The body is lean — it assumes Claude's competence, teaches no basic concepts, and every section (overview, guardrail, troubleshooting, security) earns its place; the heavy procedure is correctly offloaded to the reference file.

It provides concrete, executable commands ('aws resiliencehubv2 update-service-function', 'create-service-function-resources', 'get-service' / 'list-failure-mode-assessments') and delegates the full copy-paste-ready workflow to a reference containing complete CLI invocations.

The referenced workflow is a sequenced 9-step SOP with explicit validation checkpoints and feedback loops (verify tooling before running, confirm before the billable assessment, poll until SUCCESS/FAILED), satisfying the rubric's bar for risky batch/billable operations.

The body is a clear overview pointing to a single well-signaled reference (references/assessment-workflow.md) that is one level deep with no nested references; content is appropriately split for easy navigation.

The description enumerates multiple concrete actions — 'starting assessments, understanding findings (severity, categories, recommendations), triaging by achievability, working with AI-generated service functions, and resolving findings' — rather than vague language.

It explicitly answers both what ('Runs and interprets AWS Resilience Hub v2 failure mode assessments. Covers...') and when ('Applies when the user wants to run an assessment... or has a specific finding and asks how to resolve, remediate, or fix it'), with an explicit 'Use when'-equivalent trigger clause.

It surfaces natural phrasings a user would actually say — 'run an assessment, review findings, or understand failure modes' and 'how to resolve, remediate, or fix it' — giving good keyword coverage with common variations.

It carves a clear niche (AWS Resilience Hub v2 failure mode assessments) and explicitly excludes adjacent skills ('Does not apply to initial setup (use resilience-hub-getting-started) or FIS experiments'), minimizing conflict risk.