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limits

npx machina-cli add skill parcadei/Continuous-Claude-v3/limits --openclaw
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Limits

When to Use

Use this skill when working on limits problems in real analysis.

Decision Tree

  1. Direct Substitution

    • Try plugging in the value directly
    • If you get a determinate form, that's the answer
  2. Indeterminate Form? (0/0, inf/inf)

    • Try algebraic manipulation (factor, rationalize)
    • Try L'Hopital's rule: sympy_compute.py diff on numerator/denominator
  3. Squeeze Theorem

    • If bounded: find g(x) <= f(x) <= h(x) where lim g = lim h
    • Verify bounds with z3_solve.py prove
  4. Epsilon-Delta Proof

    • For rigorous proof: set up |f(x) - L| < epsilon
    • Find delta in terms of epsilon
    • Verify with math_scratchpad.py verify

Tool Commands

Sympy_Limit

uv run python -m runtime.harness scripts/sympy_compute.py limit "sin(x)/x" --var x --at 0

Sympy_Diff

uv run python -m runtime.harness scripts/sympy_compute.py diff "x**2" --var x

Z3_Prove

uv run python -m runtime.harness scripts/z3_solve.py prove "limit_bound" --vars x

Cognitive Tools Reference

See .claude/skills/math-mode/SKILL.md for full tool documentation.

Source

git clone https://github.com/parcadei/Continuous-Claude-v3/blob/main/.claude/skills/math/real-analysis/limits/SKILL.mdView on GitHub

Overview

This skill provides practical strategies for solving limits in real analysis. It guides you through a four-step decision tree—direct substitution, indeterminate forms, the Squeeze Theorem, and epsilon-delta proofs—and shows how to verify results with symbolic tools.

How This Skill Works

Use a decision-tree workflow: start with direct substitution, then tackle 0/0 or inf/inf with algebraic manipulation or L'Hôpital's rule, apply the Squeeze Theorem when bounds exist, or construct an epsilon-delta proof for rigor. The workflow demonstrates tool-assisted verification using Sympy and Z3 as shown in the Skill.

When to Use It

  • Direct substitution yields a determinate form
  • Encounter 0/0 or inf/inf indeterminate forms requiring algebraic manipulation or L'Hôpital's rule
  • You need to prove a limit using the Squeeze Theorem with known bounds
  • You require a rigorous epsilon-delta proof of a limit
  • You want to verify limit-related computations with symbolic tooling (Sympy or Z3)

Quick Start

  1. Step 1: Try direct substitution; if you get a determinate form, record the limit.
  2. Step 2: If you get an indeterminate form, apply algebraic simplification or L'Hôpital's rule (`sympy_compute.py diff` on numerator/denominator).
  3. Step 3: When a bound exists, use the Squeeze Theorem or craft an epsilon-delta proof and verify with the tool commands (Sympy_Limit, Sympy_Diff, Z3_Prove).

Best Practices

  • Start with direct substitution and look for a determinate form
  • If indeterminate, apply algebraic manipulation (factoring, rationalizing) before resorting to L'Hôpital
  • Use L'Hôpital's rule only after simplifying and only on valid indeterminate forms
  • Use the Squeeze Theorem when you can bound f(x) between g(x) and h(x) with known limits
  • For rigor, craft an epsilon-delta proof and verify the delta-epsilon relationship with a tool like math_scratchpad.py verify

Example Use Cases

  • lim_{x→0} sin(x)/x
  • lim_{x→0} (1 - cos x)/x^2
  • lim_{x→∞} (1 + 1/x)^x
  • lim_{x→1} (x^2 - 1)/(x - 1) = 2
  • Definition of derivative: lim_{x→a} (f(x) - f(a))/(x - a) = f'(a)

Frequently Asked Questions

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