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nbiish
by nbiish

limit

Calculate the limit of a function as it approaches a specific value to analyze mathematical behavior and continuity.

Instructions

Calculate the limit of a function as it approaches a value

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
expressionYesFunction to evaluate limit
variableYesVariable approaching the limit
approachYesValue the variable approaches

Implementation Reference

  • The handler function passed to ai.defineTool, which destructures inputs and calls the findLimit helper.
    async ({ expression, variable, approach }) => {
      return findLimit(expression, variable, approach);
    }
  • Zod schemas defining the input parameters (expression, variable, approach) and output (number or string).
    inputSchema: z.object({
      expression: z.string().describe('Function to evaluate limit'),
      variable: z.string().describe('Variable approaching the limit'),
      approach: z.number().describe('Value the variable approaches')
    }),
    outputSchema: z.union([z.number(), z.string()]),
  • index.js:324-338 (registration)
    ai.defineTool call that registers the 'limit' tool with name, description, schema, and handler function.
    ai.defineTool(
      {
        name: 'limit',
        description: 'Calculate the limit of a function as it approaches a value',
        inputSchema: z.object({
          expression: z.string().describe('Function to evaluate limit'),
          variable: z.string().describe('Variable approaching the limit'),
          approach: z.number().describe('Value the variable approaches')
        }),
        outputSchema: z.union([z.number(), z.string()]),
      },
      async ({ expression, variable, approach }) => {
        return findLimit(expression, variable, approach);
      }
    );
  • Supporting function that parses the math expression, evaluates it from left and right of the approach value using mathjs, averages if convergent within epsilon, else returns message or error.
    const findLimit = (expr, variable, approach) => {
      try {
        const node = math.parse(expr);
        const scope = {};
        const epsilon = 1e-10;
        
        // Evaluate near the approach point
        scope[variable] = approach + epsilon;
        const rightLimit = math.evaluate(node, scope);
        
        scope[variable] = approach - epsilon;
        const leftLimit = math.evaluate(node, scope);
        
        // Check if limits from both sides are approximately equal
        if (Math.abs(rightLimit - leftLimit) < epsilon) {
          return (rightLimit + leftLimit) / 2;
        }
        
        return 'Limit does not exist';
      } catch (e) {
        return `Error: ${e.message}`;
      }
    };
Behavior2/5

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

No annotations are provided, so the description carries full burden. It states what the tool does but doesn't disclose behavioral traits like error handling (e.g., for undefined limits), computational complexity, or output format. For a mathematical tool with no annotation coverage, this leaves significant gaps in understanding how it behaves.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is a single, efficient sentence that directly states the tool's purpose without any wasted words. It's appropriately sized and front-loaded, making it easy to understand at a glance.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness2/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the complexity of mathematical limit calculation and the absence of both annotations and an output schema, the description is insufficient. It doesn't explain what the tool returns (e.g., a numeric value, symbolic expression, or error), how it handles edge cases, or any mathematical assumptions. This leaves the agent with incomplete context for effective use.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

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 three parameters thoroughly. The description doesn't add any parameter-specific information beyond what's in the schema, such as format examples or constraints. Baseline 3 is appropriate when the schema does the heavy lifting.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool's purpose as 'Calculate the limit of a function as it approaches a value', which is a specific mathematical operation. It distinguishes itself from siblings like 'derivative' or 'integral' by focusing on limits, though it doesn't explicitly contrast with them in the description text.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines2/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description provides no guidance on when to use this tool versus alternatives. With siblings like 'solve' or 'derivative' that might handle related mathematical problems, there's no indication of when limit calculation is specifically appropriate or what prerequisites might be needed.

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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