What the Report Library is

The Report Library, at /reports, is the home for every report in ClinyPal. It's a catalog grid organized into categories — Financial, Appointments, Patients, Practitioners, Communications, and Compliance — with search and filter tools to help you find the report you need.

What you'll learn
  • How the report catalog is organized and how to search it
  • What the Pinned KPI strip is and how it relates to the reports underneath it
  • How the "Explain this number" feature works on every KPI card
  • How the AI-suggested Refine chips and observations work, and why they can't hallucinate numbers
  • What happens if either AI feature is unavailable
ClinyPal Report Library overview
The Report Library page showing the Pinned KPI strip at the top, the search and filter bar, and the catalog grid of report cards grouped by category.

Browsing and searching the catalog

Reports are grouped into six categories:

  • Financial
  • Appointments
  • Patients
  • Practitioners
  • Communications
  • Compliance

Use the search box to filter the grid by report name, or use the category filter to narrow the view to a single group. Clicking a report card opens that report's page, where you can apply filters and view its data.

The Pinned KPI strip

At the top of the Report Library, a Pinned strip shows seven key numbers as quick shortcuts:

  • Revenue collected
  • Uninvoiced appointments
  • Rebook rate
  • SMS balance
  • Lapsed patients
  • Outstanding balances
  • New patients
The Pinned strip isn't a report on its own These seven tiles aren't separate reports — they're shortcuts into the reports that already exist elsewhere in the library. Clicking one takes you straight into the relevant report, with the same data you'd find by browsing to it manually.

AI features on every report

Every report in ClinyPal shares two AI-assisted features. They work the same way everywhere, so they're explained fully here once — other report articles link back to this section instead of repeating it.

AI-assisted features Both features below are AI-generated content layered on top of real, server-computed data. If AI is unavailable, both fail soft: the report itself keeps working normally, only the AI layer is affected.

"Explain this number"

Every KPI card, on every report, has a small ? button. Clicking it opens a popover with a one-sentence, plain-language explanation of why that number reads the way it does — for example, why revenue is down compared to last period.

Behind the scenes, clicking ? re-runs the report server-side to generate the explanation, and the result is cached per click so you're not waiting on a fresh calculation every time you reopen the same popover.

If the explanation can't load If the AI explanation is unavailable, the popover fails silently and shows "Couldn't load an explanation" instead of an error. The KPI number itself is unaffected either way.

Refine: suggested filters and observations

After a report loads, a Refine row appears with AI-suggested filter chips and short italic "observation" notes about the data you're looking at.

Clicking a chip re-runs the real report with that filter applied — it's a genuine shortcut into a filtered view, not a cosmetic suggestion.

Chips and observations can't show a hallucinated number Chip labels and observation text are never the AI's own invented wording. They're rebuilt server-side from real, validated data, and observation text is scrubbed to reject any number, percentage, or currency value before it's shown. That means even if the AI layer produced a wrong figure internally, that figure can never actually appear on screen — the display path simply won't allow it through.

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