
entropy
by parcadei
Context management for Claude Code. Hooks maintain state via ledgers and handoffs. MCP execution without context pollution. Agent orchestration with isolated context windows.
Use Cases
MCP Server Integration
AI tool integration using Model Context Protocol. Using entropy.
API Integration
Easily build API integrations with external services.
Data Synchronization
Automatically sync data between multiple systems.
SKILL.md
name: entropy description: "Problem-solving strategies for entropy in information theory" allowed-tools: [Bash, Read]
Entropy
When to Use
Use this skill when working on entropy problems in information theory.
Decision Tree
-
Shannon Entropy
- H(X) = -sum p(x) log2 p(x)
- Maximum for uniform distribution: H_max = log2(n)
- Minimum = 0 for deterministic (one outcome certain)
scipy.stats.entropy(p, base=2)for discrete
-
Entropy Properties
- Non-negative: H(X) >= 0
- Concave in p
- Chain rule: H(X,Y) = H(X) + H(Y|X)
z3_solve.py prove "entropy_nonnegative"
-
Joint and Conditional Entropy
- H(X,Y) = -sum sum p(x,y) log2 p(x,y)
- H(Y|X) = H(X,Y) - H(X)
- H(Y|X) <= H(Y) with equality iff independent
-
Differential Entropy (Continuous)
- h(X) = -integral f(x) log f(x) dx
- Can be negative!
- Gaussian: h(X) = 0.5 * log2(2pie*sigma^2)
sympy_compute.py integrate "-f(x)*log(f(x))" --var x
-
Maximum Entropy Principle
- Given constraints, max entropy distribution is least biased
- Uniform for no constraints
- Exponential for E[X] = mu constraint
- Gaussian for E[X], Var[X] constraints
Tool Commands
Scipy_Entropy
uv run python -c "from scipy.stats import entropy; p = [0.25, 0.25, 0.25, 0.25]; H = entropy(p, base=2); print('Entropy:', H, 'bits')"
Scipy_Kl_Div
uv run python -c "from scipy.stats import entropy; p = [0.5, 0.5]; q = [0.9, 0.1]; kl = entropy(p, q); print('KL divergence:', kl)"
Sympy_Entropy
uv run python -m runtime.harness scripts/sympy_compute.py simplify "-p*log(p, 2) - (1-p)*log(1-p, 2)"
Key Techniques
From indexed textbooks:
- [Elements of Information Theory] Elements of Information Theory -- Thomas M_ Cover & Joy A_ Thomas -- 2_, Auflage, New York, NY, 2012 -- Wiley-Interscience -- 9780470303153 -- 2fcfe3e8a16b3aeefeaf9429fcf9a513 -- Anna’s Archive. What is the channel capacity of this channel? This is the multiple-access channel solved by Liao and Ahlswede.
Cognitive Tools Reference
See .claude/skills/math-mode/SKILL.md for full tool documentation.
Score
Total Score
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