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combsimp_expression

Simplify combinatorial expressions with factorials, binomial coefficients, and permutations. Get simplified results in LaTeX for Taylor series, probability, and statistical formulas.

Instructions

    Simplify combinatorial expressions (factorials, binomials).

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    🆕 PHASE 1 - NOT IN SYMPY-MCP OR NSFORGE v0.2.3!
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    Simplifies expressions involving:
    - Factorials: n!/(n-k)!
    - Binomial coefficients: C(n,k)
    - Permutations: P(n,k)

    Use cases:
    - Taylor series coefficients
    - Probability calculations
    - Statistical formulas
    - Series expansions

    Args:
        expression: Expression with factorials/binomials

    Returns:
        Simplified expression with LaTeX

    Examples:
        # Falling factorial
        combsimp_expression("factorial(n)/factorial(n - 3)")
        → {"result": "n*(n - 1)*(n - 2)", ...}

        # Binomial identity
        combsimp_expression("binomial(n, k) * factorial(k)")
        → {"result": "factorial(n)/factorial(n - k)", ...}

        # Taylor coefficient
        combsimp_expression("x**n / factorial(n)")
        → Standard form for Taylor series

        # Rising factorial
        combsimp_expression("rf(x, 3)")
        → {"result": "x*(x + 1)*(x + 2)", ...}
    

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
expressionYes

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Behavior4/5

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

With no annotations, the description carries the full burden. It clarifies the operation is a simplification (non-mutating function), specifies the return format (simplified expression with LaTeX), and gives identity examples that illustrate the transformation behavior. It does not discuss error handling or edge cases, but for a pure symbolic simplification tool this is adequate.

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 organized into purpose, use cases, args, returns, and examples, making it easy to scan. The banner and ASCII decoration add visual noise but do not obscure the essential information. It is longer than necessary but every functional section earns its place.

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 tool has a single parameter, an output schema exists, and the description covers what the tool does, when to use it, valid input examples, and return format. For a task of this complexity, the description is complete.

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

Parameters4/5

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

Schema coverage is 0%, and the description's 'Args: expression' line adds little beyond the field name. However, the examples provide concrete syntax for valid expressions (factorial(n)/factorial(n-3), binomial(n,k), rf(x,3)), which significantly compensates for the sparse 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 a clear verb+resource: 'Simplify combinatorial expressions (factorials, binomials).' It enumerates exactly what constructs are simplified and provides concrete examples that distinguish it from sibling simplification tools like trigsimp_expression or powsimp_expression.

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?

Provides explicit use cases (Taylor series, probability, statistics, series expansions) that signal appropriate contexts. However, it does not explicitly name alternatives or state when NOT to use it, so it falls short of the highest standard.

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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