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k8s-debug

Inspect pod logs, analyze resource quotas, trace network policies, check deployment rollout status, run cluster health checks for Kubernetes. Use this skill when diagnosing Kubernetes cluster issues, debugging failing pods, investigating network connectivity problems, analyzing resource usage, troubleshooting deployments, performing cluster health checks.

Quality

89%

Does it follow best practices?

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SecuritybySnyk

Low

Low-risk findings worth noting

SKILL.md
Quality
Evals
Security

Quality

Content

81%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.

The body is highly actionable, with executable commands, guarded destructive operations, and explicit validation checkpoints, and its reference files are real and well-signaled. Its main weakness is redundancy: two overlapping anti-pattern sections and some repeated commands inflate token cost without adding guidance.

Suggestions

Merge the '## Common Anti-Patterns' and '## Anti-Patterns' sections into one, dropping the duplicated exec-into-production and delete-without-diagnosis entries to save roughly 40 lines of redundant tokens.

Consolidate the repeated 'kubectl top pods -n <namespace> --containers' command (appears in both 'Performance Degradation' and 'Resource Monitoring') into a single Resource Monitoring block.

Move the detailed anti-pattern catalog and 'Advanced Debugging Techniques' (port-forwarding, proxy, custom columns) into a reference file, keeping only the highest-frequency patterns in SKILL.md to shorten the ~380-line body.

DimensionReasoningScore

Conciseness

The body is mostly lean, command-driven content, but two overlapping anti-pattern sections ('## Common Anti-Patterns' and '## Anti-Patterns') duplicate whole topics (exec into production pods, force-delete first resort), and commands like 'kubectl top pods -n <namespace> --containers' appear in two sections. It could be meaningfully tightened.

3 / 5

Actionability

Fully executable, copy-paste-ready kubectl commands throughout, with non-obvious flags annotated ('--previous', '--field-selector=status.phase!=Running', '--sort-by=.lastTimestamp') and real script invocations ('python3 scripts/pod_diagnostics.py <pod-name> -n <namespace>') that exist in the bundle.

5 / 5

Workflow Clarity

A clear layered decision framework (context -> verify -> hypothesize -> document) sequences the work, and every destructive operation carries explicit verify-before/verify-after steps ('Verify current rollout state first', 'Watch for 60s before proceeding'), plus a dedicated 4-step Verification and Validation checklist with side-effect and functional checks.

5 / 5

Progressive Disclosure

Good structure with clearly signaled one-level-deep references ('See [references/troubleshooting_workflow.md]... for: Step-by-step workflows...') and bundled scripts that all exist, but the ~380-line body retains duplicated sections that would fit better consolidated or moved to the reference files.

4 / 5

Total

17

/

20

Passed

Description

92%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.

The description is strong: it names the domain, lists five concrete capabilities in third person, and provides an explicit 'Use this skill when' clause with multiple natural trigger phrases. The only gap is a few missing synonyms ('k8s', 'kubectl', 'CrashLoopBackOff') that would make triggering even more reliable.

DimensionReasoningScore

Specificity

Lists five concrete, comprehensive actions ('Inspect pod logs, analyze resource quotas, trace network policies, check deployment rollout status, run cluster health checks') in third-person voice, fully covering the skill's diagnostic scope.

5 / 5

Completeness

Explicitly answers both 'what' (five concrete actions) and 'when' ('Use this skill when diagnosing Kubernetes cluster issues, debugging failing pods, ...') with concrete trigger phrases, matching the top anchor.

5 / 5

Trigger Term Quality

Good natural-term coverage ('debugging failing pods', 'troubleshooting deployments', 'investigating network connectivity problems', 'Kubernetes'), but common synonyms and markers users say like 'k8s', 'kubectl', or specific states like 'CrashLoopBackOff' are missing.

4 / 5

Distinctiveness Conflict Risk

Clearly scoped to a Kubernetes-debugging niche with distinct trigger phrases (pod failures, rollout status, network policies); minimal overlap risk with other skills.

5 / 5

Total

19

/

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

pantheon-org/tekhne

Path

skills/infrastructure/k8s/debug/SKILL.md

Reviewed

Table of Contents

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