Helm Chart Builder Skill for Claude

> This skill should be used when the user asks to "analyze Helm charts", "validate Helm values", "review chart structure", "check Kubernetes Helm templates", or "audit chart dependencies and configuration".

11k tokens

context cost

the whole folder, loaded on every use

files

ships runnable scripts

copies elsewhere

how many repositories repackaged it

447

stars on the repo

on the repository, not the skill itself

Install

one command, takes just this skill from the repository

npx skills add https://github.com/borghei/Claude-Skills --skill helm-chart-builder

What comes with it

39 294 bytes besides the instruction

examples/Chart.yaml

examples/values.yaml

references/helm-best-practices.md

scripts/chart_analyzer.py

scripts/values_validator.py

The instruction itself

17 sections, as written by the author

Helm Chart Builder

> Category: Engineering

> Domain: Kubernetes & Helm

Overview

The Helm Chart Builder skill provides automated analysis of Helm charts including structure validation, values checking, template inspection, and dependency review. It helps teams maintain high-quality charts with correct configurations, proper security contexts, and complete documentation.

Clarify First

Before analyzing the chart, confirm these inputs. If any is unknown or vague, ASK — do not assume:

[ ] Chart path — which chart directory to analyze (sets --path/--chart)
[ ] Values files — which environment values files to validate (sets --values and what gets checked against best practices)
[ ] Strictness — strict/lint mode and JSON for CI (sets --strict --format json and whether findings gate the pipeline)

Stop rule: ask only the 2-3 that most change the output. If the user says "just draft it," proceed and list your assumptions at the top of the artifact.

Quick Start

# Analyze chart structure and quality
python scripts/chart_analyzer.py --path ./charts/my-app

# Validate values.yaml against chart requirements
python scripts/values_validator.py --chart ./charts/my-app --values values-prod.yaml

# JSON output for CI
python scripts/chart_analyzer.py --path ./charts/my-app --format json

# Validate multiple values files
python scripts/values_validator.py --chart ./charts/my-app --values values-dev.yaml values-prod.yaml

Tools Overview

chart_analyzer.py

Analyzes Helm chart structure, metadata, templates, and dependencies.

| Feature | Description |

|---------|-------------|

| Structure validation | Checks required files exist (Chart.yaml, values.yaml, templates/) |

| Metadata check | Validates Chart.yaml fields, version format, appVersion |

| Template review | Inspects templates for common patterns and issues |

| Dependency analysis | Reviews subchart dependencies and version constraints |

| Documentation check | Verifies NOTES.txt and README presence |

values_validator.py

Validates values files against chart expectations and Kubernetes best practices.

| Feature | Description |

|---------|-------------|

| Resource limits | Checks for CPU/memory requests and limits |

| Security context | Validates runAsNonRoot, readOnlyRootFilesystem |

| Replica count | Checks for production-appropriate replica counts |

| Image tags | Flags use of latest or missing image tags |

| Ingress config | Validates ingress annotations and TLS settings |

Workflows

Chart Review Workflow

Analyze structure - Run chart_analyzer.py to check chart organization
Validate defaults - Run values_validator.py against default values.yaml
Check environments - Validate each environment's values file
Review findings - Address critical issues first, then warnings
Re-check - Confirm fixes pass validation

Pre-Release Workflow

Bump version - Update Chart.yaml version and appVersion
Lint chart - Run chart_analyzer.py in strict mode
Validate all values - Check every environment's values file
Check dependencies - Ensure subchart versions are pinned
Package - Chart is ready for helm package

CI Integration

# Structure check
python scripts/chart_analyzer.py --path ./charts/my-app --format json --strict

# Values validation for all environments
for env in dev staging production; do
  python scripts/values_validator.py \
    --chart ./charts/my-app \
    --values "values-${env}.yaml"
done

Reference Documentation

Helm Best Practices - Chart structure, templates, security, dependencies

Common Patterns Quick Reference

Required Chart Structure

my-chart/
  Chart.yaml          # Required: chart metadata
  values.yaml         # Required: default values
  templates/          # Required: template directory
    deployment.yaml
    service.yaml
    _helpers.tpl      # Recommended: template helpers
    NOTES.txt         # Recommended: post-install notes
  charts/             # Optional: subchart dependencies

