/resilience-hub-failure-mode-assessment
Runs and interprets AWS Resilience Hub v2 failure mode assessments. Covers starting assessments, understanding findings (severity, categories, recommendations), triaging by achievability, working with AI-generated service functions, and resolving findings. Applies when the user
$ npx -y skills add aws/agent-toolkit-for-aws --skill resilience-hub-failure-mode-assessment --agent claude-codeHow it fires
How this skill gets triggered: by you, by Claude, or both.
- Fires itselfAuto-invocation. Claude auto-loads it when your prompt matches the work.Auto-invocation is when the right skill fires by itself at the right moment, driven by a FLOW.md router and a hook, instead of you invoking it by name. It is the difference between a skill being installed and a skill actually getting used.Read the full definition →
- You can call itInvoke it directly when you want it.
- Slash command
/resilience-hub-failure-mode-assessment
Context preview
The summary Claude sees to decide when to auto-load this skill.
Runs and interprets AWS Resilience Hub v2 failure mode assessments. Covers starting assessments, understanding findings (severity, categories, recommendations), triaging by achievability, working with AI-generated service functions, and resolving findings. Applies when the user
SKILL.md
resilience-hub-failure-mode-assessment.SKILL.mdname: resilience-hub-failure-mode-assessment
description: >
Runs and interprets AWS Resilience Hub v2 failure mode assessments. Covers starting
assessments, understanding findings (severity, categories, recommendations), triaging
by achievability, working with AI-generated service functions, and resolving findings.
Applies when the user wants to run an assessment, review findings, or understand failure modes,
or has a specific finding and asks how to resolve, remediate, or fix it.
Does not apply to initial setup (use resilience-hub-getting-started) or FIS experiments.
version: 1
Failure Mode Assessment
Overview
Domain expertise for running Resilience Hub v2 failure mode assessments, interpreting findings, triaging by severity and achievability, and driving remediation.
> The AWS MCP server is recommended for executing this skill's AWS API calls, but it is not required — all operations also work with the AWS CLI directly.
Guardrail — where this skill's own files live (MCP vs local install)
Before reading a reference file, determine how this skill was loaded:
- **Loaded via the AWS MCP `retrieve_skill` tool:** the skill's reference files are not on the local filesystem. Fetch each one through `retrieve_skill` with the `file` parameter (e.g. `file="references/assessment-workflow.md"`) — do NOT `file_read` these paths locally or search the filesystem for them.
- **Installed locally** (e.g. `.kiro/skills/resilience-hub-failure-mode-assessment/` or `~/.claude/skills/resilience-hub-failure-mode-assessment/`): read reference files from the local skill directory using the relative paths shown here.
This applies only to the skill's own reference files; always read and write user or session data in the working directory, never through `retrieve_skill`.
Run and interpret assessments
To run assessments and triage findings, follow the procedure exactly. See [references/assessment-workflow.md](references/assessment-workflow.md).
Troubleshooting
Assessment fails with INVALID_PERMISSIONS
The service's permission model (invokerRoleName / crossAccountRoles) doesn't have access to the resources. Verify the invoker role (and any cross-account roles) can describe resources in all configured regions.
Too many findings — where to start?
Prioritize by finding severity, highest first (HIGH, then MEDIUM, then LOW). For HIGH-severity findings, check the service's achievability for the relevant policy component (from `get-service` / `list-failure-mode-assessments`): NOT_ACHIEVABLE means the architecture must change before testing; ACHIEVABLE means validate the fix with an FIS experiment. MEDIUM findings: plan remediation this sprint; LOW findings: track but don't block (see the priority matrix in [references/assessment-workflow.md](references/assessment-workflow.md) Step 5).
AI-generated service functions are wrong
Update them: `aws resiliencehubv2 update-service-function` to rename or change criticality (there is no service-function "type" parameter). Reassign resources by calling `create-service-function-resources` with the desired resource set (see [references/assessment-workflow.md](references/assessment-workflow.md) for the service-function operations).
Security Considerations
- **Least privilege:** the invoker role should be scoped to read-only discovery of only the resource types in the service's input sources; avoid granting access beyond what assessment needs.
- **Encryption & access control:** recommend that S3 buckets used for report output have server-side encryption (SSE-S3 or SSE-KMS) and block public access — assessment reports can contain sensitive architectural detail. If a bucket policy grants the Resilience Hub service principal write access, scope it with `aws:SourceArn` / `aws:SourceAccount` condition keys to prevent confused-deputy writes.
- **Further reading:** see [Security in AWS Resilience Hub](https://docs.aws.amazon.com/resilience-hub/latest/userguide/security.html) and the [AWS Well-Architected Security Pillar](https://docs.aws.amazon.com/wellarchitected/latest/security-pillar/welcome.html) for securing assessment outputs and IAM configurations.
Read more
name: resilience-hub-failure-mode-assessment description: > Runs and interprets AWS Resilience Hub v2 failure mode assessments. Covers starting assessments, understanding findings (severity, categories, recommendations), triaging by achievability, working with AI-generated service functions, and resolving findings. Applies when the user wants to run an assessment, review findings, or understand failure modes, or has a specific finding and asks how to resolve, remediate, or fix it. Does not apply to initial setup (use resilience-hub-getting-started) or FIS experiments. version: 1
Failure Mode Assessment
Overview
Domain expertise for running Resilience Hub v2 failure mode assessments, interpreting findings, triaging by severity and achievability, and driving remediation.
