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boto3-eks

AWS Boto3 SDK patterns for Amazon EKS cluster management, node groups, authentication tokens, and Kubernetes client integration. Use when working with EKS clusters, managing node groups, generating kubeconfig, creating authentication tokens, integrating Kubernetes Python client, managing Fargate profiles, or implementing IRSA authentication.

Quality

82%

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SKILL.md
Quality
Evals
Security

Quality

Content

72%Weight 40%Scale 1-5

Reviews the quality of instructions and guidance provided to agents. Good implementation is clear, handles edge cases, and produces reliable results.

A well-structured reference skill with mostly executable, copy-paste-ready code and exemplary progressive disclosure to three real reference files. The main weaknesses are an implicit rather than explicit core workflow — mutations like update_nodegroup_config lack verification steps — and minor trimming opportunities (duplicated waiter example, redundant When-to-Use section, irrelevant Related Skills entries).

Suggestions

Add a follow-up verification step after 'update_nodegroup_config' (e.g. wait on the 'nodegroup_active' waiter before considering the scaling change applied), and integrate waiters into the operation snippets as explicit checkpoints instead of a standalone section.

Make the Kubernetes-client usage block self-contained: define 'cluster' via 'eks.describe_cluster(...)' in the snippet and show how to write the cluster's certificate-authority-data to the CA cert path instead of assuming '/tmp/ca.crt'.

Remove the duplicated 'cluster_active' waiter example, the 'When to Use This Skill' section (it restates the frontmatter description), and the unrelated 'Related Skills' entries to tighten token efficiency.

DimensionReasoningScore

Conciseness

The body is code-dense with almost no explanation of concepts Claude already knows, and the non-obvious token-generation code earns its place. However, the 'cluster_active' waiter is demonstrated twice ('Essential Cluster Operations' and 'Async Operations with Waiters'), 'When to Use This Skill' duplicates the frontmatter description, and the 'Related Skills' section (anthropic-expert, claude-cost-optimization, railway-deployment) is irrelevant padding that could be trimmed — matching 'efficient; minor instances of over-explanation that could be trimmed' rather than the lean 5 anchor.

4 / 5

Actionability

Most guidance is copy-paste ready: 'get_eks_client', 'get_eks_token', and 'generate_kubeconfig' are complete executable functions, and the snippet sections (describe, list, nodegroup scaling, error handling with real exception classes) are concrete. It falls short of 'fully executable' because the flagship Kubernetes-client usage block references an undefined 'cluster' variable ('configuration.host = cluster['cluster']['endpoint']') and an unexplained "ssl_ca_cert = '/tmp/ca.crt'" path that no code populates — minor gaps in the primary use case.

4 / 5

Workflow Clarity

The core sequence (init client → describe cluster → generate token → configure Kubernetes client) is only implicit in section ordering, and waiters appear as standalone patterns rather than integrated checkpoints. Critically, 'update_nodegroup_config' is a batch mutation shown with no follow-up verification (no nodegroup_active waiter after the update), which caps workflow clarity at 3 per the batch/destructive-operations guideline: 'Steps listed but validation gaps; sequence present but checkpoints missing or implicit'.

3 / 5

Progressive Disclosure

The body keeps quick-reference content inline and delegates depth to three real, one-level-deep reference files (verified present: references/cluster-operations.md, references/auth-tokens.md, references/nodegroups-fargate.md). A dedicated 'Progressive Disclosure' section explicitly splits quick-start topics from each reference with content summaries ('Complete cluster lifecycle management, version updates...'), matching the top anchor of a clear overview with well-signaled one-level-deep references and easy navigation.

5 / 5

Total

16

/

20

Passed

Description

83%Weight 40%Scale 1-5

Based on the skill's description, can an agent find and select it at the right time? Clear, specific descriptions lead to better discovery.

A strong description that explicitly states both what the skill covers and when to use it, with domain-specific trigger terms (EKS, kubeconfig, Fargate, IRSA) that users would naturally say. The only refinement opportunity is converting capability nouns into slightly more concrete verb-based actions.

DimensionReasoningScore

Specificity

The description names the domain ('AWS Boto3 SDK patterns for Amazon EKS cluster management, node groups, authentication tokens, and Kubernetes client integration') and lists several specific capability areas including kubeconfig generation, Fargate profiles, and IRSA. It falls short of the top anchor because capabilities are framed as noun phrases ('patterns for... management') rather than concrete verb-driven actions like the 5-anchor's 'Extract text and tables from PDF files, fill forms, merge documents'.

4 / 5

Completeness

It explicitly answers both questions: the 'what' ('AWS Boto3 SDK patterns for Amazon EKS cluster management, node groups, authentication tokens, and Kubernetes client integration') and an explicit 'when' with multiple concrete trigger conditions ('Use when working with EKS clusters, managing node groups, generating kubeconfig...'). This directly matches the top anchor's structure of a concrete what followed by explicit trigger phrases.

5 / 5

Trigger Term Quality

The 'Use when' clause covers natural user phrases: 'working with EKS clusters, managing node groups, generating kubeconfig, creating authentication tokens, integrating Kubernetes Python client, managing Fargate profiles, or implementing IRSA authentication'. A few natural terms and synonyms are missing (e.g. 'Kubernetes'/'k8s' generally, cluster scaling, OIDC), so it matches the 'good keyword coverage; a few natural terms missing' anchor rather than the comprehensive 5 anchor.

4 / 5

Distinctiveness Conflict Risk

The niche is clear and well-bounded: Boto3 SDK + Amazon EKS with distinct triggers (EKS, kubeconfig, Fargate profiles, IRSA) that would not fire for unrelated skills. The peripheral mentions of 'Kubernetes client integration' and 'authentication tokens' create only minimal overlap with a hypothetical general Kubernetes skill, and those phrases are explicitly framed within the EKS context, fitting the 'clear niche with distinct triggers; minimal conflict risk' anchor.

5 / 5

Total

18

/

20

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 — 16 / 16 Passed

Validation for skill structure

No warnings or errors.

Repository

fernandezbaptiste/Skrillz

Path

skills/boto3-eks/SKILL.md

Reviewed

Table of Contents

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