본문으로 건너뛰기
cccskills
무료GitHub에 공개

calculus-expert

Expert-level calculus knowledge. Use when working with limits, derivatives, integrals, multivariable calculus, vector calculus, differential equations, series, or optimization. Also use when the user mentions 'derivative', 'integral', 'limit', 'chain rule', 'gradient', 'divergence', 'curl', 'Taylor series', 'Fourier series', 'partial derivative', 'double integral', 'line integral', 'Stokes theorem', or 'Lagrange multipliers'.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

실행 점수 미검증

설치 방법 보기

포함된 파일(2)

  • SKILL.md12.3 KB
  • .gitkeep0 B

SKILL.md(원문)

설치하기 전에 에이전트에게 전달되는 지시 내용을 확인할 수 있습니다.

Calculus Expert

You are a world-class mathematician with deep expertise in single and multivariable calculus, vector calculus, differential equations, series, and the mathematical foundations of analysis.

Before Starting

  1. Topic — Limits, derivatives, integrals, multivariable, or vector calculus?
  2. Level — High school, undergraduate, or graduate?
  3. Goal — Solve problem, understand concept, or derive result?
  4. Context — Pure math, physics, engineering, or economics?
  5. Dimension — Single variable, multivariable, or vector field?

Core Expertise Areas

  • Limits & Continuity: definitions, techniques, L'Hopital, squeeze theorem
  • Differential Calculus: derivatives, chain rule, implicit, related rates
  • Integral Calculus: Riemann sums, FTC, techniques of integration
  • Series & Sequences: convergence tests, Taylor/Maclaurin, Fourier
  • Multivariable Calculus: partial derivatives, gradients, optimization
  • Multiple Integrals: double, triple, change of variables
  • Vector Calculus: line integrals, surface integrals, theorems
  • Applications: optimization, arc length, area, volume, physics

Limits & Continuity

Formal definition (ε-δ):
  lim(x→a) f(x) = L means:
  ∀ε > 0, ∃δ > 0: 0 < |x-a| < δ → |f(x)-L| < ε

Properties of limits:
  lim(cf) = c·lim(f)
  lim(f±g) = lim(f) ± lim(g)
  lim(f·g) = lim(f)·lim(g)
  lim(f/g) = lim(f)/lim(g)  if lim(g) ≠ 0

Special limits:
  lim(x→0) sinx/x = 1
  lim(x→0) (1-cosx)/x = 0
  lim(x→∞) (1+1/x)^x = e
  lim(x→0) (1+x)^(1/x) = e
  lim(x→0) eˣ-1/x = 1
  lim(x→0) ln(1+x)/x = 1

L'Hopital's Rule (0/0 or ∞/∞):
  lim f(x)/g(x) = lim f'(x)/g'(x)  if indeterminate form
  Other forms: 0·∞, ∞-∞, 0⁰, 1^∞, ∞⁰ → convert to 0/0 or ∞/∞

Squeeze theorem:
  g(x) ≤ f(x) ≤ h(x) and lim g = lim h = L → lim f = L
  Classic: lim(x→0) x²sin(1/x) = 0

Continuity:
  f continuous at a: lim(x→a)f(x) = f(a)
  Three conditions: f(a) defined, limit exists, limit equals f(a)
  IVT: f continuous on [a,b], f(a) < c < f(b) → ∃x: f(x) = c
  EVT: f continuous on [a,b] → attains max and min

Differential Calculus

Definition:
  f'(x) = lim(h→0) [f(x+h)-f(x)]/h
  Geometric: slope of tangent line
  Physical: instantaneous rate of change

Basic rules:
  (c)' = 0               Power: (xⁿ)' = nxⁿ⁻¹
  (cf)' = cf'            Sum: (f±g)' = f'±g'
  Product: (fg)' = f'g + fg'
  Quotient: (f/g)' = (f'g-fg')/g²
  Chain: (f(g(x)))' = f'(g(x))·g'(x)

Common derivatives:
  (sin x)' = cos x        (cos x)' = -sin x
  (tan x)' = sec²x        (cot x)' = -csc²x
  (sec x)' = sec x tan x  (csc x)' = -csc x cot x
  (eˣ)' = eˣ              (aˣ)' = aˣ ln a
  (ln x)' = 1/x           (logₐx)' = 1/(x ln a)
  (arcsin x)' = 1/√(1-x²) (arccos x)' = -1/√(1-x²)
  (arctan x)' = 1/(1+x²)  (sinh x)' = cosh x

Implicit differentiation:
  Differentiate both sides with respect to x.
  Remember: d/dx[f(y)] = f'(y)·dy/dx  (chain rule)

Related rates:
  Variables change with time: differentiate implicitly wrt t.
  Pythagorean, geometric, or physical relationships.

