Skip to main content
Glama

numertel

by pl.numertel

Sprawdź wiadomość: domeny i numery

check_scam_domain
Read-onlyIdempotent

Sprawdza wklejoną podejrzaną wiadomość: (1) domeny, linki i adresy e-mail przeciw państwowej Liście Ostrzeżeń CERT Polska (mirror ~129 tys. domen oszustów), (2) polskie numery telefonów z treści przeciw bazie NumerTel (wykaz DNO UKE = spoofing, Biała Lista oficjalnych infolinii, zgłoszenia spamu). UŻYJ, gdy użytkownik pyta: czy ten link/strona/mail jest bezpieczny, albo wkleja całego SMS-a lub e-mail z linkiem i numerem. Przyjmuje pojedynczą domenę, URL, e-mail, numer lub CAŁĄ treść wiadomości (rozpoznaje zapisy evil[.]pl, hxxp:// i +48). Werdykt deterministyczny, zero LLM. Dane: numertel.pl.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
textYesDomena, URL, adres e-mail, numer telefonu albo pełna treść wiadomości do sprawdzenia (max 5000 znaków)

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
as_ofYes
phonesYes
sourceNo
checkedYes
list_sizeYes
any_listedYes
attributionYes
any_phone_flaggedNo

Schema Changelog

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

  1. Changed4 schema fields changed
    • changedInput schema / properties / text / description
      Previous value: -"Domena, URL, adres e-mail albo pełna treść wiadomości do sprawdzenia (max 5000 znaków)"New value: +"Domena, URL, adres e-mail, numer telefonu albo pełna treść wiadomości do sprawdzenia (max 5000 znaków)"
    • addedOutput schema / properties / any_phone_flagged
      Added value: +{
+  "type": "boolean"
+}
    • addedOutput schema / properties / phones
      Added value: +{
+  "items": {
+    "properties": {
+      "e164": {
+        "type": "string"
+      },
+      "is_dno": {
+        "type": "boolean"
+      },
+      "number": {
+        "type": "string"
+      },
+      "operator": {
+        "type": [
+          "string",
+          "null"
+        ]
+      },
+      "sightings_30d": {
+        "type": "integer"
+      },
+      "spam_label": {
+        "type": "string"
+      },
+      "total_opinions": {
+        "type": "integer"
+      },
+      "url": {
+        "type": "string"
+      },
+      "whitelist_institution": {
+        "type": [
+          "string",
+          "null"
+        ]
+      }
+    },
+    "required": [
+      "number",
+      "e164",
+      "spam_label",
+      "is_dno",
+      "url"
+    ],
+    "type": "object"
+  },
+  "type": "array"
+}
    • changedOutput schema / required
      Previous value: -[
-  "checked",
-  "any_listed",
-  "list_size",
-  "as_of",
-  "attribution"
-]New value: +[
+  "checked",
+  "phones",
+  "any_listed",
+  "list_size",
+  "as_of",
+  "attribution"
+]
  2. Added

TDQS

A4.6/5.0
Behavior4/5

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

Annotations already establish readOnly and idempotent behavior, so the description adds valuable extra context: the verdict is deterministic ('Werdykt deterministyczny, zero LLM') and the data sources are clearly attributed (CERT Polska, NumerTel, numertel.pl). It also discloses recognition of obfuscated formats, which helps set expectations. No contradiction with annotations.

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 dense but well-structured, front-loading the core action, then usage trigger, then acceptable inputs, then behavioral guarantees. Every sentence earns its place: it packs purpose, scope, examples, and data provenance without fluff or redundancy.

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?

Given the tool's moderate complexity, the presence of an output schema, and the readOnly/idempotent annotations, the description covers all essential aspects: what it checks, when to use it, what inputs it accepts, how it behaves (deterministic), and where its data comes from. It does not need to explain return values because the output schema exists.

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?

Although the schema already documents the 'text' parameter well, the description meaningfully enriches it by explaining accepted input forms (single domain, URL, email, number, or entire message) and how obfuscated formats are handled (evil[.]pl, hxxp://, +48). This goes beyond the schema's basic type description and gives the agent practical guidance for what to pass.

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 a specific verb-resource pair: checking pasted suspicious messages against CERT Polska's warning list and NumerTel phone database. It explicitly lists the artifact types (domains, links, emails, phone numbers) and distinguishes itself from the phone-only sibling tool by handling whole messages and multiple entity types.

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 provides an explicit trigger condition: 'UŻYJ, gdy użytkownik pyta: czy ten link/strona/mail jest bezpieczny...' This is strong when-to-use guidance. However, it does not mention when not to use it or name alternative sibling tools (e.g., check_phone_number) for phone-only queries, so it lacks explicit exclusions.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

All numertel toolsInspect
Try in Browser
RayrunBuild, deploy, and operate MCP servers without becoming an infrastructure team.ray.runAd

Glama MCP Gateway

Add one secure layer between your agents and this server.

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.

Resources