agentic-firmenbuch

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Register change feed

list_events

Read-onlyIdempotent

Track company register changes across Austria by type, time, region, industry, or watchlist FNs — management moves, capital increases, mergers, relocations and deletions in one call.

Instructions

Cross-company feed of register CHANGES (Vollzuege), newest first — the market-watch / deal-sourcing surface. Read-only. Pro.

    Answers "which companies changed X, where, since when" in one call — e.g. management
    changes, capital increases, relocations across a region or industry, or a watchlist of FNs.
    For the change history of ONE known company, use get_company_details (its `events[]`).

    Parameters (all optional, AND-combined):
    - types: DETAILED (with before/after values), forward from 2026-07-01: "name_change",
      "seat_change", "legal_form_change", "capital_change", "management_change". COARSE
      historical (type + date only, source=change_feed, back to ~2020): "founding", "deletion",
      "merger",
      "split", "conversion", "contribution", "consolidation", "division",
      "shareholder_capital_change", "management_join", "management_leave". Omit for all. The
      M&A/restructuring types (merger/split/conversion/…) + capital_change + deletion are the
      deal- and distress-signal surface.
    - since / until: ISO dates ("2024-01-01"). Default window: the last 30 days.
    - bundesland: full name ("Wien") or code; oenace_section (letter) / oenace_division
      (2-digit); legal_form ("GmbH" or a Firmenbuch code) — same facets as search_companies.
    - fnrs: restrict to these Firmenbuchnummern (a watchlist).
    - page (1), page_size (25, max 100).

    Returns {total, page, page_size, since, until, events:[{fnr, name, date, type, description,
    source, capital_from, capital_to, managers_added, managers_removed, bundesland,
    industry_section}]}. `source` is "change_feed" for the coarse historical events (no
    before/after values) vs the detailed daily-diff events. An empty result means no matching
    change in the window (not missing data).
    Field reference: https://www.agentic-firmenbuch.at/felder.html

Input Schema

TableJSON Schema

Name	Required	Description	Default
`fnrs`	No
`page`	No
`since`	No
`types`	No
`until`	No
`page_size`	No
`bundesland`	No
`legal_form`	No
`oenace_section`	No
`oenace_division`	No

Output Schema

TableJSON Schema

Name	Required	Description	Default
No arguments

Schema Changelog

Changes observed during successful MCP inspections.

First observedv1.0.0Oct 3, 2026

TDQS

A4.9/5.0

Behavior5/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

Annotations already cover safety (readOnly, idempotent, non-destructive), yet the description adds tier gating ('Pro'), data provenance semantics for `source` (change_feed coarse vs detailed daily-diff), the critical interpretation that an empty result means no matching change rather than missing data, and the default 30-day window. This is substantial context beyond the annotations.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

Purpose and the sibling alternative are front-loaded, and the parameter block is bulleted and scannable. It is long, but the length is largely justified by ten undocumented parameters; only the extended type enumeration feels slightly dense.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness5/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a 10-param, no-required-field query tool with an output schema, the description covers scope, ordering, filtering, defaults, return shape, field semantics, and the empty-result edge case, plus a field reference link. Nothing an agent needs to call it correctly is missing.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters5/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 0%, so the description carries the full burden and does so well: it enumerates the valid `types` values split by detailed vs coarse, explains their date coverage and source, documents date formats and defaults, facet formats for bundesland/oenace/legal_form, fnrs as a watchlist, and pagination defaults/limits. This fully compensates for the empty schema.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

States a specific verb+resource ('cross-company feed of register CHANGES'), its ordering ('newest first'), and its intended use case ('market-watch / deal-sourcing surface'). It explicitly distinguishes itself from the sibling get_company_details by naming the single-company alternative, so an agent can route correctly without opening a schema.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines5/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

Gives explicit when-to-use framing ('which companies changed X, where, since when'), concrete example queries, and an explicit when-not-to-use clause routing single-company history to get_company_details. Also flags the M&A/restructuring types as the deal/distress surface, which helps an agent pick the right filter.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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