Search Austrian companies

    This is the primary entry point: search/find/look up companies by NAME (substring) or
    filter by location, industry, legal form, size or financials, ranked. Whenever the user
    names a company or wants a list of companies, call THIS tool first (you do not need the
    Firmenbuchnummer/FNR to search by name). Read-only.

    Parameters:
    - filters (optional): a SearchFilters object; every field is optional and AND-combined
      (name substring; legal_form; bundesland; oenace_section/division/group and the
      4-digit oenace_class for one exact activity (11.05 = breweries; list_sectors(query=…)
      resolves a category word to the code); size_gkl W/K/M/G; bilanzsumme / anlagevermoegen
      / revenue / equity_ratio / employees min+max ranges; growth_profile; has_guv;
      last_filing_year_min;
      founded_year_min/max; gf_age_min; status active/inactive/all). Omit for an unfiltered
      list. Full-name inputs like "Wien" or "GmbH" are mapped to stored codes automatically.
      equity_ratio_min/max are FRACTIONS of the Bilanzsumme (0.35 = 35 % Eigenkapitalquote);
      percent-style values (>1.5, up to 100) are auto-converted /100, so 35 and 0.35 both
      mean 35 %.
    - sort (optional): {field, descending}; the sort field for the founding year is
      "founded_year" (never founded_year_min); an unknown field is rejected with the list
      of valid ones. field in {bilanzsumme, anlagevermoegen, revenue, equity_ratio,
      employees, last_filing_year, founded_year, revenue_growth_1y, revenue_growth_3y,
      revenue_growth_5y}
      (Umsatzwachstum: 1y YoY, 3y/5y CAGR; only companies with a multi-year GuV have them, the
      rest sort last) (or "distance" with a near filter); default bilanzsumme
      descending. Companies missing the sort field sort last. An unknown sort field is
      rejected with the list of valid ones. With a `query`, the matched companies are
      relevance-ranked by DEFAULT; pass an explicit sort to order them by that metric instead
      (e.g. "die größten Medienhäuser" -> query + sort bilanzsumme). For an exhaustive
      "largest in sector X" ranking prefer a structured filter (oenace_*) over query, since a
      query returns a relevance shortlist, not the whole sector.
    - page (optional, default 1) and page_size (optional, default 25, clamped to 1..100).
    - after (optional): KEYSET paging for bulk extraction — pass "" to start, then feed the
      response's `next_after` back here for each next page (FNR-ordered, no offset ceiling); an
      empty page means done. Not combinable with `query`/`near` (ranking has no stable cursor).
      Prefer this over deep `page` for exporting a whole segment. Credit-metered accounts:
      keyset pages are EXTRACTION and cost 1 credit per returned company (same rate as
      export_companies_csv); normal `page` browsing costs 1 credit per started 25 rows.
    - exact_count (optional, default false): force an exact `total` in keyset mode (a full COUNT
      scan). In normal (offset) mode `total` is always exact already; `total_semantics` reports
      "exact" vs "page_only".

    Returns the total match count plus a COMPACT summary card per company on the page (name,
    legal_form, bundesland, size, Bilanzsumme, equity ratio, revenue, growth, has_guv, industry)
    — NOT the full record. Use to find/rank companies; for one company's full profile call
    get_company_details, for the complete record call get_full_record, for aggregates over a
    whole group call get_cohort_summary.

    Query recipes (pick ONE primary strategy per user intent):
    - Specific company by name: filters={"name": "<name>"} — substring, case-insensitive.
      Results are relevance-ordered (exact/prefix matches first) when the hit set is small
      (≤200); a broader name acts as a market screen and keeps the numeric sort.
    - Industry as a CONCEPT ("tech companies", "Metallverarbeiter"): use oenace_division /
      oenace_group (codes + German labels via describe_fields), NOT geschaeftszweig.
    - Industry by literal ACTIVITY TEXT: geschaeftszweig matches the Firmenbuch free-text
      description as substring ("anlagenbau" works; "technisch" won't — it's not semantic).
    - Free-text query: filters={"query": "<text>"} searches name + activity and combines with
      all structured filters; cards carry match_reason. Semantic activity recall is live — a
      concept query surfaces companies by what they DO even without the literal words, and the
      matched pool is relevance-ranked by default (pass an explicit sort to override).
    - Region: bundesland (broad) > city (exact town) > postal_code prefix. Radius: use
      near={"place":"Gmunden","radius_km":25} or near={"postal_code":"4810","radius_km":25};
      cards get distance_km and sort by distance. An ambiguous town name is rejected with the
      candidate PLZs.
    - Recent corporate EVENT ("companies that raised capital / changed management / were
      acquired / changed owners"): add event_signal + event_since to filters, e.g.
      filters={"oenace_division":"41","bilanzsumme_min":5000000,"event_signal":["capital_raise"],
      "event_since":"2024-01-01"}. Signal groups: "ownership_change" (Gesellschafter-
      Kapitaländerung, often a share transfer), "leadership_change", "capital_raise",
      "restructuring" (Verschmelzung/Spaltung/…), "new_company", "closure", "rebrand",
      "relocation". Combines with EVERY financial/profile filter; each returned card gains
      `events` (the triggering register changes, rich values on forward events) +
      latest_event_date. Default window 365 days. This is the deal-sourcing / sales-trigger
      surface. Pro. (For the raw cross-company event log use list_events; for counts
      get_event_stats.)
    - Zero hits? Read `relaxations` in the response and adjust THAT filter; do not retry
      blind variations. `applied_filters` echoes how your inputs were normalized.

    The response also carries has_more (another page exists) and, when total==0 with ≥2
    filters, relaxations (which single filter to drop, most-permissive first).
    Field reference: https://www.agentic-firmenbuch.at/felder.html