# Search Zero-Learning Primary Entry

## Why this exists
- Search must be the default entry into Stella Ops for users who do not know Stella terminology, domain boundaries, or internal product structure.
- The current model asks the user to understand too many concepts before they can succeed: `Find/Explain/Act`, explicit scope switching, recovery actions, and a separate AdvisoryAI destination.
- Live verification also shows a real reliability gap: suggestion chips can render even when the active corpus cannot answer them. On 2026-03-07, the running AdvisoryAI service at `http://127.1.0.44` rebuilt with `documentCount=0`, `chunkCount=0`, and `doctorProjectionCount=0`, while unified overlays rebuilt with only `chunkCount=14`. Querying `database connectivity` then returned zero cards. The current UX still offered that suggestion.

## Product rules
1. Search is the primary entry point.
2. AdvisoryAI is a secondary deep-dive opened from search, not a competing starting point.
3. Search should infer relevance and intent; the user should not need to choose a mode.
4. Search should bias to the current page context automatically; the user should not need to toggle scope.
5. Search should never advertise a suggestion that cannot execute against the active corpus.
6. Search history should contain only successful searches.
7. Telemetry remains optional. Search behavior must not depend on analytics emission.

## Target interaction model
### Entry
- Keep one primary search field in the top bar.
- Add a compact AdvisoryAI launcher icon beside the search input.
- Opening chat from that icon inherits the current page, current query, and top evidence when available.

### Query understanding
- Infer likely user intent from the query and visible page context.
- Weight current page/domain first.
- If current-scope evidence is weak, show overflow results from outside the page scope below the in-scope section instead of asking the user to broaden scope manually.

### Result presentation
- Place `Did you mean` directly below the input because it is an input correction, not a result refinement.
- Remove explicit `Find / Explain / Act` controls.
- Remove the explicit scope toggle chip.
- Remove the recovery panel.
- If top results are close in score, compose one short summary across them.
- If one result is clearly dominant, present that answer first and then cards.

### Suggestions
- Page suggestions become executable search intents, not static chips.
- A suggestion is only shown if:
  - its preferred domain has live evidence, or
  - the backend confirms non-zero candidate coverage for it.
- If the current corpus is empty for that page/domain, suppress those suggestion chips instead of showing dead leads.

### History
- Persist and render only searches that returned results.
- Keep history clear as a low-emphasis icon action, not a labeled call-to-action.

## Runtime rules
### Implicit scope weighting
- Current route/domain is a ranking boost, not a hard filter.
- Visible entity keys and last action increase local relevance.
- Out-of-scope results are still allowed, but only after in-scope candidates are exhausted or materially weaker.

### Answer blending
- If top-N cards fall within a narrow score band, emit a blended summary with citations from multiple cards.
- If score separation is strong, emit a single-result grounded answer.
- The frontend should not ask the user to choose whether they want `find` or `explain`; the backend should infer the dominant answer shape.

### Suggestion viability
- Suggestions must be validated against the current corpus before rendering.
- Knowledge/domain emptiness should be detectable so the UI can suppress invalid chips.
- Live Playwright coverage must assert that every surfaced suggestion returns visible results.

## Phase map
- Phase 1: FE primary-entry consolidation and removal of explicit search controls.
- Phase 2: AdvisoryAI implicit scope weighting, answer blending, and suggestion viability.
- Phase 3: FE consumption of overflow results and executable suggestion contracts.
- Phase 4: Live Playwright reliability matrix with corpus preflight and chip-success guarantees.