ark-controller-development
Guidance for developing the Ark Kubernetes operator. Use when modifying Go types, CRDs, controllers, or webhooks. Helps with CRD generation and Helm chart sync issues.
84
83%
Does it follow best practices?
Impact
80%
2.96xAverage score across 3 eval scenarios
Passed
No known issues
Quality
Discovery
89%Based on the skill's description, can an agent find and select it at the right time? Clear, specific descriptions lead to better discovery.
This is a solid, well-structured skill description that clearly identifies its niche (Ark Kubernetes operator development) and provides explicit trigger conditions. The main weakness is that the capabilities could be more concrete—listing specific actions rather than general categories of work. Overall it performs well for skill selection purposes due to its strong trigger terms and clear 'Use when' clause.
Suggestions
Make capabilities more concrete by specifying exact actions, e.g., 'Generates CRD manifests from Go type definitions, syncs Helm chart values with CRD schema changes, scaffolds controller reconciliation loops.'
| Dimension | Reasoning | Score |
|---|---|---|
Specificity | Names the domain (Ark Kubernetes operator) and mentions some actions like modifying Go types, CRDs, controllers, webhooks, CRD generation, and Helm chart sync, but these are more categories of work than concrete specific actions (e.g., doesn't say 'generate CRD manifests from Go structs' or 'sync Helm values.yaml with CRD changes'). | 2 / 3 |
Completeness | Clearly answers both 'what' (guidance for developing the Ark Kubernetes operator, helps with CRD generation and Helm chart sync issues) and 'when' (explicit 'Use when modifying Go types, CRDs, controllers, or webhooks'). | 3 / 3 |
Trigger Term Quality | Includes strong natural keywords a developer would use: 'Go types', 'CRDs', 'controllers', 'webhooks', 'CRD generation', 'Helm chart sync', 'Kubernetes operator'. These are terms a user working on this project would naturally mention. | 3 / 3 |
Distinctiveness Conflict Risk | Highly specific to the 'Ark Kubernetes operator' project with distinct triggers like CRD generation and Helm chart sync. Very unlikely to conflict with generic Go, Kubernetes, or Helm skills due to the project-specific scoping. | 3 / 3 |
Total | 11 / 12 Passed |
Implementation
77%Reviews the quality of instructions and guidance provided to agents. Good implementation is clear, handles edge cases, and produces reliable results.
This is a solid, actionable skill with clear workflows and concrete commands for Ark operator development. Its main weakness is verbosity in the 'Leverage Existing Code' and 'Avoid Magic Numbers' sections, which explain general software engineering principles Claude already knows, padded with philosophical justification. The completion checklist and CRD generation flow are excellent and highly practical.
Suggestions
Trim the 'Leverage Existing Code' section to just the heuristic and the worked example's 'Good' pattern — remove the paragraph explaining why hand-rolled code is bad, as Claude already knows this.
Condense the 'Avoid Magic Numbers' section to just the priority list and the 'Good' code example — the rationale is self-evident to Claude.
| Dimension | Reasoning | Score |
|---|---|---|
Conciseness | The skill is mostly efficient but has some areas of verbosity — the 'Leverage Existing Code' section with its worked example and philosophical rationale is lengthy for something Claude already understands. The 'Avoid Magic Numbers' section similarly over-explains a well-known principle. However, the CRD generation flow, key directories table, and common tasks sections are lean and well-structured. | 2 / 3 |
Actionability | The skill provides concrete, executable commands throughout (make manifests, make build, make lint, chainsaw test commands), specific directory paths, worked code examples showing good vs bad patterns, and clear table-driven guidance for testing frameworks. Nearly everything is copy-paste ready. | 3 / 3 |
Workflow Clarity | Multi-step processes are clearly sequenced with explicit validation checkpoints. The CRD generation flow diagram is clear, the 'After Any Go Code Change' section has an ordered sequence with mandatory lint step, and the completion checklist provides a comprehensive verification loop. The 'Before Opening a PR' section includes clear guidance on when to run which test suite. | 3 / 3 |
Progressive Disclosure | The skill references the 'chainsaw skill' for additional patterns, which is good progressive disclosure. However, the worked examples for 'Leverage Existing Code' and 'Avoid Magic Numbers' are quite detailed and could be split into a separate reference file. The testing section is also fairly detailed inline. The overall structure is reasonable but the document is on the longer side for a SKILL.md overview. | 2 / 3 |
Total | 10 / 12 Passed |
Validation
100%Checks the skill against the spec for correct structure and formatting. All validation checks must pass before discovery and implementation can be scored.
Validation — 11 / 11 Passed
Validation for skill structure
No warnings or errors.
- Repository
- mckinsey/agents-at-scale-ark
- Commit
fc5746e
- Reviewed
Table of Contents
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