Name: chaos-engineering
Rating: 72 (1 reviews)
Author: alirezarezvani

chaos-engineering

Use when planning, running, or learning from chaos engineering experiments. Triggers on "chaos experiment", "fault injection", "gameday", "resilience test", "blast radius", "steady state", "abort criteria", "Chaos Toolkit", "Chaos Mesh", "Litmus", "Gremlin", "AWS FIS", or any deliberate failure-injection question. Ships experiment designer, blast-radius calculator, and postmortem generator (all stdlib Python), 4 references on chaos principles + experiment design + attack taxonomy + tooling landscape, and a /chaos-experiment slash command. Composes with feature-flags-architect (kill switches as abort triggers) and kubernetes-operator (common chaos targets).

Quality

89%

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The canonical home for this skill is chaos-engineering in alirezarezvani/claude-skills

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 strong, actionable body with copy-paste-ready commands, clear attack/tooling tables, and sequenced workflows that include abort validation. Its main weakness is progressive disclosure: the SKILL.md points to references/, scripts/, and assets/ files that are not present in the bundle, so the navigation it advertises does not resolve.

Suggestions

Ship the referenced bundle files (references/chaos_principles.md, references/experiment_design.md, references/attack_taxonomy.md, references/tooling_landscape.md, the three scripts, and the two asset templates) so the body's progressive-disclosure links resolve, or remove references to files that are not included.

Add an explicit 'fix and re-validate' loop to Workflow 1 (e.g. if blast radius is YELLOW/RED, reduce scope and re-run the calculator) to make the destructive-operation feedback loop fully explicit.

Trim the restated '4 Principles of Chaos Engineering' and the 'Verifiable success' metrics to leaner pointers, since Claude can be assumed to know the underlying principles, preserving only the discipline-enforcing additions.

Dimension	Reasoning	Score
Conciseness	Mostly efficient with quick-start commands, tables, and short tool sections, but the restated Netflix principles and the 'Anti-patterns'/'Verifiable success' sections add some content that Claude could largely infer; minor trimming possible.	4 / 5
Actionability	Fully executable, copy-paste-ready python invocations with complete flag sets (e.g. '--target', '--hypothesis', '--attack', '--magnitude', '--abort-if'), covering the common design/blast-radius/postmortem cases with enumerated outputs.	5 / 5
Workflow Clarity	Workflow 1 has an explicit validation checkpoint (step 3 'confirm GREEN before proceeding') and abort feedback (step 8), but the fix-and-re-validate loop wording is implicit and Workflow 2/3 are lighter on checkpoints, leaving minor validation gaps.	4 / 5
Progressive Disclosure	References are well-signaled and one level deep (a References section plus inline 'See references/attack_taxonomy.md'), but the referenced bundle directories (references/, scripts/, assets/) do not actually exist, so the disclosed structure is broken/dangling rather than navigable.	3 / 5
	Total	16 / 20 Passed

Description

100%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 model description: it states concrete capabilities, enumerates comprehensive natural trigger terms and tool names, explicitly gives both what and when, and clearly distinguishes itself from neighboring skills. Third-person imperative voice is used correctly throughout.

Dimension	Reasoning	Score
Specificity	Lists multiple concrete actions ('experiment designer, blast-radius calculator, and postmortem generator') plus the activities of 'planning, running, or learning from chaos engineering experiments', giving comprehensive coverage of capabilities.	5 / 5
Completeness	Explicitly answers both 'what' (the three tools, references, slash command) and 'when' ('Use when planning, running, or learning from... Triggers on...') with concrete trigger phrases.	5 / 5
Trigger Term Quality	Enumerates comprehensive natural trigger phrases ('chaos experiment', 'fault injection', 'gameday', 'resilience test', 'blast radius', 'steady state', 'abort criteria') plus the major tool names users would say.	5 / 5
Distinctiveness Conflict Risk	Occupies a clear niche (chaos engineering) with distinctive trigger vocabulary and explicit composition boundaries (feature-flags-architect, kubernetes-operator, incident-response), minimizing wrong-skill triggering.	5 / 5
	Total	20 / 20 Passed

Validation

87%

Warnings & errors only

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

Criteria	Description	Result
frontmatter_unknown_keys	Unknown frontmatter key(s) found; consider removing or moving to metadata	Warning
referenced_paths_exist	Referenced path issues: 11 missing	Warning

	Total	14 / 16 Passed

Repository: alirezarezvani/claude-skills
Path: .gemini/skills/skills-chaos-engineering/SKILL.md
Commit: 19392f7

Reviewed: ~4 hours ago

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