Generate a single combined AI-powered similarity key from a full name plus address. Records with the same combined key share both a similar address and a similar individual name. Useful for high-precision household/contact-level deduplication. Cost: $0.01 USDC via x402.
| Name | Required | Description | Default |
|---|---|---|---|
| address | Yes | Full street address (US or international) | |
| fullname | Yes | Full individual name |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The description claims to 'generate a similarity key,' implying a non-destructive read operation. However, the annotations set destructiveHint to true, creating a contradiction. The description does not clarify any destructive behavior, nor does it explain side effects, authorization needs, or error conditions. The cost information is useful but insufficient.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
Three concise sentences: purpose, outcome, and cost. No redundant wording. The key action and use case are front-loaded, making it easy for an AI agent to quickly grasp the tool's function.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
With 2 simple parameters and no output schema, the description adequately explains the output (a similarity key) and the use case. It omits details like return format or error handling, but given the tool's simplicity, the description is largely complete.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema covers 100% of the 2 parameters with descriptions. The description adds minimal extra meaning: 'US or international' for address and 'Full individual name' for fullname. This provides slight context beyond the schema, meeting the baseline expected for high coverage.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states it generates a combined similarity key from full name and address for high-precision household/contact-level deduplication. This is a specific verb-resource pair that distinguishes it from sibling tools like interzoid_fullname_match or interzoid_address_match_advanced.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description explicitly mentions the use case: 'high-precision household/contact-level deduplication.' It does not mention when not to use or alternative tools, but the context is clear and appropriate for the intended purpose.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Add one secure layer between your agents and this server.
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.
All tools follow a consistent 'interzoid_descriptive_function' pattern in snake_case, making it easy to predict purpose from the name.
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.
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.
