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chaos

Design, run, and debug Chaos Engineering experiments on Kubernetes using Litmus Chaos v3 and Chaos Mesh v2. Covers fault injection (pod-delete, network-loss, CPU stress, node-drain), steady-state hypothesis probes, GameDay runbooks, scheduled experiments, DORA feedback loop, and RBAC setup. Use when asked to "inject a pod fault", "run a GameDay", "schedule chaos experiments", or "debug why my ChaosEngine is stuck".

Quality

85%

Does it follow best practices?

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SecuritybySnyk

Passed

No findings from the security scan

The canonical home for this skill is chaos in nitinjain999/platform-skills

SKILL.md
Quality
Evals
Security

Quality

Content

78%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 lean, highly actionable command skill with well-sequenced per-mode workflows, validation checkpoints, and good safety scoping for destructive faults. Its main defect is that every referenced bundle file (references/chaos.md and the examples/chaos/*.yaml files, including two values files required by the install commands) is missing from the bundle, which breaks both the install commands and the deferred experiment guidance.

Suggestions

Ship the referenced bundle files or remove the pointers: the helm install commands require examples/chaos/litmus-install-values.yaml and chaos-mesh-install-values.yaml to exist, and the debug mode depends on references/chaos.md.

Inline one complete experiment YAML (e.g., a pod-delete ChaosEngine with an HTTP probe) in the experiment mode so it is actionable even without the absent examples/chaos/pod-delete-experiment.yaml.

Add an RBAC verification step to install mode, since 'Stuck Initialized / Missing RBAC' is listed as the most common debug failure.

DimensionReasoningScore

Conciseness

The body is dense with commands, YAML, wizard prompts, and a symptom/cause/fix table; it assumes Claude's competence and spends no tokens explaining what chaos engineering or Kubernetes is. Every section carries actionable weight, matching the 5 anchor ('lean and efficient; every token earns its place') rather than the 4 anchor's 'minor instances of over-explanation'.

5 / 5

Actionability

Mostly executable: copy-paste helm installs with pinned versions, complete ChaosSchedule/Schedule YAML, concrete kubectl diagnostics, and a debug decision table. However, the install commands pass '-f examples/chaos/litmus-install-values.yaml' (and chaos-mesh-install-values.yaml) which do not exist in the bundle, so those commands fail as written, and the experiment mode defers entirely to missing example YAMLs instead of showing one complete experiment. Mostly executable with real gaps fits 4, not 5's copy-paste-ready coverage.

4 / 5

Workflow Clarity

Each mode is a numbered sequence with an interactive wizard entry, explicit checkpoints (verify pods Running after install; require steady-state hypothesis before injecting; observe/verdict criteria in gameday), and safety constraints for the destructive operations (staging-only scheduling, 50% blast radius), so the destructive-operation cap does not apply. Minor gaps keep it at 4 rather than 5: install mode lacks an RBAC pre-flight check even though missing RBAC is listed as the top debug cause, and the experiment mode's end-to-end flow depends on example files that are absent.

4 / 5

Progressive Disclosure

Mode-based sections are well organized and references are clearly signaled at the point of need ('load references/chaos.md', 'See examples/chaos/pod-delete-experiment.yaml'), but none of the referenced bundle files exist in the skill — no references/, scripts/, assets/, or examples/ directories are present, so every external pointer dangles and navigation is impossible. Structure is present but the references are broken, fitting the 3 anchor; it is not 4 because 'references mostly clear' fails when the targets are missing, and not 2 because the inline content is genuinely well sectioned.

3 / 5

Total

16

/

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: concrete, third-person capability enumeration paired with an explicit 'Use when' clause containing natural quoted trigger phrases. The only weaknesses are trigger coverage for the install/report modes and a minor distinctiveness overlap with a sibling DORA skill.

DimensionReasoningScore

Specificity

"Design, run, and debug Chaos Engineering experiments on Kubernetes using Litmus Chaos v3 and Chaos Mesh v2. Covers fault injection (pod-delete, network-loss, CPU stress, node-drain), steady-state hypothesis probes, GameDay runbooks, scheduled experiments, DORA feedback loop, and RBAC setup" lists multiple concrete actions with specific fault types and tool names in third-person voice. Coverage is comprehensive, so it matches the 5 anchor rather than the 4 anchor's 'minor gaps'.

5 / 5

Completeness

The description explicitly answers both questions: 'what' via the enumerated capabilities (fault injection, steady-state probes, GameDays, schedules, DORA loop, RBAC) and 'when' via the 'Use when asked to ...' clause with concrete trigger phrases. This matches the 5 anchor exactly; the 4 anchor's 'when could be more explicit' does not apply since the when-clause is fully explicit.

5 / 5

Trigger Term Quality

"Use when asked to 'inject a pod fault', 'run a GameDay', 'schedule chaos experiments', or 'debug why my ChaosEngine is stuck'" provides natural verbatim trigger phrases plus named tools, but triggers cover only 4 of the 6 modes — install and report scenarios (e.g., 'install Litmus', 'summarize my chaos experiment') and synonyms like 'resilience testing' are missing. Good coverage with a few natural terms missing fits 4, not 5's comprehensive synonym coverage.

4 / 5

Distinctiveness Conflict Risk

The chaos-engineering-on-Kubernetes niche with named tools (Litmus Chaos, Chaos Mesh) and distinctive triggers (pod fault, GameDay, ChaosEngine) is mostly distinct, but claiming 'DORA feedback loop' creates minor overlap with a sibling DORA-metrics skill — the body itself cross-references '/platform-skills:dora benchmark'. Minor overlap risk with a closely related skill matches the 4 anchor; 5's 'minimal conflict risk' is undercut by the DORA claim.

4 / 5

Total

18

/

20

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.

Validation — 14 / 16 Passed

Validation for skill structure

CriteriaDescriptionResult

frontmatter_unknown_keys

Unknown frontmatter key(s) found; consider removing or moving to metadata

Warning

referenced_paths_exist

Referenced path issues: 1 missing

Warning

Total

14

/

16

Passed

Repository

nitinjain999/platform-skills

Path

plugins/platform-skills/skills/chaos/SKILL.md

Reviewed

Table of Contents

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