Method searchNodes

src/db/queries.ts:775–892

* Search nodes by name using FTS with fallback to LIKE for better matching * * Search strategy: * 1. Try FTS5 prefix match (query*) for word-start matching * 2. If no results, try LIKE for substring matching (e.g., "signIn" finds "signInWithGoogle") * 3. Score results based on match q

(query: string, options: SearchOptions = {})

   * 3. Score results based on match quality
   */
  searchNodes(query: string, options: SearchOptions = {}): SearchResult[] {
    const { limit = 100, offset = 0 } = options;

    // Parse field-qualified bits out of the raw query (kind:, lang:,
    // path:, name:). Anything not recognised stays in `text` and goes
    // to FTS unchanged. Filters compose with the SearchOptions arg —
    // both are applied (intersection-style).
    const parsed = parseQuery(query);
    const mergedKinds =
      parsed.kinds.length > 0
        ? Array.from(new Set([...(options.kinds ?? []), ...parsed.kinds]))
        : options.kinds;
    const mergedLanguages =
      parsed.languages.length > 0
        ? Array.from(new Set([...(options.languages ?? []), ...parsed.languages]))
        : options.languages;
    const pathFilters = parsed.pathFilters;
    const nameFilters = parsed.nameFilters;
    // The text portion drives FTS/LIKE; if all the user typed was
    // filters (`kind:function`), we still need *some* candidate set,
    // so synthesise an empty-text path that returns everything matching
    // the filters.
    const text = parsed.text;
    const kinds = mergedKinds;
    const languages = mergedLanguages;

    // First try FTS5 with prefix matching
    let results = text
      ? this.searchNodesFTS(text, { kinds, languages, limit, offset })
      // Over-fetch by 5× when running filter-only (no text). The
      // post-scoring path: + name: filters can be very selective, so
      // a smaller multiplier risks returning fewer than `limit`
      // results despite the DB having plenty of matches.
      : this.searchAllByFilters({ kinds, languages, limit: limit * 5 });

    // If no FTS results, try LIKE-based substring search
    if (results.length === 0 && text.length >= 2) {
      results = this.searchNodesLike(text, { kinds, languages, limit, offset });
    }

    // Final fuzzy fallback: scan all known names and keep those within
    // a tight Levenshtein distance. Only fires when both FTS and LIKE
    // returned nothing AND there's a text portion long enough to be
    // worth fuzzing (1-char queries would match too much).
    if (results.length === 0 && text.length >= 3) {
      results = this.searchNodesFuzzy(text, { kinds, languages, limit });
    }

    // Supplement: ensure exact name matches are always candidates.
    // BM25 can bury short exact-match names (e.g. "getBean") under hundreds of
    // compound names (e.g. "getBeanDescriptor") in large codebases,
    // pushing them past the FTS fetch limit before post-hoc scoring can help.
    // Use the max BM25 score as the base so the nameMatchBonus (exact=30 vs
    // prefix=20) actually differentiates them after rescoring.
    if (results.length > 0 && query) {
      const existingIds = new Set(results.map(r => r.node.id));
      const maxFtsScore = Math.max(...results.map(r => r.score));
      const terms = query.split(/\s+/).filter(t => t.length >= 2);