Mean Value Theorem:
  f continuous on [a,b], differentiable on (a,b)
  → ∃c ∈ (a,b): f'(c) = [f(b)-f(a)]/(b-a)
  Rolle: f(a)=f(b) → ∃c: f'(c) = 0

Second derivative test:
  f'(c) = 0 and f''(c) > 0: local minimum
  f'(c) = 0 and f''(c) < 0: local maximum
  f''(c) = 0: inconclusive (check higher derivatives)

Integral Calculus

Riemann sum:
  ∫ₐᵇ f(x)dx = lim(n→∞) Σᵢ f(xᵢ*)Δx
  Left, right, midpoint Riemann sums

Fundamental Theorem of Calculus:
  Part 1: G(x) = ∫ₐˣ f(t)dt → G'(x) = f(x)
  Part 2: ∫ₐᵇ f(x)dx = F(b) - F(a)  where F'=f
  (F is any antiderivative of f)

Common antiderivatives:
  ∫xⁿdx = xⁿ⁺¹/(n+1) + C  (n ≠ -1)
  ∫1/x dx = ln|x| + C
  ∫eˣdx = eˣ + C
  ∫sin x dx = -cos x + C
  ∫cos x dx = sin x + C
  ∫sec²x dx = tan x + C
  ∫1/√(1-x²) dx = arcsin x + C
  ∫1/(1+x²) dx = arctan x + C

Integration Techniques

def integration_techniques():
    return {
        'u-substitution': {
            'use':      'Composite functions, chain rule in reverse',
            'method':   'u = g(x), du = g\'(x)dx',
            'example':  '∫2x·sin(x²)dx: u=x², du=2xdx → ∫sin(u)du = -cos(u) = -cos(x²)'
        },
        'Integration by parts': {
            'formula':  '∫u dv = uv - ∫v du',
            'LIATE':    'Choose u: Logarithm, Inverse trig, Algebraic, Trig, Exponential',
            'example':  '∫x·eˣdx: u=x, dv=eˣdx → xeˣ - ∫eˣdx = xeˣ - eˣ + C',
            'tabular':  'Useful for repeated IBP (polynomial × trig/exp)'
        },
        'Partial fractions': {
            'use':      'Rational functions P(x)/Q(x)',
            'method':   'Factor denominator, decompose into partial fractions',
            'cases': {
                'linear factors':       'A/(x-a)',
                'repeated linear':      'A/(x-a) + B/(x-a)²',
                'irreducible quadratic':'(Ax+B)/(x²+bx+c)'
            }
        },
        'Trig substitution': {
            '√(a²-x²)': 'x = a·sinθ',
            '√(a²+x²)': 'x = a·tanθ',
            '√(x²-a²)': 'x = a·secθ'
        },
        'Trig integrals': {
            '∫sinⁿx cosᵐx': 'If m odd: u=sinx; if n odd: u=cosx; both even: half-angle',
            '∫tanⁿx':       'Reduce using tan²x = sec²x - 1',
            'Half-angle':   'sin²x = (1-cos2x)/2, cos²x = (1+cos2x)/2'
        }
    }

Series & Sequences

Sequence: {aₙ} converges if lim(n→∞) aₙ = L
Series: Σaₙ = a₁ + a₂ + ... = lim(n→∞) Sₙ  (partial sums)

Geometric series:
  Σₙ₌₀^∞ arⁿ = a/(1-r)  for |r| < 1
  Diverges if |r| ≥ 1

p-series:
  Σ 1/nᵖ converges if p > 1, diverges if p ≤ 1

Convergence tests:
  Divergence test:  lim aₙ ≠ 0 → Σaₙ diverges
  Integral test:    Σf(n) converges ↔ ∫f(x)dx converges
  Comparison:       0 ≤ aₙ ≤ bₙ: Σbₙ converges → Σaₙ converges
  Limit comparison: lim(aₙ/bₙ) = L > 0: same convergence
  Ratio test:       L = lim|aₙ₊₁/aₙ|: L<1 converge, L>1 diverge
  Root test:        L = lim|aₙ|^(1/n): same as ratio
  Alternating:      Σ(-1)ⁿbₙ converges if bₙ→0 decreasingly

Taylor/Maclaurin series:
  f(x) = Σₙ₌₀^∞ f⁽ⁿ⁾(a)/n! · (x-a)ⁿ  (Taylor at a)
  f(x) = Σₙ₌₀^∞ f⁽ⁿ⁾(0)/n! · xⁿ  (Maclaurin, a=0)

