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get_company_financials

Retrieve historical annual financial reports (RGFI/GFI) submitted to FINA by a Croatian company over a specified range of reporting years using its OIB or MBS. To inspect detailed statutory line items (AOP codes), set include_aop_lines=true and provide aop_filter. RULES: Never invent financial figures, revenues, expenses, or identifiers. If identifier is missing, interview the user first.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
to_yearNoOptional end year (e.g. 2024)
from_yearNoOptional start year (e.g. 2018)
aop_filterNoOptional list of specific AOP codes to filter when include_aop_lines is true
identifierYesThe company identifier (OIB or MBS)
include_aop_linesNoIf true returns full raw AOP JSON data

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A4.2/5.0
Behavior4/5

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

With no annotations, the description carries the full burden, and it does disclose real behavior: results are limited to annual RGFI/GFI filings, include_aop_lines=true returns full raw AOP JSON, and the agent must not fabricate figures or identifiers and must interview the user if the identifier is absent. It omits error behavior, permissions/auth requirements, and pagination or result-size limits.

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, all front-loaded: purpose first, then the AOP opt-in, then the integrity rules. Nothing is redundant with the name or title, and every sentence has a distinct function.

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

Completeness4/5

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

For a 5-parameter tool with no output schema and no annotations, the description covers what is returned (historical annual reports, optionally raw AOP JSON) and the identifier prerequisite. It is slightly thin on output shape and edge cases, but an agent has enough to call it correctly.

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%, so all five parameters are already documented in the schema, including the include_aop_lines/aop_filter dependency and the OIB/MBS meaning of identifier. The description restates that dependency without adding syntax, format, or range semantics beyond what the schema provides, 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?

The description states a precise verb and resource — retrieve historical annual financial reports (RGFI/GFI) filed with FINA — and scopes it to a single Croatian company identified by OIB or MBS. That per-company, historical framing implicitly separates it from siblings like search_financial_screener or get_company_overview, so an agent can select it without opening the schema.

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?

It gives clear operational context: use include_aop_lines=true with aop_filter to drill into statutory AOP line items, and interview the user when the identifier is missing. It does not, however, state when to prefer this over search_financial_screener or other siblings, so it stops short of explicit alternatives.

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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