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kubernetes-patterns

Kubernetes workload patterns, resource management, RBAC, probes, autoscaling, ConfigMap/Secret handling, and kubectl debugging for production-grade deployments.

58

Quality

68%

Does it follow best practices?

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Adds up to 20 points to the overall score

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SecuritybySnyk

High

Do not use without reviewing

Fix and improve this skill with Tessl

tessl review fix ./skills/kubernetes-patterns/SKILL.md
SKILL.md
Quality
Evals
Security

Quality

Content

65%

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

A highly actionable, well-organized Kubernetes pattern catalog with excellent copy-paste-ready YAML and kubectl examples, weakened mainly by a monolithic single-file structure and scattered rather than explicit validation workflows.

Suggestions

Move the kubectl cheatsheet and/or anti-patterns catalog into separate reference files (e.g., references/kubectl-cheatsheet.md) and link from SKILL.md to improve progressive disclosure.

Consolidate the duplicate 'When to Activate' and 'When to Use' sections into one to remove redundant tokens.

Add an explicit validate→fix→retry loop for `kubectl apply` workflows (e.g., `--dry-run=server`, then apply, then `rollout status`) to raise workflow clarity.

DimensionReasoningScore

Conciseness

Mostly lean and pattern-dense, but the duplicated 'When to Activate'/'When to Use' sections and the 'How It Works' enumeration (which restates the later table of contents) add tokens that could be tightened, matching the 'mostly efficient but could be tightened' anchor.

2 / 3

Actionability

Fully executable, copy-paste-ready YAML manifests and kubectl commands with inline comments throughout, matching the 'fully executable code/commands; copy-paste ready' anchor.

3 / 3

Workflow Clarity

Debugging sequences and dry-run validation are present, but validation checkpoints are scattered rather than sequenced as explicit validate→fix→retry loops for destructive/apply operations, which the feedback-loops note caps at 2.

2 / 3

Progressive Disclosure

Well-organized with section headers and a navigation jump-table, but it is a ~750-line monolithic SKILL.md with no reference/scripts bundle files to offload detail, fitting the 'content that should be separate is inline' anchor.

2 / 3

Total

9

/

12

Passed

Description

72%

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 specific and trigger-rich with a clear Kubernetes niche, but it omits an explicit 'when to use' clause, capping completeness and overall strength.

Suggestions

Add an explicit trigger clause such as 'Use when writing, reviewing, or debugging Kubernetes YAML manifests and workloads' to raise completeness from 2 to 3.

Reframe topic nouns as concrete actions (e.g., 'Generate production Deployments, configure probes, enforce least-privilege RBAC') to strengthen specificity.

DimensionReasoningScore

Specificity

Names a broad domain and many specific topics ('RBAC, probes, autoscaling, ConfigMap/Secret handling, ... kubectl debugging') but frames them as noun phrases rather than concrete verbs, matching the 'names domain and some actions' anchor rather than the action-list anchor at 3.

2 / 3

Completeness

Clearly answers 'what' but lacks any 'Use when...' clause or explicit trigger guidance, so per the judging guidelines completeness is capped at 2.

2 / 3

Trigger Term Quality

Strong coverage of natural terms users say — 'Kubernetes', 'RBAC', 'probes', 'autoscaling', 'ConfigMap', 'Secret', 'kubectl', 'debugging', 'deployments' — closely matching the good-coverage anchor.

3 / 3

Distinctiveness Conflict Risk

Kubernetes-specific niche with distinct triggers ('Kubernetes workload patterns', 'kubectl debugging') that are unlikely to conflict with other skills.

3 / 3

Total

10

/

12

Passed

Validation

87%

Checks the skill against the spec for correct structure and formatting. All validation checks must pass before discovery and implementation can be scored.

Validation14 / 16 Passed

Validation for skill structure

CriteriaDescriptionResult

skill_md_line_count

SKILL.md is long (757 lines); consider splitting into references/ and linking

Warning

metadata_version

'metadata.version' is missing

Warning

Total

14

/

16

Passed

Repository
affaan-m/ECC
Reviewed

Table of Contents

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