--- title: "Kubernetes YAML Validator" description: "This skill provides a comprehensive validation workflow for Kubernetes YAML resources, combining syntax linting, schema validation, cluster dry-run testing, and intelligent CRD documentation lookup. Validate any Kubernetes manifest with confidence before applying it to the cluster." type: skill canonical_url: https://claudary.paisolsolutions.com/skills/skill-101 source: "Claudary" difficulty: intermediate author: "Claude Code Knowledge Pack" date: 2026-07-10T11:43:31.357Z license: CC-BY-4.0 attribution: "Kubernetes YAML Validator — Claudary (https://claudary.paisolsolutions.com/skills/skill-101)" --- # Kubernetes YAML Validator This skill provides a comprehensive validation workflow for Kubernetes YAML resources, combining syntax linting, schema validation, cluster dry-run testing, and intelligent CRD documentation lookup. Validate any Kubernetes manifest with confidence before applying it to the cluster. ## Overview --- name: k8s-yaml-validator description: Validate, lint, audit, or dry-run Kubernetes manifests (Deployment, Service, ConfigMap, CRD). --- # Kubernetes YAML Validator ## Overview This skill provides a comprehensive validation workflow for Kubernetes YAML resources, combining syntax linting, schema validation, cluster dry-run testing, and intelligent CRD documentation lookup. Validate any Kubernetes manifest with confidence before applying it to the cluster. **IMPORTANT: This is a REPORT-ONLY validation tool.** Do NOT modify files, do NOT use Edit tool, do NOT use AskUserQuestion to offer fixes. Generate a comprehensive validation report with suggested fixes shown as before/after code blocks, then let the user decide what to do next. ## Trigger Phrases Use this skill when prompts look like: - "Validate this Kubernetes YAML before deploy." - "Lint these manifests and report what is broken." - "Check this CRD manifest and explain schema issues." - "Run dry-run checks on this manifest." - "Find line-level errors in this multi-document YAML." ## When to Use This Skill Invoke this skill when: - Validating Kubernetes YAML files before applying to a cluster - Debugging YAML syntax or formatting errors - Working with Custom Resource Definitions (CRDs) and need documentation - Performing dry-run tests to catch admission controller errors - Ensuring YAML follows Kubernetes best practices - Understanding what validation errors exist in manifests (report-only, user fixes manually) - The user asks to "validate", "lint", "check", or "test" Kubernetes YAML files ## Read-Only Boundary (Mandatory) This skill is strictly report-only: - Do NOT modify any user files. - Do NOT run Edit for fixes. - Do NOT ask for permission to apply fixes. - Do provide before/after snippets as suggestions in the report. ## Deterministic Path Setup Run with explicit paths so commands are repeatable: ```bash REPO_ROOT="$(git rev-parse --show-toplevel 2>/dev/null)" SKILL_DIR="$REPO_ROOT/devops-skills-plugin/skills/k8s-yaml-validator" TARGET_FILE="$REPO_ROOT/" ``` Path checks: - If `REPO_ROOT` is empty, stop and ask for repository root. - If `SKILL_DIR` does not exist, stop and report path mismatch. - If `TARGET_FILE` does not exist, stop and ask for the correct file. ## Validation Workflow Follow this sequential validation workflow. Each stage catches different types of issues: ### Stage 0: Pre-Validation Setup (Deterministic Resource Count) Before running validators, count documents using the bundled script: ```bash python3 "$SKILL_DIR/scripts/count_yaml_documents.py" "$TARGET_FILE" ``` Expected output (example): ```json { "file": ".../manifests.yaml", "documents": 3, "separators": 2 } ``` Gate rules: - If `documents >= 3`, load `references/validation_workflow.md` before Stage 1. - Always include the document count in the final report summary. - If `python3` is unavailable, use fallback: ```bash awk 'BEGIN{d=0;seen=0} /^[[:space:]]*---[[:space:]]*$/ {if(seen){d++;seen=0}; next} /^[[:space:]]*#/ {next} NF{seen=1} END{if(seen)d++; print d}' "$TARGET_FILE" ``` and mark the count as `estimated` in the report. ### Stage 1: Tool Check Before starting validation, verify required tools are installed: ```bash bash "$SKILL_DIR/scripts/setup_tools.sh" ``` Required tools: - **yamllint**: YAML syntax and style linting - **kubeconform**: Kubernetes schema validation with CRD support - **kubectl**: Cluster dry-run testing (optional but recommended) If tools are missing, display installation guidance from script output and continue with available tools. Document missing tools and skipped stages in the report. ### Stage 2: YAML Syntax Validation Validate YAML syntax and formatting using yamllint: ```bash yamllint -c "$SKILL_DIR/assets/.yamllint" "$TARGET_FILE" ``` **Common issues caught:** - Indentation errors (tabs vs spaces) - Trailing whitespace - Line length violations - Syntax errors - Duplicate keys **Reporting approach:** - Report all syntax issues with file:line references - For fixable issues, show suggested before/after code blocks - Continue to next validation stage to collect all issues before reporting ### Stage 3: CRD