Values Best Practices

| Setting | Requirement | Why |

|---------|------------|-----|

| resources.limits | Required | Prevents resource exhaustion |

| resources.requests | Required | Enables proper scheduling |

| securityContext.runAsNonRoot | Required | Security baseline |

| image.tag | Required (not latest) | Reproducible deployments |

| replicaCount >= 2 | Recommended for prod | High availability |

| ingress.tls | Recommended | Encrypted traffic |

Chart.yaml Required Fields

| Field | Description |

|-------|-------------|

| apiVersion | v2 for Helm 3 |

| name | Chart name (lowercase) |

| version | SemVer chart version |

| appVersion | Application version |

| description | Brief chart description |

Common Issues

| Issue | Severity | Fix |

|-------|----------|-----|

| Missing Chart.yaml | Critical | Add required chart metadata |

| No resource limits | Warning | Set CPU/memory limits |

| Latest image tag | Warning | Pin specific version |

| No security context | Warning | Add runAsNonRoot: true |

| Missing NOTES.txt | Info | Add post-install notes |

| Unpinned dependencies | Warning | Pin subchart versions |

Other skills for the same job

different authors, same section of the catalogue

Azure Kubernetes Automatic Readiness

by microsoft

vendor ×3

Assess Kubernetes workloads and cluster configuration for AKS Automatic compatibility. Identifies incompatibilities, generates fixes, and guides migration from AKS Standard to AKS Automatic. WHEN: migrate to AKS Automatic, check AKS Automatic readiness, validate manifests for Automatic, assess cluster for Automatic compatibility, fix deployment for Automatic compatibility, identify AKS Automatic migration blockers, is my cluster ready for AKS Automatic.

Discovers available Azure OpenAI model capacity across regions and projects. Analyzes quota limits, compares availability, and recommends optimal deployment locations based on capacity requirements. USE FOR: find capacity, check quota, where can I deploy, capacity discovery, best region for capacity, multi-project capacity search, quota analysis, model availability, region comparison, check TPM availability. DO NOT USE FOR: actual deployment (hand off to preset or customize after discovery), quota increase requests (direct user to Azure Portal), listing existing deployments.

Interactive guided deployment flow for Azure OpenAI models with full customization control. Step-by-step selection of model version, SKU (GlobalStandard/Standard/ProvisionedManaged), capacity, RAI policy (content filter), and advanced options (dynamic quota, priority processing, spillover). USE FOR: custom deployment, customize model deployment, choose version, select SKU, set capacity, configure content filter, RAI policy, deployment options, detailed deployment, advanced deployment, PTU deployment, provisioned throughput. DO NOT USE FOR: quick deployment to optimal region (use preset).

Unified Azure OpenAI model deployment skill with intelligent intent-based routing. Handles quick preset deployments, fully customized deployments (version/SKU/capacity/RAI policy), and capacity discovery across regions and projects. USE FOR: deploy model, deploy gpt, create deployment, model deployment, deploy openai model, set up model, provision model, find capacity, check model availability, where can I deploy, best region for model, capacity analysis. DO NOT USE FOR: listing existing deployments (use foundry_models_deployments_list MCP tool), deleting deployments, agent creation (use agent/create), project creation (use project/create).

Intelligently deploys Azure OpenAI models to optimal regions by analyzing capacity across all available regions. Automatically checks current region first and shows alternatives if needed. USE FOR: quick deployment, optimal region, best region, automatic region selection, fast setup, multi-region capacity check, high availability deployment, deploy to best location. DO NOT USE FOR: custom SKU selection (use customize), specific version selection (use customize), custom capacity configuration (use customize), PTU deployments (use customize).

This skill should be used when working with LaminDB, an open-source data framework for biology that makes data queryable, traceable, reproducible, and FAIR. Use when managing biological datasets (scRNA-seq, spatial, flow cytometry, etc.), tracking computational workflows, curating and validating data with biological ontologies, building data lakehouses, or ensuring data lineage and reproducibility in biological research. Covers data management, annotation, ontologies (genes, cell types, diseases, tissues), schema validation, integrations with workflow managers (Nextflow, Snakemake) and MLOps platforms (W&B, MLflow), and deployment strategies.

Latch platform for bioinformatics workflows. Build pipelines with Latch SDK, @workflow/@task decorators, deploy serverless workflows, LatchFile/LatchDir, Nextflow/Snakemake integration.

Run Python code in the cloud with serverless containers, GPUs, and autoscaling. Use when deploying ML models, running batch processing jobs, scheduling compute-intensive tasks, or serving APIs that require GPU acceleration or dynamic scaling.

17k tokens

How to use it

Copy the folder

Take borghei/helm-chart-builder from the repository into ~/.claude/skills for personal use, or into .claude/skills inside a project.

Check the name does not clash

The agent identifies a skill by the name field in its header. Two skills with the same name cannot sit side by side — one of them will be ignored.