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testland/chaos-mesh

Configures Chaos Mesh for Kubernetes-native chaos engineering - picks fault types (PodChaos, NetworkChaos, StressChaos, IOChaos, TimeChaos, DNSChaos, KernelChaos, HTTPChaos), targets via label selectors, controls blast radius via namespace whitelists + selector filters, schedules via CronJobs, observes via dashboard. Distinct from Litmus by architecture (Chaos Mesh has its own dashboard + workflow orchestration; Litmus uses ChaosCenter UI). Use when the target system runs on Kubernetes and fault experiments should be declared as CRDs in the cluster alongside the workloads they target.

75

Quality

94%

Does it follow best practices?

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SecuritybySnyk

Medium

Suggest reviewing before use

Overview
Quality
Evals
Security
Files

Quality

Content

85%

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 complete, sequenced, copy-paste-ready Chaos Mesh guidance and explicit verdict/validation steps. The main weakness is conciseness: a marketing blockquote and repeated source-attribution prefixes consume tokens that add no instructional value.

Suggestions

Drop or condense the opening marketing blockquote ('brings various types of fault simulation... enormous capability') — it restates what Chaos Mesh is without guiding action.

Reduce the repeated 'Per [chaos-mesh-home][cm]' attribution prefixes; cite the source once near the top instead of prefixing ~8 sections.

Expand the Workflow example's `selector: { ... }` placeholders to minimal real selectors (or note they reuse the Step 3 selector) so the example is fully copy-paste runnable.

DimensionReasoningScore

Conciseness

Mostly efficient actionable content (tables, YAML, anti-patterns), but padded with a marketing blockquote ('brings various types of fault simulation... enormous capability') and ~8 repeated 'Per [chaos-mesh-home][cm]' attribution prefixes that add tokens without instruction value; not 3 because these could be trimmed, not 1 because the bulk is lean and non-redundant.

2 / 3

Actionability

Provides fully executable, copy-paste-ready guidance — install commands, complete NetworkChaos/PodChaos/PhysicalMachineChaos YAML, kubectl watch/describe, and a CI snippet; not 2 because the core examples are complete rather than pseudocode (the Workflow's `selector: { ... }` placeholders re-use syntax already shown in full in Steps 3-4).

3 / 3

Workflow Clarity

Nine clearly sequenced steps (Install → Fault types → Author → Workflow → Dashboard → Run+verdict → Physical machine → CI) with explicit validation in Step 7 (watch state, 'verify the steady-state hypothesis held') and Step 9 (datadog-verdict.sh); not 2 because validation checkpoints are present and explicit, satisfying the destructive-operation requirement.

3 / 3

Progressive Disclosure

Single self-contained file with well-organized sections and a clearly signaled References list pointing to sibling skills (litmus-chaos, gremlin-chaos, chaos-experiment-author) and the upstream site; no bundle files exist and references are one level deep with no nesting; not 2 because navigation is easy and content is appropriately sectioned.

3 / 3

Total

11

/

12

Passed

Description

100%

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: third-person voice, concrete multi-action capability list, natural trigger terms, an explicit 'Use when' clause, and clear differentiation from the sibling Litmus skill. All four dimensions land at the top of the scale.

DimensionReasoningScore

Specificity

Lists multiple concrete actions — 'picks fault types (PodChaos, NetworkChaos, StressChaos, IOChaos, TimeChaos, DNSChaos, KernelChaos, HTTPChaos), targets via label selectors, controls blast radius via namespace whitelists + selector filters, schedules via CronJobs, observes via dashboard' — matching the anchor for naming multiple specific concrete actions; not 2 because the action set is comprehensive rather than partial.

3 / 3

Completeness

Explicitly answers both what (configures fault types, targeting, scheduling, observation) and when — 'Use when the target system runs on Kubernetes and fault experiments should be declared as CRDs in the cluster alongside the workloads they target'; not 2 because the 'Use when' clause is explicit rather than implied.

3 / 3

Trigger Term Quality

Covers natural terms a user would say — 'Chaos Mesh', 'Kubernetes', 'chaos engineering', 'CRDs', 'label selectors', 'blast radius', 'CronJobs', 'dashboard' — giving good coverage; not 2 because common variations are present rather than missing.

3 / 3

Distinctiveness Conflict Risk

Delineates a clear niche and explicitly contrasts the sibling skill — 'Distinct from Litmus by architecture (Chaos Mesh has its own dashboard + workflow orchestration; Litmus uses ChaosCenter UI)'; not 2 because the distinguishing triggers make overlap with other skills unlikely.

3 / 3

Total

12

/

12

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.

Validation16 / 16 Passed

Validation for skill structure

No warnings or errors.

Reviewed

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