Asterwise

Business Name Analysis

asterwise_get_business_name_analysis

Read-onlyIdempotent

Reduces a business name to Expression and root digits and returns thematic suitability lists plus a harmony score. Uses the name only; no founder birth date is involved.

WORKFLOW: BEFORE: None — standalone. AFTER: asterwise_get_name_correction — if the entity is a person, not a brand.

INPUT CONTRACT: business_name (required): special characters and digits are acceptable; reduction strips non-letters per upstream rules. date: not used; omit it (accepted only so older calls keep working).

DO NOT CONFUSE WITH: asterwise_get_name_correction — personal spelling alternatives, not corporate Expression scoring. asterwise_check_mobile_number — numeric line analysis, not brand letters.

Full output and error contract: https://docs.asterwise.com/mcp/tools/get-business-name-analysis/

Input Schema

TableJSON Schema

Name	Required	Description	Default
`date`	No	Not used: the analysis depends only on the business name. Omit it; it is accepted only so older calls keep working.
`business_name`	Yes	Business or brand name to analyse.
`response_format`	No	Output format: 'markdown' (default) for a readable report, or 'json' for the raw structured payload.	markdown

Output Schema

TableJSON Schema

Name	Required	Description	Default
`result`	Yes

Schema Changelog

Changes observed during successful MCP inspections.

Changed5 schema fields changedOct 6, 2026

addedInput schema / properties / date / anyOf

Added value: +[
+  {
+    "type": "string"
+  },
+  {
+    "type": "null"
+  }
+]

addedInput schema / properties / date / default
```
Added value: +null
```

changedInput schema / properties / date / description

Previous value: -"Date in YYYY-MM-DD format."New value: +"Not used: the analysis depends only on the business name. Omit it; it is accepted only so older calls keep working."

removedInput schema / properties / date / type
```
Removed value: -"string"
```

changedInput schema / required

Previous value: -[
-  "business_name",
-  "date"
-]New value: +[
+  "business_name"
+]

Changed1 schema field changedSep 7, 2026

changedInput schema / properties / date / description

Previous value: -"Date in YYYY-MM-DD format. Defaults to today when omitted."New value: +"Date in YYYY-MM-DD format."

Changed3 schema fields changedSep 5, 2026

addedInput schema / properties / business_name / description
```
Added value: +"Business or brand name to analyse."
```

addedInput schema / properties / date / description

Added value: +"Date in YYYY-MM-DD format. Defaults to today when omitted."

addedInput schema / properties / response_format / description

Added value: +"Output format: 'markdown' (default) for a readable report, or 'json' for the raw structured payload."

Changed2 schema fields changedSep 4, 2026

addedInput schema / properties / response_format / default
```
Added value: +"markdown"
```

changedInput schema / required

Previous value: -[
-  "business_name",
-  "date",
-  "response_format"
-]New value: +[
+  "business_name",
+  "date"
+]

First observedApr 22, 2026

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/destructiveHint=false, so the safety profile is covered. The description adds real behavioral context beyond that: the computation uses the name only and no birth date, the date param is inert, and reduction strips non-letters per upstream rules. It stops short of discussing determinism guarantees or output shape, but the output schema covers the latter.

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?

Front-loaded one-line summary followed by labeled sections (WORKFLOW, INPUT CONTRACT, DO NOT CONFUSE WITH, doc link). Every sentence carries routing or contract information; nothing is padding.

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?

An output schema exists, so return values needn't be restated. Given the tool is a standalone, single-input computation, the description covers purpose, disambiguation, input handling, and workflow transitions, leaving no gap an agent would need filled before calling it.

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%, which sets a baseline of 3, but the description adds meaning the schema lacks — that special characters and digits are acceptable in business_name and that non-letters are stripped during reduction. The date parameter's inert status is clarified in both places.

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?

States a specific verb+resource ('Reduces a business name to Expression and root digits') and names the actual outputs (thematic suitability lists, harmony score). The DO NOT CONFUSE WITH block explicitly separates it from asterwise_get_name_correction and asterwise_check_mobile_number, so an agent can route 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 block gives explicit before/after conditions ('BEFORE: None — standalone', 'AFTER: get_name_correction — if the entity is a person, not a brand') and the DO NOT CONFUSE WITH block names the two most confusable siblings with the discriminating condition for each.

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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