Detection and Documentation Lookup Before schema validation, detect if the YAML contains Custom Resource Definitions: ```bash bash "$SKILL_DIR/scripts/detect_crd_wrapper.sh" "$TARGET_FILE" ``` The wrapper script automatically handles Python dependencies by creating a temporary virtual environment if PyYAML is not available. **Resilient Parsing:** The script is resilient to syntax errors in individual documents. If a multi-document YAML file has some valid and some invalid documents, the script will: - Parse valid documents and detect their CRDs - Report errors for invalid documents but continue processing - This matches kubeconform's behavior of validating 2/3 resources even when 1/3 has syntax errors The script outputs JSON with resource information and parse status: ```json { "resources": [ { "kind": "Certificate", "apiVersion": "cert-manager.io/v1", "group": "cert-manager.io", "version": "v1", "isCRD": true, "name": "example-cert" } ], "parseErrors": [ { "document": 1, "start_line": 2, "error_line": 6, "error": "mapping values are not allowed in this context" } ], "summary": { "totalDocuments": 3, "parsedSuccessfully": 2, "parseErrors": 1, "crdsDetected": 1 } } ``` **For each detected CRD:** 1. **Try Context7 MCP first (preferred):** - Resolve library: - Tool: `mcp__context7__resolve-library-id` - `libraryName`: CRD project name (example: `cert-manager` for `cert-manager.io`) - Query docs: - Tool: `mcp__context7__query-docs` - `libraryId`: resolved library ID from previous step - `query`: include CRD kind, group, and version (example: `Certificate cert-manager.io v1 required fields in spec`) 2. **Fallback to `web.search_query` if Context7 fails or returns insufficient details:** ``` Search query pattern: "" "" kubernetes CRD "" documentation spec Example: "Certificate" "cert-manager.io" kubernetes CRD "v1" documentation spec ``` 3. **Extract key information:** - Required fields in `spec` - Field types and validation rules - Examples from documentation - Version-specific changes or deprecations **Secondary CRD Detection via kubeconform:** If `detect_crd_wrapper.sh` cannot identify CRDs (for example, syntax errors in all documents), but kubeconform still validates a CRD resource, look up docs for that CRD anyway. Parse kubeconform output to identify validated CRDs and perform Context7/`web.search_query` lookups. **Why this matters:** CRDs have custom schemas not available in standard Kubernetes validation tools. Understanding the CRD's spec requirements prevents validation errors and ensures correct resource configuration. ### Stage 4: Schema Validation Validate against Kubernetes schemas using kubeconform: ```bash kubeconform \\ -schema-location default \\ -schema-location 'https://raw.githubusercontent.com/datreeio/CRDs-catalog/main/{{.Group}}/{{.ResourceKind}}_{{.ResourceAPIVersion}}.json' \\ -strict \\ -ignore-missing-schemas \\ -summary \\ -verbose \\ "$TARGET_FILE" ``` **Options explained:** - `-strict`: Reject unknown fields (recommended for production - catches typos) - `-ignore-missing-schemas`: Skip validation for CRDs without available schemas - `-kubernetes-version 1.30.0`: Validate against specific K8s version **Common issues caught:** - Invalid apiVersion or kind - Missing required fields - Wrong field types - Invalid enum values - Unknown fields (with -strict) **For CRDs:** If kubeconform reports "no schema found", this is expected. Use the documentation from Stage 3 to manually validate the spec fields. **kubeconform line number behavior — two distinct cases:** kubeconform does NOT report file-absolute line numbers. You must translate: 1. **Parse errors** (e.g. `error converting YAML to JSON: yaml: line N`): - `N` is **document-relative** (line N within that document's content). - Convert to file-absolute: `file_line = doc_start_line + N - 1` - `doc_start_line` comes from the `start_line` field in `detect_crd_wrapper.sh` output. - Example: document starts at file line 4, kubeconform says `yaml: line 5` → file-absolute line = 4 + 5 − 1 = **line 8** (matches yamllint output). 2. **Schema validation errors** (e.g. `got string, want integer`): - kubeconform reports **JSON path only**, no line number. - Example: `at '/spec/template/spec/containers/0/ports/0/containerPort': got string, want integer` - To find the line: search the YAML file for the field name (e.g. `containerPort`) within the relevant document section, using file-absolute line numbers from the surrounding context. Always present line numbers as file-absolute in the validation report even when translating from kubeconform's document-relative output. ### Stage 5: Cluster Dry-Run (if available) **IMPORTANT: Always try server-side dry-run first.