sympy

sympy is a skill for Claude Code, Codex from magic3007/dotfiles. It costs 50 tokens per session (3,961 once invoked), scanned A, a copy of sympy, MIT.

A Python library for doing exact mathematics with symbols instead of rounded decimal numbers. It covers algebra, calculus, equation solving, symbolic matrices, physics calculations, and turning formulas into usable code.

In plain words
What is it for?
Use it to simplify formulas, solve equations, calculate derivatives and integrals, work with symbolic linear algebra, and generate code or LaTeX from expressions.
Why use it?
It keeps expressions exact when numerical approximations could hide important details or introduce rounding errors.

Skill for Claude CodeCodex

Install

Getting it into your agent

One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.

agentmods
npx agentmods add skills/magic3007/dotfiles/sympy
Any agent
npx skills add magic3007/dotfiles --skill sympy
Clone the repo
git clone --depth 1 https://github.com/magic3007/dotfiles

Made for: Claude Code, Codex.

Wrote this? Show the measurements

A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.

agentmods badge for sympy

README.md
[![agentmods](https://agentmods.dev/badge/skills/magic3007/dotfiles/sympy.svg)](https://agentmods.dev/skills/magic3007/dotfiles/sympy)
Your own site
<a href="https://agentmods.dev/skills/magic3007/dotfiles/sympy"><img src="https://agentmods.dev/badge/skills/magic3007/dotfiles/sympy.svg" alt="Measured on agentmods" height="20"></a>
Per session 50 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 3,961 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. Scan, not verified.
Origin 92% copy Near-identical to another mod in the catalogue.
Token cost

What it costs to keep this loaded

Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.

ModelPer sessionOnce invoked
Fable 5.1 $0.00050 $0.03961
Opus 5 $0.00025 $0.01980
Sonnet 5 $0.00010 $0.00792
Haiku 4.5 $0.00005 $0.00396

Measured 2d ago against content hash 7e363438dc0d, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-05, from the pricing page.

Security

Grade A, and why

sympy scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 2d ago.

A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.

Nothing flagged

None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.

Origin

This is a copy

92% identical to sympy — 30 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.

claude/skills/scientific-agent-skills/skills/sympy/SKILL.md · 521 lines

How it starts

The opening of the file, as written. The whole thing — 521 lines — stays where its author put it; the contents beside it link to each section on GitHub.

SymPy - Symbolic Mathematics in Python

Overview

SymPy is a Python library for symbolic mathematics that enables exact computation using mathematical symbols rather than numerical approximations. This skill provides comprehensive guidance for performing symbolic algebra, calculus, linear algebra, equation solving, physics calculations, and code generation using SymPy.

Installation

Tested against SymPy 1.14.0 (stable; April 2025). Requires Python 3.9+.

# Install SymPy using uv
uv pip install "sympy>=1.14"

# Optional: for lambdify and plotting examples
uv pip install numpy scipy matplotlib

Check your version:

import sympy
print(sympy.__version__)

When to Use This Skill

Use this skill when:

  • Solving equations symbolically (algebraic, differential, systems of equations)
  • Performing calculus operations (derivatives, integrals, limits, series)
  • Manipulating and simplifying algebraic expressions
  • Working with matrices and linear algebra symbolically
  • Doing physics calculations (mechanics, quantum mechanics, vector analysis)
  • Number theory computations (primes, factorization, modular arithmetic)
  • Geometric calculations (2D/3D geometry, analytic geometry)
  • Converting mathematical expressions to executable code (Python, C, Fortran)
  • Generating LaTeX or other formatted mathematical output
  • Needing exact mathematical results (e.g., sqrt(2) not 1.414...)

Core Capabilities

1. Symbolic Computation Basics

Creating symbols and expressions:

from sympy import symbols, Symbol
x, y, z = symbols('x y z')
expr = x**2 + 2*x + 1

# With assumptions
x = symbols('x', real=True, positive=True)
n = symbols('n', integer=True)

Simplification and manipulation:

from sympy import simplify, expand, factor, cancel
simplify(sin(x)**2 + cos(x)**2)  # Returns 1
expand((x + 1)**3)  # x**3 + 3*x**2 + 3*x + 1
factor(x**2 - 1)    # (x - 1)*(x + 1)

For detailed basics: See references/core-capabilities.md

Read the full file on GitHub · 521 lines

Files

What ships with it

5 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.

Changes

What this file has done since we first saw it

Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.

  1. 2d ago First seen · 521 lines · 50 tokens per session scan A 7e363438dc0d

Subscribe to this mod's changes

sympy is a skill published in the GitHub repository magic3007/dotfiles (11 stars, last pushed yesterday), licensed MIT. It adds 50 tokens to every session and 3,961 once invoked, about $0.0003 per session on Opus 5. A static security scan graded it A with 0 findings. It is 92% identical to sympy, differing in 30 lines, and is treated as a copy.

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