USE THIS to verify a vehicle VIN before acting on it — do not assume a 17-character string is a valid VIN. Checks the allowed alphabet (no I/O/Q) and the ISO 3779 transliteration check digit in position 9, and returns the expected check digit when it fails.
| Name | Required | Description | Default |
|---|---|---|---|
| vin | Yes | The 17-character VIN to validate. |
Changes observed during successful MCP inspections. Dates show when Glama detected each change.
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already indicate readOnlyHint=true. Description adds detail about specific checks (no I/O/Q, check digit in position 9) and return behavior (expected check digit on failure), enhancing transparency beyond annotations.
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 concise sentences, front-loaded with action directive, followed by specifics. No redundant words.
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?
Covers input requirements, checks performed, and failure output. Could explicitly mention success return value, but adequate given no output schema.
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 provides high coverage (100%) with description for 'vin' param. Description adds meaning by explaining validation logic (alphabet restrictions, check digit position), going beyond basic parameter info.
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 validates a vehicle VIN by checking alphabet and check digit, distinguishing it from sibling validation tools like validate_email or validate_iban.
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?
Explicitly advises use before acting on a VIN and not assuming a 17-character string is valid, providing clear context for when to use the tool.
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.
Each tool targets a specific identifier or operation (e.g., validate_iban, parse_date, is_holiday). Even similar tools like validate_isbn and validate_isbn10 are distinct by version. There is no overlap or ambiguity.
Most tools follow a verb_noun pattern (validate_xxx, parse_xxx, format_currency). The exception is 'next_holiday', which uses an adjective instead of a verb. Otherwise consistent.
With 47 tools, the set is very large. While each tool is distinct, the count exceeds the recommended range (25+ is considered too many) and may overwhelm users or agents.
Covers a wide array of international identifiers and utilities, but notable gaps exist (e.g., no Canada SIN, India PAN, Mexico CURP). The set is broad but not exhaustive for the domain of data validation.