Risk Registry

How This Page Was Built

1. Plan the result. We defined five risks, their scoring rules, the dashboard, and what the filters should do before asking for code.
2. Build one file. ChatGPT helped shape the content and design; Codex generated the HTML, CSS, JavaScript, and embedded risk data. One data block supplies the rows, charts, and counts.
3. Check the behavior. We tested calculations, filters, keyboard controls, responsive layouts, and changes to the data. Testing limitations were recorded rather than treated as passes.
4. Publish and verify. GitHub Pages hosts the file. We opened the public URL and checked the filters and expanded details after deployment.

1. Start With the File

Download HTML

If the link opens the page instead of downloading it, use your browser’s Save Page As option and choose HTML Only. Keep the filename index.html.

Double-click the saved file to open it in your browser. Try the filters and expand a risk. To check local operation, turn off Wi-Fi and refresh the local file. It should not need a server or an internet connection.

2. Build or Adapt With AI

To adapt this page, attach the downloaded file to your coding assistant and describe the organization, risks, and changes you want. Ask it to return the complete updated file.

To build from a written plan, copy this prompt into a coding assistant you already have access to:

Build a small risk registry as one self-contained index.html file.
Use the organization and risk information I provide. If I have not provided them, ask me for an example organization before building.

Include five risks across different domains and levels. Each risk needs an ID, title, domain, owner role, cause-event-impact statement, likelihood, impact, response, proposed next action, target likelihood and impact, verification step, and review trigger. Keep current residual risk marked "Not assessed" unless I provide assessed values.

Calculate inherent and target scores as likelihood × impact using whole numbers from 1 to 5. Use Low 1–4, Moderate 5–9, High 10–16, Critical 17–25. Explain these chosen bands. Show labels such as "High · 12" and put the arithmetic in expanded details.

Create a compact dashboard with a doughnut chart of risk counts by level, bars of counts by primary domain, and a count of High or Critical risks. Derive all summaries from the records. Charts summarize the full registry; severity buttons filter the risk list.

Use a near-black header, warm-white background, restrained orange accent, large readable text, buttons at least 52px tall, and expandable risk rows. Include written severity labels alongside color.

Put all CSS, JavaScript, and risk data inside the HTML. Use no external assets, libraries, fetch calls, installation, server, or build step. Double-clicking the file must work offline.

Check score calculations, every filter, dashboard totals, keyboard controls, and mobile wrapping. Change one record temporarily to verify that summaries update, then restore it. Test direct file opening if your environment permits it and report any test you could not run.

Return the complete index.html file and short browser-only instructions to open it locally and publish it in my own GitHub Pages repository.

3. Change One Risk and Check the Result

Try this request with the downloaded file attached:

In the risk-data JSON block, change R-001’s inherentLikelihood from 4 to 3. Keep everything else unchanged and return the complete index.html file.

Save and reopen the result. R-001 should move from Critical · 20 to High · 15. The Critical count becomes 0, High becomes 2, and the priority count stays 2. The Critical filter should show no risks. The dashboard should still total 5 risks.

Explain why you changed a rating. A lower number alone does not show that a treatment worked.

4. Publish With GitHub Pages

1. Create your own public repository on GitHub and initialize it with a README. Use information you intend to share publicly.
2. Choose Add file → Upload files. Upload index.html at the repository root and commit it to main.
3. Open Settings → Pages. Under Build and deployment, select Deploy from a branch, choose main and / (root), then save.
4. Wait for deployment, then open the URL shown in Pages settings in a private browser window. Check that the dashboard, filters, and risk details work without signing in.

To make another change, upload the revised file, commit it, and check the published result. Your commit records the change; it does not by itself prove that the page was tested or deployed.

GitHub Pages publishing instructions

The Vocabulary Behind the Build

Repository

The project’s files and change history.

Commit

A recorded set of changes, with a message explaining the work.

Deployment

Publishing a version of the page so others can open it.

The same sequence applies to your next GRC tool: plan the result, build a small version, validate its behavior, and maintain it after launch.