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Leadgen MCP

by io.github.darksider4all

lookup_director

Find Romanian companies by director or legal representative name.

Searches the ONRC reprezentanti table (persoana_imputernicita) via a
ranked FTS5 index; diacritic-insensitive ('popescu' matches 'POPESCU').
Returns companies with their director names and roles.

Args:
    name: Director / representative name to search for (e.g. "Ion Popescu").
    max_results: Maximum number of companies to return (1-100).

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
nameYes
max_resultsNo

TDQS

A4.1/5.0
Behavior4/5

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

The description discloses key behaviors: it searches the ONRC reprezentanti table via a ranked FTS5 index, is diacritic-insensitive ('popescu' matches 'POPESCU'), and returns companies with director names and roles. Since no annotations are provided, this detail bears the full burden of behavioral transparency.

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?

The description is compact, starting with the main purpose in the first sentence, followed by technical context and an Args list. All sentences add value without redundancy.

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?

Given the tool's simplicity (2 params, no output schema), the description adequately covers the key aspects: purpose, search behavior, and return value. It lacks details on result ordering or error handling, but these are not critical for this usage.

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?

The schema provides no descriptions for params (0% coverage), but the description fully explains both: 'name' is defined with an example and the purpose; 'max_results' states the range (1-100) and meaning. This adds significant semantics beyond the schema's type/default.

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 clearly states the tool's function: 'Find Romanian companies by director or legal representative name.' It specifies the resource (companies) and search criterion (director name), distinguishing it from sibling tools like lookup_business or lookup_domain.

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

Usage Guidelines2/5

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

The description provides no comparison with alternatives or guidance on when to use this tool versus other lookup tools. It describes the search mechanism and return values, but does not mention exclusions or refer to sibling tools.

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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TDQS

A4/5.0
Disambiguation5/5

Each tool has a clearly distinct purpose: web contact extraction, company registration lookup, director search, domain intelligence, and financial statements. Even the two ONRC-based tools differ in query type (name/CUI vs director name), eliminating ambiguity.

Naming Consistency4/5

Four of five tools follow the consistent 'lookup_' prefix with a clear noun (business, director, domain, financials). The fifth, 'extract_contacts', uses a verb-noun pattern but with a different verb. This is a minor deviation and still readable, but slightly breaks the uniform style.

Tool Count5/5

With exactly 5 tools, the set is well-scoped for a lead-generation server. Each tool covers a distinct aspect of lead research without redundancy, making the count appropriate for the purpose.

Completeness4/5

The toolset covers the core leadgen workflow: find companies, identify directors, extract contacts, check domains, and review financials. Minor gaps exist (e.g., no social profile lookup or email verification), but the surface is sufficient for typical lead generation tasks.

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