** Server-side validation catches more issues than client-side because it runs through admission controllers and webhooks. **Decision Tree:** ``` 1. Try server-side dry-run first: kubectl apply --dry-run=server -f "$TARGET_FILE" └─ If SUCCESS → Use results, continue to Stage 6 └─ If FAILS with connection error (e.g., "connection refused", "unable to connect", "no configuration"): │ ├─ 2. Attempt client-side dry-run (parse-only fallback): │ kubectl apply --dry-run=client --validate=false -f "$TARGET_FILE" │ │ ├─ If SUCCESS: │ │ Document in report: "Server-side validation skipped (no cluster access); client fallback ran in parse-only mode" │ │ │ └─ If FAILS with discovery/openapi error (e.g., "unable to recognize", │ "failed to download openapi", "couldn't get current server API group list"): │ Document in report: "Dry-run skipped (cluster discovery unavailable)" │ Continue to Stage 6 │ └─ If FAILS with validation error (e.g., "admission webhook denied", "resource quota exceeded", "invalid value"): └─ Record the error, continue to Stage 6 └─ If FAILS with parse error (e.g., "error converting YAML to JSON", "yaml: line X: mapping values are not allowed"): └─ Record the error, skip client-side dry-run (same error will occur) Document in report: "Dry-run blocked by YAML syntax errors - fix syntax first" Continue to Stage 6 ``` **Note:** Parse errors from earlier stages (yamllint, kubeconform) will also cause dry-run to fail. Do NOT attempt client-side dry-run as a fallback for parse errors - it will produce the same error. Parse errors must be fixed before dry-run validation can proceed. **Server-side dry-run catches:** - Admission controller rejections - Policy violations (PSP, OPA, Kyverno, etc.) - Resource quota violations - Missing namespaces - Invalid ConfigMap/Secret references - Webhook validations **Client-side dry-run with `--validate=false` catches (fallback, when command succeeds):** - YAML/JSON conversion and request-construction issues - Whether `kubectl` can process and submit the manifest shape in client mode - **Note:** `--validate=false` disables schema/type/required-field validation and still does NOT catch admission controller or policy issues. **Document in your report which mode was used:** - If server-side: "Full cluster validation performed" - If client-side with `--validate=false`: "Limited parse-only validation (no cluster access) - schema and admission policies not checked" - If skipped: "Dry-run skipped - kubectl not available" - If skipped after client fallback attempt: "Dry-run skipped (cluster discovery unavailable)" **For updates to existing resources:** ```bash kubectl diff -f "$TARGET_FILE" ``` This shows what would change, helping catch unintended modifications. ### Stage 6: Generate Detailed Validation Report (REPORT ONLY) After completing all validation stages, generate a comprehensive report. **This is a REPORT-ONLY stage.** **NEVER do any of the following:** - Do NOT use the Edit tool to modify files - Do NOT use AskUserQuestion to offer to fix issues - Do NOT prompt the user asking if they want fixes applied - Do NOT modify any YAML files **ALWAYS do the following:** - Generate a comprehensive validation report - Show before/after code blocks as SUGGESTIONS only - Let the user decide what to do after reviewing the report - End with "Next Steps" for the user to take manually 1. **Summarize all issues found** across all stages in a table format: ``` | Severity | Stage | Location | Issue | Suggested Fix | |----------|-------|----------|-------|---------------| | Error | Syntax | file.yaml:5 | Indentation error | Use 2 spaces | | Error | Schema | file.yaml:21 | Wrong type | Change to integer | | Warning | Best Practice | file.yaml:30 | Missing labels | Add app label | ``` 2. **Categorize by severity:** - **Errors** (must fix): Syntax errors, missing required fields, dry-run failures - **Warnings** (should fix): Style issues, best practice violations - **Info** (optional): Suggestions for improvement 3. **Show before/after code blocks for each issue:** For every issue, display explicit before/after YAML snippets showing the suggested fix: ``` **Issue 1: deployment.yaml:21 - Wrong field type (Error)** Current: ```yaml - containerPort: "80" ``` Suggested Fix: ```yaml - containerPort: 80 ``` **Why:** containerPort must be an integer, not a string. Kubernetes will reject string values. Reference: See k8s_best_practices.md "Invalid Values" section. ``` 4. **Provide validation summary:** ``` ## Validation Report Summary File: deployment.yaml Resources Analyzed: 3 (Deployment, Service, Certificate) | Stage | Status | Issues Found | |-------|--------|--------------| | YAML Syntax | ❌ Failed | 2 errors | | CRD Detection | ✅ Passed | 1 CRD detected (Certificate) | | Schema Validation | ❌ Failed | 1 error | | Dry-Run | ❌ Failed | 1 error | Total Issues: 4 errors, 2 warnings ## Detailed Findings [List each issue with before/after code blocks as shown above] ## Next Steps 1. Fix the 4 errors listed above (deployment will fail without these) 2. Consider addressing the 2 warnings for best practices 3. Re-run validation after fixes to confirm resolution ``` 5. **Do NOT modify files** - this is a reporting tool only - Present all findings clearly - Let the user decide which fixes to apply - User can request fixes after reviewing the report ## Objective Stage Gates (Repeatable) Use this table to keep stage decisions deterministic: | Stage --- Source: [Claudary](https://claudary.paisolsolutions.com/skills/skill-101) · https://claudary.paisolsolutions.com