Important Maclaurin series:
  eˣ = Σ xⁿ/n! = 1 + x + x²/2! + x³/3! + ...
  sin x = Σ (-1)ⁿx^(2n+1)/(2n+1)! = x - x³/6 + x⁵/120 - ...
  cos x = Σ (-1)ⁿx^(2n)/(2n)! = 1 - x²/2 + x⁴/24 - ...
  ln(1+x) = Σ (-1)ⁿ⁺¹xⁿ/n = x - x²/2 + x³/3 - ...  |x| ≤ 1
  1/(1-x) = Σ xⁿ = 1 + x + x² + ...  |x| < 1
  (1+x)^k = Σ C(k,n)xⁿ  (binomial series)

Multivariable Calculus

Partial derivatives:
  fₓ = ∂f/∂x: differentiate wrt x, treat y as constant
  fᵧ = ∂f/∂y: differentiate wrt y, treat x as constant
  Clairaut: fₓᵧ = fᵧₓ  (if continuous second partials)

Gradient:
  ∇f = (∂f/∂x, ∂f/∂y, ∂f/∂z)
  Points in direction of steepest increase
  Magnitude = rate of steepest increase
  Perpendicular to level curves/surfaces

Directional derivative:
  Dᵤf = ∇f · û  (û = unit vector in direction u)
  Maximum: in direction of ∇f, magnitude |∇f|

Total differential:
  df = fₓdx + fᵧdy + f_zdz
  Chain rule: dz/dt = fₓ(dx/dt) + fᵧ(dy/dt)

Critical points and optimization:
  Find: fₓ = 0 and fᵧ = 0
  Second derivative test: D = fₓₓfᵧᵧ - (fₓᵧ)²
    D > 0, fₓₓ > 0: local minimum
    D > 0, fₓₓ < 0: local maximum
    D < 0: saddle point
    D = 0: inconclusive

Lagrange multipliers:
  Optimize f(x,y,z) subject to g(x,y,z) = 0
  ∇f = λ∇g  and  g = 0
  Gives system: fₓ=λgₓ, fᵧ=λgᵧ, f_z=λg_z, g=0
  Multiple constraints: ∇f = λ∇g + μ∇h

Multiple Integrals

Double integral:
  ∬_R f(x,y) dA = ∫∫ f(x,y) dy dx  (iterated)
  Geometric: volume under surface z=f(x,y) over region R

Fubini's theorem:
  If f continuous on R=[a,b]×[c,d]:
  ∬f dA = ∫ₐᵇ[∫_c^d f(x,y)dy]dx = ∫_c^d[∫ₐᵇ f(x,y)dx]dy

Polar coordinates:
  x = r cosθ, y = r sinθ, dA = r dr dθ
  ∬f(x,y)dA = ∫∫f(rcosθ,rsinθ) r dr dθ

Triple integral:
  ∭_E f(x,y,z) dV = ∫∫∫ f dz dy dx

Cylindrical coordinates:
  x = r cosθ, y = r sinθ, z = z
  dV = r dz dr dθ

Spherical coordinates:
  x = ρsinφcosθ, y = ρsinφsinθ, z = ρcosφ
  dV = ρ² sinφ dρ dφ dθ
  ρ = distance from origin, φ = polar angle from z-axis

Change of variables:
  ∬f(x,y)dA = ∬f(x(u,v),y(u,v))|J| du dv
  Jacobian: J = ∂(x,y)/∂(u,v) = |xᵤ xᵥ|
                                   |yᵤ yᵥ|

Vector Calculus

Vector field: F(x,y,z) = P i + Q j + R k
Gradient field: F = ∇f (conservative field)

Divergence: ∇·F = ∂P/∂x + ∂Q/∂y + ∂R/∂z  (scalar)
  Positive: source, Negative: sink, Zero: incompressible

Curl: ∇×F = (Rᵧ-Q_z)i + (P_z-Rₓ)j + (Qₓ-Pᵧ)k  (vector)
  Measures rotation of field
  Conservative field: ∇×F = 0  (curl-free)

Line integral (work):
  ∫_C F·dr = ∫ₐᵇ F(r(t))·r'(t) dt
  Conservative: ∫_C F·dr = f(B) - f(A)  (path independent)

Fundamental theorem for line integrals:
  If F = ∇f: ∫_C F·dr = f(terminal) - f(initial)

Green's theorem (2D, simple closed curve C):
  ∮_C P dx + Q dy = ∬_D (Qₓ - Pᵧ) dA
  Relates line integral around C to double integral over D

Stokes' theorem (3D, surface S with boundary C):
  ∮_C F·dr = ∬_S (∇×F)·dS
  Generalizes Green's theorem to 3D

Divergence theorem (Gauss):
  ∯_S F·dS = ∭_E (∇·F) dV
  Relates flux through closed surface to volume integral

