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riemann_sum

Calculate the Riemann sum of a function to approximate definite integrals using left, right, midpoint, or trapezoid methods.

Instructions

Calculate the Riemann sum of a function using different methods

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
expressionYesFunction to integrate
variableYesVariable of integration
aYesLower limit of integration
bYesUpper limit of integration
nYesNumber of subintervals
methodNoMethod: left, right, midpoint, or trapezoidmidpoint

Implementation Reference

  • Handler function that receives tool inputs and delegates to the riemannSum helper function to compute the Riemann sum.
    async ({ expression, variable, a, b, n, method }) => {
      return riemannSum(expression, variable, a, b, n, method);
    }
  • Zod schemas defining the input parameters and numeric output for the riemann_sum tool.
    inputSchema: z.object({
      expression: z.string().describe('Function to integrate'),
      variable: z.string().describe('Variable of integration'),
      a: z.number().describe('Lower limit of integration'),
      b: z.number().describe('Upper limit of integration'),
      n: z.number().describe('Number of subintervals'),
      method: z.enum(['left', 'right', 'midpoint', 'trapezoid']).default('midpoint')
        .describe('Method: left, right, midpoint, or trapezoid')
    }),
    outputSchema: z.number(),
  • index.js:110-128 (registration)
    Complete registration of the 'riemann_sum' tool using Genkit's ai.defineTool, including name, description, schema, and handler.
    ai.defineTool(
      {
        name: 'riemann_sum',
        description: 'Calculate the Riemann sum of a function using different methods',
        inputSchema: z.object({
          expression: z.string().describe('Function to integrate'),
          variable: z.string().describe('Variable of integration'),
          a: z.number().describe('Lower limit of integration'),
          b: z.number().describe('Upper limit of integration'),
          n: z.number().describe('Number of subintervals'),
          method: z.enum(['left', 'right', 'midpoint', 'trapezoid']).default('midpoint')
            .describe('Method: left, right, midpoint, or trapezoid')
        }),
        outputSchema: z.number(),
      },
      async ({ expression, variable, a, b, n, method }) => {
        return riemannSum(expression, variable, a, b, n, method);
      }
    );
  • Core helper function that performs the actual Riemann sum calculation using mathjs for expression parsing and evaluation, supporting left, right, midpoint, and trapezoid methods.
    const riemannSum = (expr, variable, a, b, n, method = 'midpoint') => {
      try {
        const deltaX = (b - a) / n;
        let sum = 0;
        const node = math.parse(expr);
        const scope = {};
        
        if (method === 'left' || method === 'right') {
          const offset = method === 'right' ? 1 : 0;
          for (let i = 0; i < n; i++) {
            const x = a + (i + offset) * deltaX;
            scope[variable] = x;
            sum += math.evaluate(node, scope) * deltaX;
          }
        } else if (method === 'midpoint') {
          for (let i = 0; i < n; i++) {
            const x = a + (i + 0.5) * deltaX;
            scope[variable] = x;
            sum += math.evaluate(node, scope) * deltaX;
          }
        } else if (method === 'trapezoid') {
          for (let i = 0; i <= n; i++) {
            const x = a + i * deltaX;
            scope[variable] = x;
            const coef = (i === 0 || i === n) ? 0.5 : 1;
            sum += coef * math.evaluate(node, scope) * deltaX;
          }
        }
        
        return sum;
      } 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 the full burden of behavioral disclosure. It states the tool calculates Riemann sums but does not describe what the tool returns (e.g., numerical result, error handling), performance characteristics (e.g., computational limits), or side effects. For a tool with 6 parameters and no annotations, this lack of behavioral context is a significant gap.

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: 'Calculate the Riemann sum of a function using different methods.' It is front-loaded with the core purpose, has zero waste, and is appropriately sized for the tool's complexity, making it easy for an agent to parse quickly.

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 tool's complexity (6 parameters, mathematical calculations) and lack of annotations and output schema, the description is incomplete. It does not explain what the tool returns (e.g., a numerical approximation), error conditions, or limitations (e.g., handling of invalid inputs). For a tool performing numerical integration, more context is needed to guide 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?

The description adds no parameter semantics beyond what the input schema provides. The schema has 100% description coverage, with clear documentation for each parameter (e.g., 'Function to integrate' for 'expression', 'Method: left, right, midpoint, or trapezoid' for 'method'). Since the schema does the heavy lifting, the baseline score of 3 is appropriate, as the description does not compensate or add value.

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: 'Calculate the Riemann sum of a function using different methods.' It specifies the verb ('calculate') and resource ('Riemann sum of a function'), making the intent unambiguous. However, it does not explicitly distinguish this tool from sibling tools like 'integral' or 'darboux_sum', which might serve similar mathematical purposes.

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. It mentions 'different methods' but does not specify contexts, prerequisites, or exclusions. Given sibling tools like 'integral' and 'darboux_sum', there is no indication of when this tool is preferred, leaving the agent without usage direction.

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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