The latest Resilience Testing documentation update brings Chaos Hub directly into the docs, making it easier to discover and use fault, probe, and action templates. It also introduces a Prompt Library with ready-to-use AI prompts for Harness MCP, helping teams run resilience workflows faster using natural language.
Most teams find out their system has a weak point the hard way, when it's already down in production. Harness Resilience Testing (formerly known as Chaos Engineering) exists to flip that around. It lets you intentionally inject controlled faults into your services and infrastructure, observe how the system responds, and fix what breaks before a real incident occurs. It comes with 200+ built-in faults, probes, and actions across Kubernetes, cloud platforms, Linux, and Windows, plus an AI Reliability Agent and an MCP server so you can run and analyze experiments from your IDE instead of jumping into a separate UI every time.
In this blog, we’ll cover two updates to the Resilience Testing documentation that help close that gap. First, we’ve brought the Chaos Hub directly into the docs. Second, we’ve introduced a Prompt Libraryin natural language rather than that lets you interact with Harness MCP using natural language instead of memorizing commands.
Here's a walkthrough of both features
Chaos Hub, without leaving the docs
Go to the Resilience Testing docs, click Chaos Hub, then Enterprise Hub, and you get the full catalog of fault, probe, and action templates in one place. Filter by infra type (Kubernetes, GCP, whatever you're running), browse probe templates, and check what action templates exist before you build an experiment instead of guessing.
Prompt Library Integration
The bigger update is the Prompt Library, under the AI section in the sidebar. If you have connected Harness MCP to your IDE or Claude, you already know the hard part isn't the connection; it's knowing what to ask for. The Prompt Library gives you a set of pre-built prompts for common resilience workflows, each with input fields for your org and project name that get inserted into the prompt text as you type. Copy the finished prompt into Cursor, Claude, or wherever you run MCP, and go.
Three worth trying first:
Resilience coverage map
Audits every service in your project for chaos coverage and flags the ones with none. Fill in org and project, paste into your IDE, and it returns experiments grouped by target service, which services have zero experiments, and a priority ranking for what to fix first.
Useful as a first pass on any project you inherited or haven't touched in a while.
Service resilience risk scan
Ranks every service by unmitigated risk and surfaces AI-generated experiment recommendations you haven't acted on. Running this against a payment/banking service set returned a resilience score breakdown by service, a critical/high-risk tier, a list of recommended experiments, and a flag for anything with no new experiments in the last 30 days. It also proposed a sprint backlog from the output, which is the part worth stealing, even if you ignore everything else.
Pod failure experiment design
This one goes further than reporting; it builds and runs an experiment. Give it org, project, environment, infra type, infra name, and target deployment, and it will confirm the target is active, create an HTTP probe, and show you the full experiment configuration before saving. And then it will create and run your chaos experiment. Check out this video to see it in action.
Try it today
Pick one service in your project with no chaos experiments and no MCP history against it. Run the resilience coverage map, then the risk scan, and see what comes back. You'll probably find something closer to the Bank of Anthos result than you'd expect.
More prompts are getting added to the library as we build them out. If there's a specific resilience workflow you keep doing by hand, that's usually a sign it belongs in the library next.
New to Harness Resilience Testing? Explore our documentation to get started.
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Pritesh Kiri is a community manager, developer advocate, and open-source contributor focused on building thriving developer communities and improving developer experience. Previously, he worked as a Developer Advocate at ToolJet and DevRel Engineer at Locofy.ai.
