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testland/chaos-experiment-author

Build-an-X workflow for a chaos experiment per the Principles of Chaos Engineering - defines steady-state hypothesis, picks the variables (real-world events: network latency, node failure, region outage), sets the blast radius (which percentage / namespace / user cohort), automates execution, and emits the verdict (steady-state held / didn't hold). Use to scope a chaos experiment before running it via Litmus / Chaos Mesh / Gremlin / Toxiproxy.

75

Quality

94%

Does it follow best practices?

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SecuritybySnyk

Passed

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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.

A well-structured, actionable skill body with executable examples, a clear sequenced workflow, and proper offloading of detail to a one-level reference. The only weakness is mild verbosity from quoting and restating the chaos principles.

Suggestions

Trim the Overview's verbatim principlesofchaos.org definition to a brief paraphrase, since the concept is well known and the five principles are already enumerated there.

Avoid restating 'Per principles principle N' at the start of every step; a single mapping in the Overview is enough, letting each step focus on the action.

Consider moving the per-step principle citations into the reference or a compact table to recover tokens in the body.

DimensionReasoningScore

Conciseness

Mostly efficient with code blocks and a table, but the Overview quotes the full principlesofchaos.org definition and restates the principles at each step, which is mild padding of a concept Claude already knows. Not score 3 because it could be tightened; not score 1 because it avoids concept tutoring.

2 / 3

Actionability

Provides executable, copy-paste-ready YAML for the hypothesis and blast radius plus a real GitHub Actions workflow with kubectl/wait/jsonpath commands, rather than pseudocode or vague direction.

3 / 3

Workflow Clarity

Clear seven-step sequence tied to principles, with explicit validation/abort checkpoints (abort_conditions, 'wait for completion + check verdict', staging->canary->production progression) for these inherently destructive operations.

3 / 3

Progressive Disclosure

SKILL.md is a concise overview that offloads the event catalog, report template, and anti-patterns to references/experiment-authoring.md (a real, one-level-deep file) via clearly signaled links, splitting content appropriately.

3 / 3

Total

11

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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.

A strong description that concretely enumerates the authoring actions, names the relevant tools and natural trigger terms, and gives an explicit 'when to use' clause. It is distinctive and unlikely to conflict with neighboring skills.

DimensionReasoningScore

Specificity

Lists multiple concrete actions in third person ('defines steady-state hypothesis', 'picks the variables', 'sets the blast radius', 'automates execution', 'emits the verdict') with concrete event examples (network latency, node failure, region outage), matching the multi-action anchor.

3 / 3

Completeness

Explicitly answers both what it does (the five authoring actions) and when to use it via the 'Use to scope a chaos experiment before running it via...' clause, satisfying the both-what-and-when anchor.

3 / 3

Trigger Term Quality

Includes natural terms users would say ('chaos experiment', 'steady-state hypothesis', 'blast radius') plus the named tools (Litmus / Chaos Mesh / Gremlin / Toxiproxy) and an explicit 'Use to scope a chaos experiment' trigger, giving good keyword coverage.

3 / 3

Distinctiveness Conflict Risk

Occupies a clear niche (chaos experiment authoring per the Principles of Chaos Engineering) with triggers unlikely to overlap with sibling skills like failure-injection-test-author or prod-canary-validator.

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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