braille_math_nemethConverts a linear math expression (e.g. x^2+1=5) to Nemeth-code braille cells. Note the surrounding engine is pronunciation-based, NOT an official national braille code. Best for linear expressions; complex 2D layouts need reviewer post-processing. 한국어: 한 줄 수식을 네메스 점자로 변환합니다.
| Name | Required | Description | Default |
|---|---|---|---|
| text | Yes | Math expression, e.g. x^2+1=5 |
Changes observed during successful MCP inspections.
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Adds real context beyond the annotations: the underlying engine is pronunciation-based and NOT an official national braille code, which warns the agent about output fidelity. Annotations already cover the safe/idempotent/closed-world profile, so this caveat is the meaningful addition. It still does not describe output shape or failure modes.
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?
Front-loaded with the verb and scope, and the caveat is placed before the scope guidance. The Korean translation restates the first sentence rather than adding value, a small redundancy.
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 single-parameter, annotation-covered conversion tool with no output schema, the description covers purpose, input example, scope limit, and fidelity caveat. It leaves the exact return representation slightly implicit, but nothing critical to a correct invocation is missing.
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?
Only one parameter and schema coverage is 100%, so the schema already documents `text` fully, including the same example used in the description. The description adds no syntax, formatting, or constraint detail (e.g. what counts as 'linear') 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?
States a specific verb and resource: converts a linear math expression to Nemeth-code braille cells, with a concrete input example. It scopes itself to linear expressions, which implicitly separates it from the generic braille_convert sibling, but it never names that sibling explicitly.
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?
"Best for linear expressions; complex 2D layouts need reviewer post-processing" gives a clear use condition plus an exclusion. It stops short of pointing the agent at an alternative tool for the excluded case, so it is not a full 5.
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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