Symbolic Algebra 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. It discloses key behavioral traits: it solves equations algebraically, returns LaTeX strings or error messages, and has a default domain. However, it doesn't mention computational complexity, limitations on equation types, whether it modifies state, or error handling specifics beyond 'issues occur'.

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 clear sections (purpose, Args, Returns) and front-loaded with the core functionality. Every sentence adds value, though the 'Returns' section could be slightly more concise by combining the two sentences about LaTeX strings and errors.

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 (3 parameters, algebraic solving), no annotations, and no output schema, the description is reasonably complete. It covers purpose, parameters, return format, and default behavior. However, it lacks details on error conditions, performance characteristics, or examples that would make it fully comprehensive for an AI agent.

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 description adds substantial meaning beyond the input schema, which has 0% description coverage. It explains that expr_key refers to 'previously introduced' expressions, solve_for_var_name is for 'previously introduced' variables, and domain has four specific options with their meanings and a default. This fully compensates for the schema's lack of descriptions.

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 with specific verbs ('solves an equation algebraically') and resources ('expression = 0', 'for a given variable'). It distinguishes itself from sibling tools like solve_linear_system and solve_nonlinear_system by focusing on algebraic solutions of single equations rather than systems of equations.

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 context by specifying it solves 'expression = 0' and mentions previously introduced expressions/variables, suggesting it works within a session context. However, it doesn't explicitly state when to use this tool versus alternatives like solve_linear_system or differentiate_expression, nor does it provide exclusion criteria.

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