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get_jyutping

Convert Cantonese text to Jyutping romanization. Get pronunciation for each character with tone numbers.

Instructions

Convert Cantonese text to Jyutping romanization.

Returns the Jyutping pronunciation for each character in the input text. Jyutping is the standard romanization system for Cantonese, where each syllable ends with a tone number from 1-6 (with 7-9 for entering tones).

Args: text: Cantonese text to convert (Traditional or Simplified Chinese)

Returns: Dictionary with the original text and a list of character-pronunciation pairs

Example: Input: "你好" Output: {"text": "你好", "jyutping": [["你", "nei5"], ["好", "hou2"]]}

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
textYes
Behavior3/5

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

No annotations provided, so the description carries full burden. It discloses the return format and example, but does not address error handling, character coverage limitations, or performance. For a simple read-like tool, this is adequate but not thorough.

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 concise with no wasted words. It starts with the main action, followed by explanation and example. Every sentence adds value, and the structure is clear.

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 the tool's simplicity (1 parameter, no output schema), the description is nearly complete. It covers purpose, parameter meaning, return format, and example. Minor gaps like error behavior or edge cases are acceptable for such a straightforward tool.

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?

The input schema has 0% description coverage for the only parameter 'text'. The description adds meaning by specifying 'Cantonese text to convert (Traditional or Simplified Chinese)', which clarifies the input beyond the schema's bare type definition.

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 purpose: 'Convert Cantonese text to Jyutping romanization.' It explains what Jyutping is and provides an illustrative example. The tool is distinct from siblings (get_rhyming_characters, get_tone_pattern) as it covers conversion to romanization.

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

Usage Guidelines2/5

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

No guidance on when to use this tool versus alternatives. While the purpose is clear, there is no explicit when-to-use or when-not-to-use context, nor mention of prerequisites or exclusions.

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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