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calculate_limit

Calculate the limit of a mathematical expression as a variable approaches a specified point, with support for one-sided and two-sided limits to analyze steady-state, boundary, and asymptotic behavior.

Instructions

    Calculate the limit of an expression.

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    🆕 NOT AVAILABLE IN SYMPY-MCP!
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    Use cases:
    - Steady-state analysis (t → ∞)
    - Boundary behavior (x → 0)
    - Asymptotic behavior
    - L'Hôpital's rule situations

    Args:
        expression: The expression to take limit of
        variable: The variable approaching the point
        point: The point to approach (can be "oo", "-oo", "0", "1", etc.)
        direction: Direction of approach
            - "+-" or "": Two-sided (default)
            - "+": From the right (x → 0⁺)
            - "-": From the left (x → 0⁻)

    Returns:
        Limit result with LaTeX

    Examples:
        # Steady-state concentration
        calculate_limit("C0 * exp(-k*t)", "t", "oo")
        → {"result": "0", "latex": "0"}

        # Indeterminate form (0/0)
        calculate_limit("sin(x)/x", "x", "0")
        → {"result": "1", "latex": "1"}

        # One-sided limit
        calculate_limit("1/x", "x", "0", direction="+")
        → {"result": "oo", "latex": "\infty"}
    

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
pointYes
variableYes
directionNo+-
expressionYes

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Behavior3/5

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

With no annotations, the description carries the burden of behavioral disclosure. It explains direction semantics, return format ('Limit result with LaTeX'), and provides examples of one-sided limits. However, it does not explicitly state that this is a read-only operation, that it may fail on unsupported expressions, or any other behavioral caveats beyond the note about SymPy-MCP availability.

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 sections for use cases, args, returns, and examples, but the large 'NOT AVAILABLE IN SYMPY-MCP!' banner is a distraction and adds noise. The core content is concise and front-loaded, but the banner makes it feel less polished.

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?

For a symbolic math tool, the description is complete: it covers purpose, parameters, return format, and provides three concrete examples including one-sided limits. The output schema is already indicated by the examples and 'Returns' line, so no further return-value explanation is needed.

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?

Schema description coverage is 0%, so the description must compensate. It does so thoroughly with an 'Args:' section that explains each parameter (expression, variable, point, direction) including allowed values for direction and examples. This fully addresses the otherwise bare 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 clearly states 'Calculate the limit of an expression' with specific use cases that distinguish it from sibling tools like calculate_series and calculate_summation. The verb 'calculate' and resource 'limit' are specific, and the examples further clarify the purpose.

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 clear use cases (steady-state analysis, boundary behavior, asymptotic behavior, L'Hôpital's rule) which indicate when to use the tool. However, it does not explicitly mention alternatives or list exclusions, so it falls slightly short of a 5.

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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