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 describes the tool as a scanning operation that returns analytical outputs, implying it's a read-only, non-destructive process, but does not detail error handling, performance characteristics, or any side effects. This is adequate for a basic read tool but lacks depth in behavioral traits.

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 front-loaded with the core action and outputs in the first sentence, followed by a context sentence. It is efficient with two sentences that directly convey purpose and use case, though the second sentence could be slightly more concise by integrating the context more tightly.

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 (scanning and analysis), no annotations, no output schema, and 100% schema coverage, the description is minimally complete. It covers what the tool does and its intended use but lacks details on output format, error cases, or integration with sibling tools, leaving some gaps for an AI agent to infer behavior.

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 schema description coverage is 100%, with both parameters ('inputFile' and 'outputReport') clearly documented in the schema. The description does not add any parameter-specific details beyond what the schema provides, such as file format expectations or report structure, so it meets the baseline for high schema coverage without extra value.

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 ('Scan a markdown file for all LaTeX math') and resource ('markdown file'), distinguishing it from sibling tools like 'validate_equations' or 'render_markdown_with_math' by focusing on analysis rather than validation or rendering. It explicitly lists the outputs (equation inventory, symbol frequency table, etc.), making the purpose distinct and comprehensive.

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 implies usage for 'maintaining consistency in scientific papers,' suggesting it's for quality control in academic writing. However, it lacks explicit guidance on when to use this tool versus alternatives like 'validate_equations' or 'render_markdown_with_math,' and does not specify prerequisites or exclusions, leaving some ambiguity in context.

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