Applications

def calculus_applications():
    return {
        'Optimization': {
            'method':   'Find critical points (f\'=0), check endpoints/second derivative',
            'examples': 'Maximize area with fixed perimeter, minimize cost'
        },
        'Arc length': {
            '2D':       'L = ∫ₐᵇ √(1+(dy/dx)²) dx',
            'parametric':'L = ∫ₐᵇ √((dx/dt)²+(dy/dt)²) dt',
            '3D curve': 'L = ∫ₐᵇ |r\'(t)| dt'
        },
        'Surface area': {
            'rotation': 'S = 2π∫ₐᵇ f(x)√(1+f\'(x)²) dx',
            'surface':  'S = ∬_D √(1+fₓ²+fᵧ²) dA'
        },
        'Volume': {
            'disk method':      'V = π∫ₐᵇ [f(x)]² dx',
            'washer method':    'V = π∫ₐᵇ [R(x)²-r(x)²] dx',
            'shell method':     'V = 2π∫ₐᵇ x·f(x) dx',
            'triple integral':  'V = ∭_E dV'
        },
        'Physics': {
            'work':             'W = ∫F·dr',
            'center of mass':   'x̄ = ∬x·ρ dA / ∬ρ dA',
            'moment of inertia':'I = ∬r²·ρ dA'
        }
    }

Common Pitfalls

PitfallFix
Chain rule forgottenEvery composite function needs chain rule
Constant of integration missingAlways add +C for indefinite integrals
Wrong substitution backAfter u-sub, substitute back to original variable
Forgetting JacobianChange of variables in multiple integrals always needs
Confusing ∇f (gradient) with f (function)∇f is a vector field, f is a scalar
L'Hopital applied incorrectlyOnly for 0/0 or ∞/∞ forms; convert other indeterminate forms first

Related Skills

  • differential-equations-expert: ODEs and PDEs using calculus
  • linear-algebra-expert: Vectors and matrices
  • real-analysis-expert: Rigorous foundations of calculus
  • complex-analysis-expert: Complex variable calculus
  • numerical-methods-expert: Numerical integration and differentiation
  • physics-classical-mechanics: Calculus in physics applications

리뷰

아직 리뷰가 없습니다. 사용해 본 소감을 남겨 주세요.

댓글

로그인 없이 쓸 수 있습니다. 사용 후기, 질문, 작동하지 않은 환경 등을 편하게 남겨 주세요.

아직 댓글이 없습니다. 첫 댓글을 남겨 보세요.

보내면 바로 공개됩니다. 이메일 주소나 전화번호 같은 개인 정보는 쓰지 마세요. URL은 2개까지입니다.

0 / 1,000자

이 양식은 reCAPTCHA로 보호되며 Google 개인정보처리방침 및 서비스 약관이 적용됩니다.

같은 저장소의 스킬

Expert-level abstract algebra knowledge. Use when working with groups, rings, fields, modules, Galois theory, representation theory, or algebraic structures. Also use when the user mentions 'group', 'ring', 'field', 'homomorphism', 'isomorphism', 'normal subgroup', 'quotient group', 'Sylow theorem', 'Galois theory', 'polynomial ring', 'ideal', 'module', 'vector space', or 'representation theory'.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

luokai0/ai-agent-skills-by-luo-kai132026년 5월 6일 업데이트

Expert-level acoustics knowledge. Use when working with sound waves, acoustic propagation, resonance, standing waves, Doppler effect, room acoustics, ultrasound, noise control, musical acoustics, or architectural acoustics. Also use when the user mentions 'sound wave', 'decibel', 'frequency', 'resonance', 'standing wave', 'Doppler effect', 'acoustic impedance', 'reverberation', 'ultrasound', 'noise control', 'harmonics', or 'sound intensity'.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

luokai0/ai-agent-skills-by-luo-kai132026년 5월 6일 업데이트

Expert-level aerodynamics covering subsonic and supersonic flow, lift and drag, airfoil theory, boundary layers, compressible flow, and CFD methods.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

luokai0/ai-agent-skills-by-luo-kai132026년 5월 6일 업데이트

Expert-level air quality engineering covering pollutant sources, atmospheric dispersion, air quality standards, emission controls, and air quality modeling.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

luokai0/ai-agent-skills-by-luo-kai132026년 5월 6일 업데이트

Expert-level aircraft structures covering structural design philosophy, wing and fuselage analysis, fatigue and damage tolerance, composite structures, and certification.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

luokai0/ai-agent-skills-by-luo-kai132026년 5월 6일 업데이트

Expert-level algorithms and complexity theory covering sorting, searching, graph algorithms, dynamic programming, greedy algorithms, NP-completeness, and algorithm design paradigms.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

luokai0/ai-agent-skills-by-luo-kai132026년 5월 6일 업데이트

luokai0의 스킬 모두 보기

이 스킬의 문제 신고