lookup

Number Lookup

vri_number_lookup

Read-onlyIdempotent

Live intelligence for ONE North American phone number: current carrier of record, line type, LRN routing data, porting activation date, and optionally caller-ID name (cnam), spam reputation, and messaging provider. Always a fresh read of live numbering infrastructure — never cached carrier data.

Input Schema

TableJSON Schema

Name	Required	Description	Default
`products`	No	Data sets to include. Default ['lrn'] (carrier/line-type/routing).
`phone_number`	Yes	US/Canada number, any common format

Output Schema

TableJSON Schema

Name	Required	Description
`data`	No	Carrier, line type, LRN, and any requested cnam/spam/messaging fields
`risk`	No	Explainable spam/risk verdict: WHY the number is flagged (or not), with an honest confidence band. A clean verdict means "nothing found against it", never "verified safe".
`billed`	No	Whether this lookup was charged
`status`	No	success or error
`phone_number`	No	Normalized number

Schema Changelog

Changes observed during successful MCP inspections.

Changed1 schema field changedSep 6, 2026

addedOutput schema / properties / risk

Added value: +{
+  "additionalProperties": true,
+  "description": "Explainable spam/risk verdict: WHY the number is flagged (or not), with an honest confidence band. A clean verdict means \"nothing found against it\", never \"verified safe\".",
+  "properties": {
+    "confidence": {
+      "description": "How much weight the evidence actually carries",
+      "enum": [
+        "low",
+        "medium",
+        "high"
+      ],
+      "type": "string"
+    },
+    "confidence_note": {
+      "description": "One plain sentence explaining the band",
+      "type": "string"
+    },
+    "reasons": {
+      "description": "Individual pieces of evidence behind the verdict",
+      "items": {
+        "additionalProperties": true,
+        "properties": {
+          "code": {
+            "description": "provider_flag, ftc_complaints, complaint_category, community_reports, line_type_voip, recently_ported, no_complaints",
+            "type": "string"
+          },
+          "signal": {
+            "enum": [
+              "negative",
+              "positive",
+              "context"
+            ],
+            "type": "string"
+          },
+          "text": {
+            "description": "Human-readable evidence",
+            "type": "string"
+          },
+          "weight": {
+            "enum": [
+              "strong",
+              "moderate",
+              "weak"
+            ],
+            "type": "string"
+          }
+        },
+        "type": "object"
+      },
+      "type": "array"
+    },
+    "verdict": {
+      "description": "unknown = no reputation data was read for this number",
+      "enum": [
+        "scam",
+        "robocall",
+        "reported",
+        "clean",
+        "unknown"
+      ],
+      "type": "string"
+    }
+  },
+  "type": "object"
+}

First observedSep 5, 2026

TDQS

A4.5/5.0

Behavior4/5

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

Annotations already declare readOnlyHint and idempotentHint, and the description adds meaningful behavioral context: 'Always a fresh read of live numbering infrastructure — never cached carrier data.' This tells the agent the data is not stale and that each call reflects current numbering infrastructure, which is useful beyond the 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?

Two sentences with no filler. The core scope ('ONE North American phone number') and key outputs are front-loaded, and the freshness guarantee is a compact, high-value addition. Every part of the description earns its place.

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?

For a low-complexity tool with an output schema and strong annotations, the description is fully sufficient. It covers the purpose, scope, optional data products, and freshness behavior. There is no critical operational information missing that an agent would need to invoke this tool correctly.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters4/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 100%, so the parameters are already documented. The description adds value by explaining what the default data set contains ('current carrier of record, line type, LRN routing data, porting activation date') and clarifying what optional products mean (CNAM, spam reputation, messaging provider), which maps directly to the products enum values.

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 uses a specific, informative phrase: 'Live intelligence for ONE North American phone number,' and enumerates the data returned (carrier, line type, LRN, porting date, optional CNAM/spam/messaging). This clearly distinguishes it from the sibling bulk and spam-focused tools by emphasizing single-number lookup and the optional product mix.

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 establishes clear context: use for a single North American number when fresh, live carrier/routing data is needed, and optionally additional products. It does not explicitly name sibling alternatives like vri_bulk_lookup or vri_spam_check, but the 'ONE number' scoping and optional-product phrasing strongly imply the right usage without requiring exclusions.

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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