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Znajdź oficjalny numer infolinii

find_official_number
Read-onlyIdempotent

Znajdź PRAWDZIWY, oficjalny numer telefonu banku, urzędu lub operatora w Polsce. UŻYJ, gdy użytkownik pyta: jaki jest oficjalny numer lub infolinia danej instytucji (np. ZUS, mBank, PKO, NFZ), albo chce zweryfikować, czy numer podany w wiadomości to faktyczna infolinia. Zwraca zweryfikowane numery z Białej Listy NumerTel ze źródłem (link do oficjalnej strony) i datą weryfikacji. Uwaga: dzwoniąc NA te numery trafisz do instytucji, ale połączenie PRZYCHODZĄCE z nich może być sfałszowane (spoofing). Dane: numertel.pl.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
institutionYesNazwa instytucji: bank, urząd lub operator, np. „ZUS”, „mBank”, „PKO”, „NFZ”, „Orange”

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
noteNo
countYes
queryYes
matchesYes
attributionYes

Schema Changelog

Changes observed during successful MCP inspections. Dates show when Glama detected each change.

  1. Added

TDQS

A4.2/5.0
Behavior4/5

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

Annotations already provide readOnlyHint=true and idempotentHint=true, so the safety profile is known. The description adds valuable context beyond annotations: the warning about spoofing of incoming calls, the data source (numertel.pl), and the return fields (source link, verification date). No contradiction.

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 description is well-structured with clear sections: purpose, usage, returns, and a security warning. Each sentence earns its place, though the use of all-caps emphasis is slightly noisy and could be toned down. It is efficient but not maximally concise.

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?

All essential contextual aspects are covered: what it does, when to use it, what it returns (verified numbers with source link and verification date), and a critical security caveat about spoofing. The output schema exists, so return details are handled. Low complexity (one parameter) makes this description complete.

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 the baseline is 3. The description reinforces examples of institution names (ZUS, mBank, PKO, NFZ) but does not add new semantic details beyond the schema's parameter description.

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 finds the REAL, official phone number for banks, offices, or operators in Poland, and can also verify if a number in a message is the official hotline. It uses a specific verb ('Znajdź') and resource, and is distinct from siblings like check_phone_number which likely checks scam numbers.

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 explicitly says 'UŻYJ, gdy użytkownik pyta...' and lists concrete use cases (e.g., asking for official number or verifying a provided number). However, it does not mention when not to use the tool or alternatives, so it misses the 'when-not' and 'alternatives' part for a 5.

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

A4.1/5.0
Disambiguation3/5

Some tools overlap in functionality: check_phone_number and check_scam_domain both accept phone numbers, and search and find_official_number both return official numbers. The descriptions differentiate them, but an agent might be unsure which tool is best for a given query.

Naming Consistency2/5

Tool names follow mixed conventions: check_phone_number and check_scam_domain use verb_noun, fetch and search are bare verbs, recent_scam_domains is adjective_noun, and spam_weather is noun_noun. There is no consistent naming pattern across the set.

Tool Count5/5

With 7 tools, the set is well-scoped for a phone and scam reputation service. Each tool has a distinct role, and the count feels neither sparse nor bloated.

Completeness5/5

The tool surface covers the domain comprehensively: phone number reputation, scanning suspicious messages, finding official numbers, listing recent scam domains, and providing aggregate statistics. There are no obvious dead ends or missing core operations.