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Romanian court cases of a company

get_company_court_cases

Court cases (portal.just.ro, Ministry of Justice) where a Romanian company (by CUI) is a party: summary (total, by category/stage/company role, pending vs decided, insolvency) and a case list with court, subject, stage, company role, other parties and last/next hearing. Natural persons are masked (GDPR). Costs 3 credits; not billed if nothing is found.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
cuiYesRomanian CUI, e.g. 14399840
roleNoFilter by the company's role, e.g. Reclamant (plaintiff), Pârât (defendant), Debitor, Creditor
limitNoMax cases returned (default 50, max 200); summary covers all
sinceNoOnly cases registered on/after this date (YYYY-MM-DD). Default: Jan 1, three years ago
categoryNoFilter by category, e.g. Civil, Penal, Insolventa, Contencios administrativ si fiscal

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A3.9/5.0
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 does well: it discloses the billing model ('Costs 3 credits; not billed if nothing is found') and a privacy behavior ('Natural persons are masked (GDPR)') that the agent could not otherwise know. It omits auth/permission requirements and any pagination caveat beyond the limit param.

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?

The resource and source are front-loaded in the first clause, followed by the returned summary/list fields and then the cost/privacy notes. It is dense but every clause carries information; the enumerated return-field list is slightly long but justified given there is no output schema.

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-param, no-annotation, no-output-schema tool, the description compensates by enumerating the return payload (summary breakdowns plus case list fields) and noting cost and GDPR masking. Only auth/permission expectations and any rate-limit behavior are missing.

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 every parameter (cui, role, limit, since, category) is already documented in the schema, including the 'summary covers all' nuance for limit. The description adds no syntax, format, or filter semantics beyond that, 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?

States a specific resource (Romanian court cases), the data source (portal.just.ro, Ministry of Justice), and the exact scoping key (a company by CUI). This is clearly distinguishable from the sibling get_court_case, which retrieves an individual case rather than a company's case portfolio.

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

Usage Guidelines3/5

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

The description implies the usage context (fetch all litigation for a company identified by CUI) but never states when to prefer it over get_court_case or how it relates to sibling legal tools. No explicit alternatives or prerequisites are named, leaving the agent to infer the distinction from the name alone.

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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