UpMath MCP Server

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 effectively describes key behaviors: rendering markdown to HTML, using KaTeX for standard math and UpMath API for TikZ/special packages, and handling various markdown elements. However, it lacks details on performance implications (e.g., speed differences), error handling, or output specifics, leaving some behavioral aspects unclear.

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 appropriately sized and front-loaded, starting with the core purpose and key features (LaTeX rendering, KaTeX/UpMath usage). Every sentence adds value without redundancy, efficiently covering the tool's functionality in a compact format with zero waste.

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 complexity of rendering markdown with LaTeX math, no annotations, and no output schema, the description is moderately complete. It covers the main purpose and behavioral traits but lacks details on output format, error cases, or dependencies, which could be important for an AI agent to use it correctly in varied contexts.

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 description coverage is 100%, so the schema already documents all parameters thoroughly. The description adds minimal value beyond the schema by implying the tool processes markdown files with LaTeX, but it does not provide additional semantics for parameters like inputFile or outputFile. Baseline 3 is appropriate as the schema does the heavy lifting.

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 specific action ('Render a full markdown paper') and resource ('to a publication-ready HTML file'), distinguishing it from siblings like render_equation or render_markdown_with_math by emphasizing full paper rendering with LaTeX math support. It explicitly mentions handling various markdown elements (headings, bold, lists, etc.), which further clarifies its comprehensive scope.

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 provides clear context for when to use this tool (rendering markdown papers with LaTeX math to HTML) and implies alternatives by noting the fallback to UpMath API for special cases, but it does not explicitly name sibling tools like render_markdown_with_math or specify when to choose this over them. It offers some guidance on math rendering options but lacks explicit when-not-to-use statements.

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