USE THIS to verify the format and checksum of an Indian Aadhaar number — never assume 12 digits are valid. Checks the Verhoeff check digit and the leading-digit rule. Validates structure only; does NOT look the number up.
| Name | Required | Description | Default |
|---|---|---|---|
| aadhaar | Yes | The 12-digit Aadhaar number (spaces ignored). |
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 provide readOnlyHint=true, and description adds that it validates structure only and does not perform lookup. No contradictions. The behavioral constraints are fully disclosed.
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 with zero waste. Information is front-loaded with imperative instruction. Every phrase adds value.
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?
For a validation tool with one parameter and no output schema, the description fully covers what it does (format, checksum) and explicitly states what it does not do (lookup). It is complete for the tool's complexity.
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% with one parameter described. Description adds important detail 'spaces ignored' and mentions Verhoeff check digit and leading-digit rule, enriching the schema with algorithmic context.
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 verifies format and checksum of an Indian Aadhaar number, and distinguishes from other validation tools by specifying it does not look up the number. It uses specific verb 'verify' and resource 'Aadhaar number'.
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?
Description begins with 'USE THIS to...', providing clear context. It warns against assuming validity of 12 digits, but does not explicitly state when not to use or mention alternatives among sibling tools. However, given the sibling set is all validation tools, the usage context is clear.
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.