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eks-observability

EKS observability with metrics, logging, and tracing. Use when setting up monitoring, configuring logging pipelines, implementing distributed tracing, building production dashboards, troubleshooting EKS issues, optimizing observability costs, or establishing SLOs.

63

Quality

75%

Does it follow best practices?

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Adds up to 20 points to the overall score

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SecuritybySnyk

Low

Low-risk findings worth noting

Fix and improve this skill with Tessl

tessl review fix ./.claude/skills/eks-observability/SKILL.md

The canonical home for this skill is eks-observability in fernandezbaptiste/Skrillz

SKILL.md
Quality
Evals
Security

Quality

Content

61%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 thorough, actionable EKS observability guide with executable commands and clean reference structure. Its main weaknesses are verbosity from decorative and recap sections, and missing per-step validation checkpoints for batch provisioning operations.

Suggestions

Remove or move the ASCII architecture diagram, the repeated 'What You Get' bullet lists, and the 10-point Best Practices Summary into the reference files to tighten the SKILL.md token budget.

Add an explicit post-deploy validation checkpoint (e.g., verify pods/remote-write/ingestion) after each of Steps 2–5, and frame the production checklist as a validate-fix-retry loop rather than a static list.

Replace the console-recommended Grafana workspace step with a copy-paste CLI sequence, or at minimum move the manual console steps into references/metrics.md to keep the quick start fully executable.

DimensionReasoningScore

Conciseness

Mostly efficient with direct commands and configs, but several padded sections (the decorative ASCII architecture diagram, repeated 'What You Get' lists, a 10-point best-practices recap, and filler cost estimates) could be trimmed.

3 / 5

Actionability

Mostly executable guidance with real aws/eksctl/helm commands and a complete ADOT Collector YAML manifest, though console-recommended Grafana setup and ACCOUNT_ID/role-name placeholders leave minor gaps.

4 / 5

Workflow Clarity

A clear 5-step Quick Start sequence exists, but post-deploy validation checkpoints are present only for step 1; the batch/destructive provisioning operations (IAM roles, addons, workspaces) lack per-step validate-fix-retry loops, capping this dimension at 3.

3 / 5

Progressive Disclosure

Clear section structure with well-signaled one-level-deep references to three real files (metrics.md, logging.md, tracing.md), though the SKILL.md itself remains heavy with inlined detail that could live in those references.

4 / 5

Total

14

/

20

Passed

Description

88%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 clearly states the skill's purpose and provides explicit, concrete trigger guidance. It is specific and well-scoped, with only minor gaps in trigger-term synonym coverage.

DimensionReasoningScore

Specificity

Names the three-pillar domain and lists multiple concrete actions across setup, troubleshooting, cost optimization, and SLOs — comprehensive coverage of the skill's capabilities.

5 / 5

Completeness

Explicitly answers both what ('EKS observability with metrics, logging, and tracing') and when (a concrete 'Use when...' clause listing six trigger scenarios).

5 / 5

Trigger Term Quality

Good natural keyword coverage (monitoring, logging pipelines, distributed tracing, dashboards, troubleshooting, SLOs), but a few common synonyms and tool-specific terms a user might say (alerts, X-Ray, Prometheus) are absent.

4 / 5

Distinctiveness Conflict Risk

Scoped to EKS observability with EKS-specific triggers, giving a clear niche with only minor overlap risk against generic monitoring skills.

4 / 5

Total

18

/

20

Passed

Validation

93%

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

Validation15 / 16 Passed

Validation for skill structure

CriteriaDescriptionResult

skill_md_line_count

SKILL.md is long (547 lines); consider splitting into references/ and linking

Warning

Total

15

/

16

Passed

Repository
fernandezbaptiste/Skrillz
Reviewed

Table of Contents

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