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asterwise

Asterwise

Official

Mobile Number Check

asterwise_check_mobile_number
Read-onlyIdempotent

Analyze a mobile number with the owner's name and birth date to produce numerology harmonic scoring and interpretive insights.

Instructions

Digit-strips a mobile string (keeping country code digits), reduces it with the owner's name and birth date, and returns harmonic scoring plus interpretive copy.

WORKFLOW: BEFORE: RECOMMENDED — asterwise_get_numerology_profile — anchor Life Path before judging the line. AFTER: None.

INPUT CONTRACT: Formatting noise is ignored; only digits contribute. Country code digits are included in the reduction sum.

DO NOT CONFUSE WITH: asterwise_check_vehicle_number — plate digit rules, not SIM numbering. asterwise_get_business_name_analysis — letter Expression scan, not phone roots.

Full output and error contract: https://docs.asterwise.com/mcp/tools/check-mobile-number/

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
dateYesDate in YYYY-MM-DD format. Defaults to today when omitted.
nameYesPerson's full name as commonly written; letters are converted to numerology values.
mobile_numberYesMobile number to analyse; digits only, country code optional.
response_formatNoOutput format: 'markdown' (default) for a readable report, or 'json' for the raw structured payload.markdown

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes

Schema Changelog

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

  1. First observedv0.1.0

TDQS

A4.7/5.0
Behavior4/5

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

Annotations already declare readOnlyHint, idempotentHint, and destructiveHint, so the safety profile is covered. The description adds useful behavioral detail beyond annotations: formatting noise is ignored, only digits contribute, country code digits are included in the reduction, and the output is harmonic scoring plus interpretive copy. It does not mention auth or rate limits, but the annotations cover the main safety concerns.

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 well-structured with WORKFLOW, INPUT CONTRACT, DO NOT CONFUSE WITH, and a docs link, and every section earns its place. The core behavior is front-loaded in the first sentence, and the remaining sections are compact and scannable.

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 output schema, annotations, and 100% schema coverage, the description is complete enough for correct invocation. It covers the workflow, exclusions, input contract, and points to a full output and error contract URL, so nothing critical is missing.

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 description coverage is 100%, so the baseline is 3. The description adds meaningful semantics for mobile_number by clarifying that formatting noise is ignored and country code digits are included in the reduction sum, which is not fully explicit in the schema. It also frames date as the birth date, though the schema already documents the format and 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 states a specific verb and resource: it digit-strips a mobile string, reduces it with the owner's name and birth date, and returns harmonic scoring plus interpretive copy. It also explicitly names sibling tools it is not, such as asterwise_check_vehicle_number and asterwise_get_business_name_analysis, so an agent can distinguish it without opening schemas.

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

Usage Guidelines5/5

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

The WORKFLOW section gives an explicit recommended predecessor (asterwise_get_numerology_profile) and states AFTER: None. The DO NOT CONFUSE WITH section explicitly names alternatives and the conditions that separate them, such as 'plate digit rules, not SIM numbering' and 'letter Expression scan, not phone roots.'

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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