USE THIS to interpret a human-written date into ISO 8601 (YYYY-MM-DD), especially ambiguous numeric dates like 03/04/2025 which mean different things in the UK (day-first) vs US (month-first). Pass locale 'en-GB' or 'en-US'. Returns valid:false for impossible dates.
| Name | Required | Description | Default |
|---|---|---|---|
| input | Yes | The date text to parse. | |
| locale | No | 'en-GB' (day-first) or 'en-US' (month-first); default en-GB. |
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?
The annotations already indicate readOnlyHint=true, so the description doesn't need to reiterate. It adds value by mentioning locale-dependent behavior and the 'valid:false' return for impossible dates, though it doesn't detail successful return structure.
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?
The description is two sentences with no unnecessary words. It front-loads the primary purpose and includes critical usage notes efficiently.
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?
Given the two parameters and full schema coverage, the description adequately covers the tool's behavior. It mentions return values for invalid dates but could be more explicit about successful return format. However, without an output schema, it provides reasonable context.
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 descriptions for both parameters. The description adds context about locale values ('en-GB' vs 'en-US') and their impact, and explains the purpose of the 'input' parameter for ambiguous dates, going 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 clearly states the tool parses human-written dates into ISO 8601 format, specifically highlighting its use for ambiguous numeric dates. It distinguishes itself from sibling validation tools by focusing on date interpretation.
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 says 'USE THIS' and provides context for when to use it, especially for ambiguous dates. It lacks explicit when-not-to-use or alternative tools, but the sibling tools are mostly validators, so the guidance is sufficient.
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.