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qinisolabs

localecheck

parse_date

Parse human-written dates into ISO 8601 by specifying locale (en-GB or en-US) to resolve ambiguous formats and validate impossible dates.

Instructions

Convert a human-written date into ISO 8601 (YYYY-MM-DD). USE THIS whenever you need to interpret a date a person typed — especially ambiguous numeric dates like 03/04/2025, which mean different things in the UK (day-first) vs US (month-first) — before storing, scheduling, or acting on it. Pass locale 'en-GB' or 'en-US'. Returns valid:false for impossible dates.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
inputYes
localeNoen-GB
Behavior3/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

No annotations are provided, so the description carries the burden. It discloses that the tool returns 'valid:false for impossible dates,' but does not describe the full return format or behavior on success (e.g., whether it returns the parsed ISO string). This is a minor gap.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is three sentences with no waste. The first sentence states the core purpose, the second gives usage guidance, and the third provides a behavioral detail. It is front-loaded and efficient.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness4/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given two parameters, no output schema, and no annotations, the description is largely complete. It covers purpose, usage, and a return indicator. However, it does not explicitly state the output format on success (implied by the first sentence) or any prerequisites.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters4/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 0%, so the description must add meaning. It explains the 'input' parameter as a human-written date and 'locale' as 'en-GB' or 'en-US', with an example of ambiguity. It adds value beyond the schema, though it could explicitly state the default locale and optionality.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool's action: 'Convert a human-written date into ISO 8601 (YYYY-MM-DD).' It specifies the input and output format, and the purpose is distinct from sibling tools like format_currency or parse_address.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines4/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description explicitly advises when to use ('USE THIS whenever you need to interpret a date a person typed') and highlights ambiguity with numeric dates, including locale sensitivity. It does not explicitly exclude usage scenarios, but the guidance is clear for the primary use case.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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