deploy-gcp-gke
Guide for deploying the Anyscale GCP GKE new cluster example from examples/gcp/gke-new_cluster/. Use when the user asks about deploying, setting up, or configuring GKE for Anyscale.
64
77%
Does it follow best practices?
Impact
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No eval scenarios have been run
Advisory
Suggest reviewing before use
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npx tessl skill review --optimize ./.claude/skills/deploy-gcp-gke/SKILL.mdQuality
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.
The description is well-structured with explicit 'what' and 'when' clauses and good trigger terms for its specific niche. Its main weakness is a lack of concrete action details—it says 'guide for deploying' but doesn't enumerate specific steps or capabilities like Terraform configuration, cluster provisioning, or network setup. Overall it is a solid, functional description for a narrowly scoped skill.
Suggestions
Add specific concrete actions the skill covers, e.g., 'Configures Terraform modules, provisions GKE clusters, sets up networking and IAM for Anyscale on GCP' to improve specificity.
| Dimension | Reasoning | Score |
|---|---|---|
Specificity | Names the domain (Anyscale GCP GKE new cluster deployment) and references a specific example path, but does not list concrete actions beyond 'deploying, setting up, or configuring'. It lacks detail on what specific steps or operations the skill performs. | 2 / 3 |
Completeness | Clearly answers both 'what' (guide for deploying the Anyscale GCP GKE new cluster example from a specific path) and 'when' (explicit 'Use when the user asks about deploying, setting up, or configuring GKE for Anyscale'). | 3 / 3 |
Trigger Term Quality | Includes natural keywords users would say: 'deploying', 'setting up', 'configuring', 'GKE', 'Anyscale', 'GCP'. These are terms a user would naturally use when seeking help with this specific task. | 3 / 3 |
Distinctiveness Conflict Risk | Highly specific niche targeting Anyscale on GCP GKE with a specific example path. Very unlikely to conflict with other skills unless there are multiple Anyscale GKE deployment skills. | 3 / 3 |
Total | 11 / 12 Passed |
Implementation
64%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 deployment guide with excellent actionability — every step has concrete, executable commands with specific versions and parameters. The main weaknesses are the lack of explicit validation checkpoints between steps (critical for infrastructure deployments where failures cascade) and some minor verbosity in prerequisites and explanations. The workflow is well-sequenced but would benefit from verification gates.
Suggestions
Add explicit validation checkpoints between steps, e.g., after Step 2 verify terraform outputs exist, after Step 3 run 'kubectl get nodes' to confirm cluster access, after Step 4 verify ingress controller pod is running before proceeding to registration.
Trim prerequisites to just tool names and version requirements — Claude doesn't need links explaining what kubectl or helm are.
Add a brief error recovery note for the cloud registration step (Step 5), since getting the deployment ID wrong would cause Step 6 to fail silently.
| Dimension | Reasoning | Score |
|---|---|---|
Conciseness | Generally efficient but includes some unnecessary context like linking to what Google Cloud Project/SDK/kubectl/helm are (Claude knows these), and some explanatory text that could be trimmed. The variable descriptions are useful but slightly verbose. | 2 / 3 |
Actionability | Provides fully executable shell commands, specific helm chart versions, concrete terraform variable examples, and copy-paste ready commands for every step. The conditional logic (public vs private nginx, filestore flags) is clearly specified. | 3 / 3 |
Workflow Clarity | Steps are clearly sequenced and logically ordered, with good notes about dependencies between steps (e.g., terraform outputs needed for later steps, cloud deployment ID from registration). However, there are no explicit validation checkpoints or feedback loops — no 'verify the cluster is ready before proceeding' or 'if registration fails, check X' between steps, which is important for this multi-step infrastructure deployment. | 2 / 3 |
Progressive Disclosure | References to external files like `variables.tf`, `gpu_instances.tfvars.example`, and sample values YAML files are present and helpful. However, the skill is fairly long (~130 lines of substantive content) and could benefit from splitting detailed GPU configuration or troubleshooting into separate referenced files. The structure is reasonable but not optimally layered. | 2 / 3 |
Total | 9 / 12 Passed |
Validation
81%Checks the skill against the spec for correct structure and formatting. All validation checks must pass before discovery and implementation can be scored.
Validation — 9 / 11 Passed
Validation for skill structure
| Criteria | Description | Result |
|---|---|---|
allowed_tools_field | 'allowed-tools' contains unusual tool name(s) | Warning |
frontmatter_unknown_keys | Unknown frontmatter key(s) found; consider removing or moving to metadata | Warning |
Total | 9 / 11 Passed | |
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