code conversion. Supports Lambda→Functions, Beanstalk/Heroku/App Engine→App Service, Fargate/Kubernetes/Cloud Run/Spring Boot→Container Apps. WHEN: migrate Lambda to Functions, AWS to Azure, migrate Beanstalk, migrate Heroku, migrate App Engine, Cloud…

microsoft/skills · 106 tokens

atmos-helmfile

Helmfile orchestration: sync/apply/destroy/diff, Kubernetes deployments, varfile generation, EKS integration, source management.

cloudposse/atmos · 33 tokens