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SelskabsInfo — Danish company data

List bankruptcies of Danish companies

list_bankruptcies
Read-only

Bankruptcy decrees (konkursdekreter) for Danish companies as the bankruptcy courts publish them in Statstidende, newest decree first: the court, case number and trustee (kurator), with the company's industry and company form from CVR. Needs no CVR number, so it answers "which companies went bankrupt" filtered by decree date, court, industry, city or name. One row per bankruptcy: a decree printed again or corrected appears once, as its newest notice. Companies only: personal bankruptcies and sole proprietorships in the owner's name are not listed. Complete for decrees from January 2026 on; the handful of earlier decrees it holds are not a full record, so do not count bankruptcies before 2026 with it. A decree arrives when Statstidende prints it, two days after it at the earliest and nearly always within a week, so the past week is still filling in. Statistics Denmark's monthly figure is a different count, not a contradiction: it dates a bankruptcy by its notice in Statstidende, not by the decree, and it includes sole proprietorships, so a month counted here differs from it, most when many decrees fall in the month's last days. "total" is the full count of matches, so "how many" takes one call, not paging. A row's "cvr" is null when the notice gave none; otherwise get_company and the section tools take it from there. "virksomhedsform" is CVR's short code here (APS, A/S), not the full name list_new_companies gives. Costs 1 credit per page and works on every plan.

Input Schema

NameRequiredDescriptionDefault
toNoLatest decree date to include, YYYY-MM-DD.
cityNoCity, exact match including the postal district: "København K" or "Aarhus C", not "København". Matches the city on the notice or the company's registered city, which can be spelled differently ("Århus C", "Aarhus C"). When unsure of the spelling, list without this filter and reuse a value from the results.
fromNoEarliest decree date to include, YYYY-MM-DD.
pageNoPage of results, starting at 1. page × per_page may be at most 100000.
courtNoBankruptcy court (skifteret), exact match, e.g. "Sø- og Handelsretten" or "Retten i Aarhus".
queryNoPart of the company name, matched anywhere in it and ignoring case.
industryNoIndustry, exact match on the Danish text CVR uses, e.g. "Servering af mad i restauranter og caféer". When unsure of the spelling, list without this filter and reuse a value from the results.
per_pageNoRows per page (max 100). Every page costs a credit, so to count, read "total" rather than paging through the rows.

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A4.7/5.0
Behavior5/5

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

Goes well beyond the readOnly/openWorld annotations: it discloses the deduplication rule (one row per bankruptcy, newest notice wins), the ingestion latency (two days after printing, usually within a week, so the past week is still filling in), coverage boundaries (complete only from January 2026), null cvr rows, and the credit cost per page. These are exactly the operational facts an agent needs before trusting the result.

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

Conciseness5/5

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

Dense but waste-free: identity first, then filters, dedup, coverage limits, latency, the Statistics Denmark reconciliation, output shape, and cost. Every sentence carries an operational fact and the caveats are front-loaded rather than buried.

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?

With eight optional parameters, no output schema, and rich annotations, the description covers what is missing elsewhere: freshness, completeness horizon, dedup semantics, null handling, and cost. Nothing an agent needs to call or interpret this tool is absent.

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

Parameters3/5

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

Schema description coverage is 100% and the schema itself already documents each filter, including spelling pitfalls for city and industry. The description reinforces 'total' as the match count and explains the cvr/virksomhedsform shape, but adds little parameter-level detail the schema does not already carry, so the baseline 3 applies.

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?

Opens with a specific verb and resource ('Bankruptcy decrees ... for Danish companies') and immediately scopes it against the sibling tools by noting that get_company and the section tools consume the returned cvr. An agent can distinguish this from search_companies or list_new_companies 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?

States explicitly that no CVR number is needed, lists the filter axes (decree date, court, industry, city, name), and excludes personal bankruptcies and sole proprietorships. It also warns not to use it for pre-2026 counts and explains why its monthly totals differ from Statistics Denmark's.

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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