Skip to main content
Glama

interzoid_fullname_match_score

Destructive

Compare two individual/person names and receive a match score from 0-100 indicating similarity. Handles name order, nicknames, and abbreviations. Cost: $0.01 USDC via x402.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
fullname1YesFirst full name
fullname2YesSecond full name to compare

TDQS

A3.8/5.0
Behavior2/5

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

The description portrays a read-only operation (compare names, return score), but annotations set 'destructiveHint: true', suggesting possible side effects or state changes. This contradiction undermines transparency. Cost disclosure is helpful but not sufficient.

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 extremely concise: two sentences, no fluff. The first sentence defines the primary action and output, making it efficient for quick comprehension.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness4/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a simple comparison tool with only two parameters and no output schema, the description provides necessary context: similarity score range, handling of variations, and cost. Missing details about error handling or response format, but adequate given low complexity.

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?

The schema provides 100% coverage with descriptions for both parameters. The description adds useful context that the tool handles nicknames and abbreviations, enhancing understanding beyond raw schema.

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 it compares two names and returns a match score from 0-100, handling nicknames and abbreviations. It distinguishes from the sibling 'interzoid_fullname_match' by including 'score' in the name, implying a numeric output.

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

Usage Guidelines3/5

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

The description does not explicitly state when to use this tool vs alternatives like 'interzoid_fullname_match'. It mentions cost, which may imply usage considerations, but lacks direct guidance on tool selection.

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

Try in Browser

Glama MCP Gateway

Add one secure layer between your agents and this server.

TDQS

B3.4/5.0
Disambiguation4/5

Most tools target distinct data operations (matching, standardization, enrichment) with clear descriptions. Minor overlaps exist, e.g., address_match_advanced vs global_address_match, but descriptions differentiate them.

Naming Consistency5/5

All tools follow a consistent 'interzoid_descriptive_function' pattern in snake_case, making it easy to predict purpose from the name.

Tool Count3/5

58 tools is high for a single server, exceeding the typical 3-15 range. While each serves a specific data enrichment function, the quantity may overwhelm agents without clear categorization.

Completeness4/5

The tool surface covers a broad domain including address, company, person, and financial data. Minor gaps exist (e.g., no reverse IP lookup, limited social media coverage), but core data needs are well-addressed.