searchWyszukiwanie w bazie NumerTel: podaj polski numer telefonu (zwróci jego kartę reputacji) ALBO nazwę banku/urzędu/operatora (zwróci zweryfikowane oficjalne numery z Białej Listy infolinii). Wyniki zawierają id, title i url.
| Name | Required | Description | Default |
|---|---|---|---|
| query | Yes | Numer telefonu (9 cyfr / +48...) lub nazwa instytucji, np. 'mBank', 'ZUS' |
Changes observed during successful MCP inspections. Dates show when Glama detected each change.
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint=true and idempotentHint=true, so the safety profile is covered. The description adds valuable behavioral context: it specifies the Polish number format, the 'White List' source for verified official numbers, and that results contain id, title, and url. This goes beyond the annotations without contradicting them.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is two sentences, front-loaded with the core action ('Search in NumerTel database'), and contains no wasted words. It efficiently communicates the two modes and the result structure.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
With a single parameter, no output schema, and good annotations, the description fully compensates for the missing output schema by stating the result fields. It also mentions the verified nature of the official numbers. No crucial information is missing for a tool of this simplicity.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The schema already provides 100% coverage for the query parameter, including examples ('mBank', 'ZUS'). The description repeats essentially the same information (number or institution name) without adding new semantic details. Since the schema does the heavy lifting, a baseline score of 3 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states that the tool searches the NumerTel database, with two distinct modes: searching by Polish phone number to get a reputation card, or by institution name to get verified official numbers. It explicitly mentions the result fields (id, title, url), making the tool's purpose unambiguous and differentiated from siblings like check_phone_number.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides clear guidance on when to use the tool: when a phone number or institution name needs to be looked up in the database. It outlines the two types of queries accepted. However, it does not explicitly contrast with sibling tools such as check_phone_number or find_official_number, so it stops short of a full when-not/alternatives explanation.
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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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.
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.
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.
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.