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Get key financials from an annual report

get_financials

Retrieve a Danish company's financial figures from its annual report via CVR number: revenue, profit, equity, assets, cash, employees, and auditor. Notes explain any missing data.

Instructions

Read a Danish company's published annual report (XBRL) and return key figures for the reporting year and the year before: revenue, gross profit, profit, equity, assets, cash, employees, plus auditor. Values are in the filing's currency (usually DKK). Small companies often omit revenue legally; notes explain gaps and conflicts instead of guessing.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
cvrYesDanish CVR number, 8 digits (spaces, dashes and a DK prefix are accepted).
yearNoCalendar year the reporting period ends in. Omit for the latest annual report.

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

A4.3/5.0
Behavior4/5

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

With no annotations provided, the description carries the full behavioral burden. It discloses that values use the filing currency, often DKK, and that revenue may be legally omitted by small companies—with notes explaining gaps and conflicts instead of guessing. This goes beyond input mechanics, though it does not specify behavior for missing filings or errors.

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?

Three sentences with no filler: the first states the action and result, the second clarifies currency, and the third handles edge cases around omitted revenue and guessing. The key information is front-loaded, and every sentence earns its place.

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?

There is no output schema, but the description enumerates all returned fields, explains the two-year comparison, and covers the main edge case. The two parameters are fully documented in the schema, so an agent has enough information to invoke the tool correctly and interpret the results.

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?

The input schema already describes both parameters fully, with 100% coverage, so the baseline is 3. The description adds useful output context such as 'reporting year and the year before' and currency, but it does not add new per-parameter constraints or syntax beyond what the schema already provides.

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?

The description uses a specific verb and resource: 'Read a Danish company's published annual report (XBRL)' and return key figures. It clearly enumerates the outputs, making it easy to distinguish from the sibling tool list_filings, which is about discovering filings rather than extracting financials.

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

Usage Guidelines4/5

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

The description makes the context clear: use this when you need key financial numbers from a Danish annual report, including the prior-year comparison and currency behavior. It does not explicitly name list_filings as an alternative or state when not to use this tool, so exclusions are absent, but the intended use is unambiguous.

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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