Standardize an organization name to its canonical form. Normalizes abbreviations, suffixes, and formatting (e.g. 'b.o.a.' -> 'Bank of America'). Cost: $0.01 USDC via x402.
| Name | Required | Description | Default |
|---|---|---|---|
| org | Yes | Organization name to standardize |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The description says 'Standardize' which implies a non-destructive transformation, but annotations mark destructiveHint=true and readOnlyHint=false. The mention of cost via x402 hints at mutability, but no details on side effects. This contradiction reduces transparency.
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?
Two sentences effectively convey the purpose and an example. No wasted words, front-loaded with the core action.
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?
The description explains what the tool does and gives a cost hint, but with no output schema, it omits what the return value looks like (e.g., is it just the standardized string?). This is a notable gap for a simple tool.
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 lone parameter 'org' is described in the schema, but the tool description adds semantic context: it normalizes abbreviations, suffixes, and formatting with an example. This adds value beyond the schema's bare parameter description.
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 standardizes organization names to canonical form, with normalization of abbreviations and suffixes. The example 'b.o.a.' -> 'Bank of America' demonstrates the behavior. This distinguishes it from siblings that handle addresses, companies, or other entities.
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?
No guidance on when to use this vs other org-related tools like interzoid_company_match_advanced or interzoid_org_match_score. It mentions cost but not usage context or alternatives.
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.
