Ring:Creating Helm Charts logo

Ring:Creating Helm Charts

Organization
LerianStudio
ring:creating-helm-charts

Creating Helm charts to Lerian conventions via ring:helm: standardized chart structure, full env-var coverage from .env.example, security defaults (runAsNonRoot, readOnlyRootFilesystem), ClusterIP-only services, and health probes; validates helm lint and template render. Use when creating, modifying, or reviewing a chart, or migrating docker-compose to Helm. Skip for app-code-only changes or docker-compose-only deployments.

Overview

PublisherLerianStudio
Repositoryring
Skill namering:creating-helm-charts
Stars
215
Forks
28
Bundled files
Instructions only
LicenseApache-2.0
Links
  • Markdown instructions

    A SKILL.md file the model loads on demand, so it only costs tokens when a request actually matches.

  • Works with any LLM

    AI skills are plain Markdown, not provider-specific code, so this works with GPT, Claude, Gemini, Grok, or a local model.

  • Self-contained

    Everything the model needs lives in the instructions — no extra files to sync.

  • Open source

    Published by LerianStudio on GitHub. Read the source before you install it.

Installation

Install the Ring:Creating Helm Charts AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

1

Install in TypingMind

TypingMind installs a skill straight from its GitHub folder — it reads SKILL.md, bundles the resource files, and stores the result locally.

  1. Open the app and go to Plugins → Skills.
  2. Choose "Install from GitHub".
  3. Paste the skill folder URL below and confirm.
  4. Enable the skill in any chat where you want it available.
Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.
2

Install in another agent

Any agent that reads the Agent Skills format can use this skill — copy the folder into that agent's skills directory.

Claude Code — .claude/skills
git clone --depth 1 https://github.com/LerianStudio/ring.git /tmp/ring
mkdir -p .claude/skills
cp -r /tmp/ring/dev-team/skills/creating-helm-charts .claude/skills/lerianstudio-ring-creating-helm-charts
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Ring:Creating Helm Charts in any TypingMind chat and the model takes it from there. Its name and description sit in the system prompt, and the moment a request matches, the model loads the full instructions itself — you never invoke it by hand, and it costs no tokens until it is actually used.

The model loads Ring:Creating Helm Charts on its own as soon as a request matches it.

Works with any AI model

AI skills are plain Markdown instructions rather than provider-specific code, so Ring:Creating Helm Charts is not tied to the model it was written for. Install it once in TypingMind and use it with GPT-5, Claude, Gemini, Grok, DeepSeek, Mistral, Llama, or a local model you run yourself — all on your own API keys.

  • Loaded only when it is needed

    The system prompt carries just the name and description. The instructions are fetched on the first matching request, so an idle skill costs nothing.

  • Switch models mid-chat

    Because the skill is instructions rather than code, changing model does not break it — the next model reads the same SKILL.md.

Skill instructions

This is the SKILL.md content the model loads. Read it before installing — a skill is instructions your model will follow.

Helm Chart Creation & Maintenance

When to use

  • Creating a new Helm chart for any Lerian service
  • Modifying an existing Helm chart (adding components, dependencies, templates)
  • Reviewing a Helm chart PR for convention compliance
  • Migrating a docker-compose setup to Helm

Skip when

  • Modifying only application code (no chart changes)
  • Working on non-Helm deployment (docker-compose only) → use backend engineer via ring:implementing-tasks

Sequence

Standalone/on-demand. Not part of the lean backend dev-cycle.

Related

Complementary: ring:implementing-tasks

Standards reference: dev-team/docs/standards/helm/ Executor agent: ring:helm

You orchestrate. ring:helm creates chart files.

Step 1: Validate Input

Required: service_name, chart_type (single|multi-component|umbrella), components (non-empty). Optional: dependencies (postgresql, mongodb, rabbitmq, valkey, keda), has_worker, namespace.

Step 2: Naming Convention

Default: {service_name}-helm  (e.g., reporter-helm, tracer-helm)
Exceptions (no -helm suffix):
  - plugin-access-manager
  - otel-collector-lerian

Step 3: Dispatch Agent

yaml
Task:
  subagent_type: "ring:helm"
  description: "Create Helm chart for {service_name}"
  prompt: |
    ## Helm Chart Creation

    service_name: {service_name}
    components: {components}
    dependencies: {dependencies}
    chart_type: {chart_type}
    namespace: {namespace}

    Standards: Load dev-team/docs/standards/helm/ files.

