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calculate_summation

Calculate symbolic summations for finite and infinite series, returning LaTeX-formatted results with convergence conditions.

Instructions

    Calculate symbolic summation.

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    🆕 NOT AVAILABLE IN SYMPY-MCP!
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    Use cases:
    - Finite sums (Σ from n=1 to N)
    - Infinite series (Σ from n=1 to ∞)
    - Partition functions
    - Probability mass functions

    Args:
        expression: The summand (term being summed)
        index: Summation index variable
        lower: Lower bound (integer or symbol)
        upper: Upper bound (integer, symbol, or "oo" for infinity)

    Returns:
        Summation result with LaTeX

    Examples:
        # Finite sum: Σ k from k=1 to n
        calculate_summation("k", "k", "1", "n")
        → {"result": "n*(n+1)/2", ...}

        # Infinite geometric series: Σ r^n from n=0 to ∞
        calculate_summation("r**n", "n", "0", "oo")
        → {"result": "1/(1-r)", "condition": "|r| < 1"}

        # Partition function: Σ exp(-E_i/(k*T)) from i=0 to N
        calculate_summation("exp(-E*i/(k*T))", "i", "0", "N")
    

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
indexYes
lowerYes
upperYes
expressionYes

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Behavior4/5

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

No annotations are provided, so the description carries the full burden. It discloses return format (LaTeX result, plus condition for infinite series), and examples illustrate expected outputs including the convergence condition. It does not explicitly state read-only behavior or potential errors, but for a calculation tool this is largely implicit. The 'NOT AVAILABLE IN SYMPY-MCP!' warning is confusing but not misleading about the tool's core behavior.

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

Conciseness4/5

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

The description is well-structured with clear sections (Use cases, Args, Returns, Examples). However, the prominent 'NOT AVAILABLE IN SYMPY-MCP!' banner is extraneous and could confuse agents, and the use cases are somewhat verbose. The core description is efficient, but the banner reduces conciseness.

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

Completeness5/5

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

The description is comprehensive for a calculation tool: it lists use cases, defines all four parameters, explains the return format, and provides three worked examples with expected results. Even though an output schema exists, the description adds valuable context about conditions and conventions (e.g., using 'oo' for infinity), making it complete.

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

Parameters5/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The schema only provides parameter names with no descriptions. The description includes a dedicated Args section explaining each parameter ('expression: The summand (term being summed)', etc.), plus examples that show how to pass expressions like 'r**n' and 'oo' for infinity. This adds substantial meaning beyond the schema.

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

Purpose5/5

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

The description opens with 'Calculate symbolic summation', which is a specific verb+resource statement. It clearly distinguishes from siblings like calculate_limit and calculate_series by focusing on summation. Use cases (finite sums, infinite series, partition functions, PMFs) further clarify its scope.

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

Usage Guidelines4/5

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

The description provides a clear list of use cases (finite sums, infinite series, partition functions, probability mass functions), which tells the agent when to use this tool. It does not explicitly mention alternatives or when not to use it, but the use cases imply a targeted scope and the sibling tools are distinct enough to avoid confusion.

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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