> The AWS MCP server is recommended for executing this skill's AWS API calls, but it is not required — all operations also work with the AWS CLI directly.
Guardrail — where this skill's own files live (MCP vs local install)
Before reading a reference file, determine how this skill was loaded:
- **Loaded via the AWS MCP `retrieve_skill` tool:** the skill's reference files are not on the local filesystem. Fetch each one through `retrieve_skill` with the `file` parameter (e.g. `file="references/assessment-workflow.md"`) — do NOT `file_read` these paths locally or search the filesystem for them.
- **Installed locally** (e.g. `.kiro/skills/resilience-hub-failure-mode-assessment/` or `~/.claude/skills/resilience-hub-failure-mode-assessment/`): read reference files from the local skill directory using the relative paths shown here.
This applies only to the skill's own reference files; always read and write user or session data in the working directory, never through `retrieve_skill`.
Run and interpret assessments
To run assessments and triage findings, follow the procedure exactly. See [references/assessment-workflow.md](references/assessment-workflow.md).
Troubleshooting
Assessment fails with INVALID_PERMISSIONS
The service's permission model (invokerRoleName / crossAccountRoles) doesn't have access to the resources. Verify the invoker role (and any cross-account roles) can describe resources in all configured regions.
Too many findings — where to start?
Prioritize by finding severity, highest first (HIGH, then MEDIUM, then LOW). For HIGH-severity findings, check the service's achievability for the relevant policy component (from `get-service` / `list-failure-mode-assessments`): NOT_ACHIEVABLE means the architecture must change before testing; ACHIEVABLE means validate the fix with an FIS experiment. MEDIUM findings: plan remediation this sprint; LOW findings: track but don't block (see the priority matrix in [references/assessment-workflow.md](references/assessment-workflow.md) Step 5).
AI-generated service functions are wrong
Update them: `aws resiliencehubv2 update-service-function` to rename or change criticality (there is no service-function "type" parameter). Reassign resources by calling `create-service-function-resources` with the desired resource set (see [references/assessment-workflow.md](references/assessment-workflow.md) for the service-function operations).
Security Considerations
- **Least privilege:** the invoker role should be scoped to read-only discovery of only the resource types in the service's input sources; avoid granting access beyond what assessment needs.
- **Encryption & access control:** recommend that S3 buckets used for report output have server-side encryption (SSE-S3 or SSE-KMS) and block public access — assessment reports can contain sensitive architectural detail. If a bucket policy grants the Resilience Hub service principal write access, scope it with `aws:SourceArn` / `aws:SourceAccount` condition keys to prevent confused-deputy writes.
- **Further reading:** see [Security in AWS Resilience Hub](https://docs.aws.amazon.com/resilience-hub/latest/userguide/security.html) and the [AWS Well-Architected Security Pillar](https://docs.aws.amazon.com/wellarchitected/latest/security-pillar/welcome.html) for securing assessment outputs and IAM configurations.
Help AI coding agents build, deploy, and manage applications on AWS. The Agent Toolkit for AWS gives AI coding agents the tools, knowledge, and guardrails they need to work with AWS services.
Repo: aws/agent-toolkit-for-aws
Other skills on agent-toolkit-for-aws.
- /analyzing-release-readiness
Trigger a pre-merge release readiness review on a GitHub PR, GitLab MR, or local branch. Use when the user wants to analyze code changes for risk, correctness, and potential rollback issues before merging. Trigger words include release readiness, analyze PR, analyze MR, review
Open skill - /chatting-with-aws-devops-agent
Have a fast, conversational analysis with the AWS DevOps Agent. Use for cost optimization, architecture review, topology mapping, knowledge / runbook discovery, security audits, dependency questions, and quick diagnostics — anything that needs a 5-30 second answer rather than a
Open skill - /coordinating-multi-space-devops-agent
Coordinate the AWS DevOps Agent across multiple AgentSpaces from one Claude Code session — route questions to the right space (prod vs staging vs knowledge), query several spaces in parallel and synthesize, or compare findings across accounts. Use whenever the user has more than
Open skill - /diff-scanning-with-aws-security-agent
Run a fast AWS Security Agent diff scan on only the changed code since a git ref. Use when the user asks to scan changes, run a diff scan, check what changed for security issues, scan before committing, scan before PR, or any pre-commit/pre-push security check.
Open skill - /investigating-incidents-with-aws-devops-agent
Run a deep root-cause investigation on the AWS DevOps Agent. Use when the user describes an incident, alarm, outage, or unexplained behavior — keywords like "5xx", "503", "OOM", "latency spike", "deployment failure", "rollback", "sev1", "investigate", "root cause", "debug",
Open skill - /pentesting-with-aws-security-agent
Run an AWS Security Agent penetration test against a live web application — registers and verifies the target domain, exercises the supplied endpoints with the managed Security Agent service, and returns verified runtime findings. Use when the user asks to pentest, run a
Open skill