    ## Required Steps
    1. Read application .env.example and bootstrap/config.go
       — extract ALL env vars (missing vars = CrashLoopBackOff)
    2. Verify health check endpoint in application source
    3. Create chart structure:

    charts/{service_name}-helm/
    ├── Chart.yaml
    ├── values.yaml
    ├── templates/
    │   ├── _helpers.tpl
    │   ├── deployment.yaml
    │   ├── service.yaml
    │   ├── configmap.yaml
    │   ├── secret.yaml (if secrets exist)
    │   ├── hpa.yaml (optional)
    │   └── serviceaccount.yaml
    └── charts/ (dependencies)

    4. Chart.yaml: name, version, appVersion, description, type: application
    5. _helpers.tpl: name, fullname, chart, labels, selectorLabels, versionLabelValue
    6. values.yaml structure:
       - global: replicaCount, image.repository/tag/pullPolicy
       - Per-component config sections
       - configmap: all non-secret env vars
       - secrets: all sensitive env vars (no real values)
       - service: type: ClusterIP, port, targetPort
       - resources: requests/limits
       - probes: livenessProbe, readinessProbe (match /health and /readyz)
       - dependencies config sections

    7. Security defaults:
       - securityContext: runAsNonRoot: true, runAsUser: 1000
       - readOnlyRootFilesystem: true
       - allowPrivilegeEscalation: false

    8. Service type: ALWAYS ClusterIP (never NodePort or LoadBalancer)

    ## Required Output
    - Env Var Coverage table (100% of .env.example covered)
    - helm lint result: MUST PASS
    - helm template render: MUST produce valid YAML
    - Files created list

Step 4: Validate Output

if env_vars_missing > 0:
  → FAIL: list missing vars, re-dispatch

if helm lint fails:
  → Re-dispatch with specific lint errors

if all checks PASS:
  → Proceed to worker setup or final validation

Worker Chart (if has_worker = true)

Additional dispatch for worker component:

  • Separate Deployment without Service
  • Different resource limits (CPU-focused, no port exposure)
  • Same configmap/secrets references
  • LivenessProbe via process check (not HTTP)

Validation Checklist

markdown
## Helm Chart Validation

| Check | Status | Evidence |
|-------|--------|----------|
| Env var coverage (100%) | ✅/❌ | X/Y vars mapped |
| helm lint PASS | ✅/❌ | command output |
| helm template renders | ✅/❌ | YAML valid |
| Security context set | ✅/❌ | deployment.yaml:{line} |
| Service type = ClusterIP | ✅/❌ | service.yaml:{line} |
| Health probes match endpoints | ✅/❌ | deployment.yaml:{line} |
| No real secrets in values | ✅/❌ | |

Frequently asked questions

What does the Ring:Creating Helm Charts AI skill do?

Creating Helm charts to Lerian conventions via ring:helm: standardized chart structure, full env-var coverage from .env.example, security defaults (runAsNonRoot, readOnlyRootFilesystem), ClusterIP-only services, and health probes; validates helm lint and template render. Use when creating, modifying, or reviewing a chart, or migrating docker-compose to Helm. Skip for app-code-only changes or docker-compose-only deployments.

Why use Ring:Creating Helm Charts on TypingMind?

Because you install it once and use it with any model. Ring:Creating Helm Charts is plain Markdown rather than provider-specific code, so the same skill runs on GPT-5, Claude, Gemini, Grok, or a local model — and you can switch model mid-chat without it breaking. TypingMind runs on your own API keys, so you pay providers directly instead of a per-seat subscription, and your skills and chats stay in your own storage.

How do I install Ring:Creating Helm Charts in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/LerianStudio/ring/tree/main/dev-team/skills/creating-helm-charts. TypingMind reads its SKILL.md and installs it as a skill you can enable per chat.

Which AI models can use Ring:Creating Helm Charts?

Any model you connect in TypingMind. AI skills are plain Markdown instructions rather than provider-specific code, so GPT, Claude, Gemini, Grok, and local models can all load this skill when a request matches it.

How many AI models can I use with Ring:Creating Helm Charts?

As many as you like. As long as a model supports skills, you can use Ring:Creating Helm Charts with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.

Is the Ring:Creating Helm Charts AI skill free?

Yes. It is published on GitHub by LerianStudio under the Apache-2.0 license. You only pay your own AI provider for the tokens you use.

What are AI skills?

An AI skill is a reusable instruction bundle that teaches an AI model how to do one specific task. It follows the open Agent Skills format: a SKILL.md file with a name and description, plus any scripts, templates or reference files the model may need. The model reads the instructions only when your request matches the skill, so an installed skill costs nothing until it is used.

How are AI skills different from plugins or MCP servers?

A plugin or MCP server gives a model new tools to call — code that runs somewhere and returns a result. An AI skill gives the model knowledge and process instead: how to approach a task, which steps to follow, what good output looks like. Skills are plain Markdown, so they need no server, no API key and no runtime, and they work with any model.

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