Conciseness

The body is lean with no explanations of concepts Claude already knows, but there is minor duplication: the skip-to-step resume behavior is stated both in the intro ("unless the user provides `skip-to-step N`") and again in Rule 5, and "MCP tools | None" in the Quick Reference table is repeated by a dedicated "MCP Tools" section. Efficient with minor trimmable instances, matching the level 4 anchor rather than the every-token-earns-its-place level 5.

Actionability

The error-handling table gives copy-paste-ready commands ("kubectl logs -n airunway-system -l control-plane=controller-manager --previous", "--dtype float16") and the rules are concrete (✓/✗ status reporting, confirmation before installs), but the main executable detail is delegated to step references and some guidance is loose ("Run `az aks get-credentials` or equivalent"). Mostly executable guidance with minor gaps — level 4, not the fully copy-paste-ready level 5.

Workflow Clarity

Six steps are clearly sequenced with a per-step reference, Rule 2 mandates reporting cluster state (✓ healthy / ✗ missing) at each step as an explicit validation checkpoint, Rule 3 gates installs/deployments on user confirmation (with a cost warning for GPU provisioning), and the error-handling table plus skip/resume logic provide feedback and recovery paths. This matches the top anchor: clear sequence, explicit validation, and error-recovery loops.

Progressive Disclosure

The body is a clear overview with well-signaled, existing step references and a properly gated optional add-on (optional-gpu-day2.md), but the supporting references (gpu-profiles.md, model-sizing.md, powershell-notes.md) are only reachable via a second hop through the step files rather than signaled directly from SKILL.md, and step files cross-reference each other's material. Good structure with minor organization gaps — level 4 rather than the ideal one-level-deep level 5.

Specificity

"Set up AI Runway on AKS — from bare cluster to running model. Covers cluster verification, controller install, GPU assessment, provider setup, and first deployment" lists five concrete actions that comprehensively cover the end-to-end workflow, matching the top anchor. It exceeds level 4 because there are no meaningful gaps in coverage of the setup lifecycle.

Completeness

It explicitly answers both what ("from bare cluster to running model", with enumerated phases) and when (an explicit "WHEN:" clause with concrete trigger phrases), which is the exact pattern of the top anchor. A missing or weak when-clause would cap it at 3; here both are explicit.

Trigger Term Quality

The WHEN clause lists eleven natural phrases users would actually say — "setup AI Runway", "airunway setup", "deploy model to AKS", "KAITO setup on AKS", "vLLM on AKS", "run LLM on AKS" — including synonyms (setup/set up, AI Runway/airunway) and specific tool names. Coverage is comprehensive rather than merely good (level 4).

Distinctiveness Conflict Risk

The AI Runway niche is clear and most triggers are distinct, but broad phrases like "GPU inference on AKS", "run LLM on AKS", and "vLLM on AKS" could also match the closely related aks-gpu-inference skill the body itself references — minor overlap risk with a closely related skill, fitting the level 4 anchor rather than the minimal-conflict level 5.