feat: always-on Insights — correlation analysis over viewing habits

Conservative, live insights (ADR-0010) derived from each user's diary:
rating lift by genre (first-time watches only), genre seasonality vs a
uniform 1/12 month baseline, medium weekend-lift, and watch-time rhythm.

- domain: WatchRow model, InsightsQuery port, pure insights_analyzer with
  all honesty thresholds (sample minimums, strength cutoffs, suppressions
  for import noise), unit-tested
- adapters: thin Sqlite/Postgres fetch twins, reusing WrapUp's genre fetch
- application: get_insights use case, InsightsGroup in Deps
- composition/server: wiring through Repositories/DatabaseOutput
- presentation: GET /api/v1/insights handler, typed serde-tagged DTOs,
  openapi doc
- spa: /insights route (shadcn cards), insights feature hook, profile
  entry link, en locale strings
- server test: end-to-end seed sqlite → HTTP → rating lift + rhythm

Also records ADR-0010, defines "Insight" in the glossary, and includes
pre-existing worktree comment-stripping cleanups.

crates/application/src/movies/discovery_indexer.rs

@@ -8,9 +8,6 @@ use domain::{
     ports::{EventHandler, MovieQuery, SearchCommand},
 };
 
-/// Reacts to `MovieDiscovered` and inserts a bare search index entry immediately,
-/// so movies are findable before TMDb enrichment runs.
-/// Enrichment will later overwrite this with the full document (cast, genres, etc.).
 pub struct MovieDiscoveryIndexer {
     movie_repository: Arc<dyn MovieQuery>,
     search_command: Arc<dyn SearchCommand>,

crates/application/src/movies/enrich_movie.rs

@@ -8,22 +8,18 @@ use domain::{
 use crate::movies::{commands::EnrichMovieCommand, deps::EnrichMovieDeps};
 
 pub async fn execute(deps: &EnrichMovieDeps, cmd: EnrichMovieCommand) -> Result<(), DomainError> {
-    // 1. Persist the enriched profile (also handles movie_cast, movie_crew, genres, keywords)
     deps.movie_profile.upsert(&cmd.profile).await?;
 
-    // 2. Upsert persons extracted from cast + crew (no reads — only upsert)
     let persons = extract_persons(&cmd.profile.cast, &cmd.profile.crew);
     if !persons.is_empty() {
         deps.person_command.upsert_batch(&persons).await?;
     }
 
-    // 3. Fetch the movie for the search index document
     let Some(movie) = deps.movie_query.get_movie_by_id(&cmd.movie_id).await? else {
         tracing::warn!(movie_id = %cmd.movie_id.value(), "enrich_movie: movie not found after profile upsert");
         return Ok(());
     };
 
-    // 4. Index the movie in search
     deps.search_command
         .index(IndexableDocument::Movie {
             id: cmd.movie_id.clone(),
@@ -32,7 +28,6 @@ pub async fn execute(deps: &EnrichMovieDeps, cmd: EnrichMovieCommand) -> Result<
         })
         .await?;
 
-    // 5. Index each unique person in search (no reads — persons built from in-memory data)
     for person in &persons {
         deps.search_command
             .index(IndexableDocument::Person {
@@ -50,9 +45,6 @@ pub async fn execute(deps: &EnrichMovieDeps, cmd: EnrichMovieCommand) -> Result<
     Ok(())
 }
 
-/// Build unique Person values from cast and crew.
-/// Uses deterministic UUIDv5 so the same tmdb_person_id always maps to the same PersonId.
-/// No DB reads — persons are built entirely from in-memory TMDb data.
 fn extract_persons(cast: &[CastMember], crew: &[CrewMember]) -> Vec<Person> {
     let mut seen: HashMap<u64, Person> = HashMap::new();
 

crates/application/src/movies/resolve.rs

@@ -9,9 +9,6 @@ use domain::{
 use crate::diary::commands::MovieInput;
 use crate::diary::movie_resolver::{MovieResolver, MovieResolverDeps};
 
-/// Resolves a movie from input, persists it, and publishes `MovieDiscovered` if new.
-///
-/// Returns `(movie, is_new_movie)`.
 pub async fn resolve_and_persist_movie(
     input: &MovieInput,
     movie_command: &dyn MovieCommand,