get_tone_pattern

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

With no annotations provided, the description carries the full burden of behavioral disclosure. It details the tone grouping algorithms for both systems, the return structure (text, system, pattern, breakdown), and includes an example. It does not discuss error handling, performance, or limitations, but for a straightforward analysis tool, the transparency is adequate.

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 well-structured with sections for purpose, system explanations, args, returns, and example. It is slightly lengthy but each section is justified. The bullet points for tone groupings are clear. Minor redundancy (e.g., repeating 'the X system uses different digits but same groupings') could be trimmed.

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 tool's moderate complexity (2 parameters, no output schema), the description provides comprehensive information: input format, system choices with rationale, output structure, and a concrete example. It covers all necessary aspects for correct invocation and interpretation of results.

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?

The input schema has 0% description coverage, but the description compensates fully. It explains both parameters: 'text' as Cantonese text to analyze, and 'system' as an enum with detailed explanations of each option (1056 and 0243), including the tone groupings. The example further clarifies usage. This adds significant value 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's purpose: analyzing tonal patterns of Cantonese text for lyrics writing. It specifies the verb ('analyze'), resource ('tonal pattern'), and domain ('Cantonese lyrics writing'). It distinguishes from siblings like get_jyutping (romanization) and get_rhyming_characters (rhyming) by focusing on tone mapping systems.

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 implicitly provides usage context by explaining the two tonal classification systems (1056 and 0243) and their relevance to Cantonese lyrics. However, it does not explicitly state when to use this tool versus alternatives like get_jyutping or get_rhyming_characters, leaving the differentiation to the user's understanding of the tool's purpose.

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