# AI Import Column Mapping

## Objective

Guess how an uploaded file's columns line up with the app's fields, then ask.

A proposed mapping from uploaded columns to destination fields, shown with samples and confirmed before the import runs.

## Before You Begin

This feature is being added to an application that already exists and already
works. Do not scaffold a new project, and do not assume a blank slate.

Inspect the codebase first and establish:

- The existing application structure and where code of this kind already lives.
- The framework and version in use.
- The existing design system — colours, spacing, typography, and component conventions.
- Existing UI components you can reuse instead of writing new ones.
- The existing database structure, if this feature needs to persist anything.
- The existing authentication and authorization system, if this feature is user-scoped.
- Dependencies already installed, so you don't add a library that duplicates one.
- The existing test setup and conventions.

Only start writing code once you understand the above. If the application
already implements part of this feature, extend it rather than replacing it.

## Implementation Instructions

1. Take the uploaded headers and a small sample of rows and propose a mapping to the destination fields. Match on exact and near-exact header names first and only consult the model for the columns that remain unresolved.
2. Constrain the candidate set to fields the current user and the importer are actually permitted to write. A mapping that targets a read-only, computed, or privileged field must never be offered, whatever the header says.
3. Show the proposal as a table: source column, sample values, destination field, confidence, and the transformation that will be applied. A user cannot approve a mapping they cannot see the effect of.
4. Require an explicit confirmation before any row is written, with low-confidence and unmapped columns called out for attention. Do not start the import on the strength of the suggestion alone.
5. This brief ends when the mapping is confirmed. Rows that then fail validation belong to AI Import Error Repair, and corrections to data already stored belong to AI Data Cleanup Suggestions; hand off rather than duplicating their review screens.

## UI and UX Requirements

Match the application's existing design system exactly. Reuse its components,
spacing, and typography. This feature should look like it was always there.

## Responsive Requirements

Works on mobile, tablet, and desktop. Touch targets are large enough to hit on a
phone, and nothing overflows horizontally at 320px.

## Accessibility Requirements

- Fully keyboard navigable.
- Correct semantic elements and ARIA roles.
- Visible focus states.
- Meets WCAG AA contrast.
- Dynamic changes are announced to screen readers.
- Respects prefers-reduced-motion.

## Edge Cases

- Only fields the importer may write can be offered as targets. Filter the candidate list by permission before the suggestion is made, not after the user has chosen.
- Every proposed mapping needs a confidence and a worked sample showing what a real value becomes after transformation, so a wrong date or currency assumption is visible before the import rather than after.
- Two source columns silently pointing at one field will overwrite each other unpredictably. Detect the collision, refuse to proceed, and make the user resolve it.
- Custom fields defined per workspace and headers in another language both need to map. Read the destination list at runtime rather than assuming a fixed schema, and match on meaning rather than English keywords alone.
- No row is written until the user confirms. An import that begins while the mapping preview is still on screen cannot be taken back.
- Columns the user leaves unmapped must be reported explicitly before confirmation, because silently dropped data is discovered weeks later.
- Files with no header row, duplicate headers, or a header row that is actually data must be handled rather than mapped confidently to nonsense.
- Send only headers and a bounded sample of rows to the model, never the whole file, and set a ceiling on that sample so a large upload cannot run up an unbounded cost.

## Testing

Exercise the feature end to end in the running application. Cover every edge case
above, then run the existing test suite and confirm nothing regressed.

## Acceptance Criteria

- [ ] Uploaded columns arrive with a proposed destination field, a confidence, and a sample transformation.
- [ ] Only fields the importer and the current user may write appear as mapping targets.
- [ ] Two columns mapped to the same field block confirmation until resolved.
- [ ] Unmapped columns are listed explicitly before the user confirms.
- [ ] No rows are written until the user confirms the mapping.
- [ ] Workspace-specific custom fields and non-English headers map correctly.
- [ ] Only headers and a bounded row sample are sent to the model.
- [ ] The feature matches the existing design system.
- [ ] No existing functionality is broken.

## Adaptation Rules

- Match the existing design system. Do not introduce a new colour palette,
  spacing scale, or component library.
- Reuse existing components and utilities wherever they fit.
- Follow the naming, file layout, and code style already present.
- Do not upgrade, replace, or remove existing dependencies to make this
  feature fit. Adapt the feature to the app, not the app to the feature.
- Do not break existing functionality. If a change is genuinely required in
  existing code, make the smallest one that works and say so.
- If something in these instructions conflicts with how the application is
  built, follow the application and explain the deviation.

## Final Verification

Before you report the work as done:

1. Re-read the acceptance criteria above and check each one against what you
   actually built.
2. Run the application and exercise the feature end to end.
3. Run the existing test suite and confirm you have broken nothing.
4. Check the feature on mobile, tablet, and desktop widths.
5. Check keyboard navigation and focus handling.
6. Summarize what changed: files added, files modified, and anything you
   deliberately did differently because of how this application is built.

If any acceptance criterion is unmet, fix it before reporting completion.