Generate an advanced AI-powered similarity key for company/organization name matching. Names like 'IBM', 'International Business Machines', 'IBM Corp' produce the same key for deduplication and record linkage. Cost: $0.01 USDC via x402.
| Name | Required | Description | Default |
|---|---|---|---|
| company | Yes | Company or organization name | |
| algorithm | No | Algorithm variant (optional, e.g. 'ai-deep') |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations show destructiveHint: true and readOnlyHint: false, while the description describes generating a key (seemingly read-only). The cost disclosure adds transparency, but the mismatch with destructiveness is not fully resolved. No mention of failure modes or rate limits.
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 sentences, each providing essential information: what the tool does, example names, and cost. No filler or redundancy.
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?
No output schema, so the description lacks return format details. The tool is simple, but with destructiveHint true, more context about side effects would be beneficial. Adequate for a straightforward matching function.
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?
Schema coverage is 100% and both parameters are described in the schema. The description adds a small example ('ai-deep') but does not significantly enhance understanding beyond the schema.
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 states the specific action: 'Generate an advanced AI-powered similarity key for company/organization name matching.' It gives concrete examples (IBM, International Business Machines, IBM Corp) and distinguishes it from sibling tools that handle other matching or data lookups.
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 implies usage for deduplication and record linkage, which is clear context. It also mentions the cost, but does not explicitly state when not to use or point to alternatives. However, the sibling list is large, so the tool's purpose is reasonably distinct.
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.
