docs(mincut): Major README improvements + SEO optimization

Examples README (examples/mincut/):
- New title: "Networks That Think For Themselves"
- Added compelling intros with analogies for all 6 examples
- Added "Core Insight" section with visual network comparison
- Added "Why This Changes Everything" performance comparison
- Fixed run commands to use -p ruvector-mincut format
- Added badges linking to crates.io, docs.rs, GitHub, ruv.io

Crate README (crates/ruvector-mincut/):
- Added "Self-Organizing Network Examples" section with table
- Links to GitHub examples guide

Cargo.toml SEO:
- Improved description for discoverability
- Added keywords: graph, minimum-cut, network-analysis, self-healing, dynamic-graph
- Added categories: algorithms, data-structures, science, mathematics, simulation
- Added homepage (ruv.io) and documentation links
- Registered all 7 examples in crate

Version bump: 0.1.25 → 0.1.26

🤖 Generated with [Claude Code](https://claude.com/claude-code)

Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com>

Author: ruvnet

Cargo.toml

@@ -45,7 +45,7 @@ members = [
 resolver = "2"
 
 [workspace.package]
-version = "0.1.25"
+version = "0.1.26"
 edition = "2021"
 rust-version = "1.77"
 license = "MIT"

crates/ruvector-mincut/Cargo.toml

@@ -7,7 +7,11 @@ license.workspace = true
 authors.workspace = true
 repository.workspace = true
 readme = "README.md"
-description = "Subpolynomial-time dynamic minimum cut algorithm with real-time graph monitoring"
+description = "World's first subpolynomial dynamic min-cut: self-healing networks, AI optimization, real-time graph analysis"
+keywords = ["graph", "minimum-cut", "network-analysis", "self-healing", "dynamic-graph"]
+categories = ["algorithms", "data-structures", "science", "mathematics", "simulation"]
+homepage = "https://ruv.io"
+documentation = "https://docs.rs/ruvector-mincut"
 
 [dependencies]
 # RuVector dependencies
@@ -72,16 +76,36 @@ name = "snn_bench"
 harness = false
 
 [[example]]
-name = "mincut_neural_optimizer"
-path = "../../examples/mincut/neural_optimizer/main.rs"
+name = "temporal_attractors"
+path = "../../examples/mincut/temporal_attractors/src/main.rs"
+required-features = ["exact"]
+
+[[example]]
+name = "strange_loop"
+path = "../../examples/mincut/strange_loop/main.rs"
 required-features = ["exact"]
 
 [[example]]
-name = "mincut_causal_discovery"
+name = "causal_discovery"
 path = "../../examples/mincut/causal_discovery/main.rs"
 required-features = ["exact"]
 
+[[example]]
+name = "time_crystal"
+path = "../../examples/mincut/time_crystal/main.rs"
+required-features = ["exact"]
+
 [[example]]
 name = "morphogenetic"
 path = "../../examples/mincut/morphogenetic/main.rs"
 required-features = ["exact"]
+
+[[example]]
+name = "neural_optimizer"
+path = "../../examples/mincut/neural_optimizer/main.rs"
+required-features = ["exact"]
+
+[[example]]
+name = "benchmarks"
+path = "../../examples/mincut/benchmarks/main.rs"
+required-features = ["exact"]

crates/ruvector-mincut/README.md

@@ -228,6 +228,23 @@ let current_cut = mincut.min_cut_value();
 
 ---
 
+## 🧪 Self-Organizing Network Examples
+
+Learn to build networks that think for themselves. These examples demonstrate self-healing, self-optimizing, and self-aware systems:
+
+| Example | Description | Run Command |
+|---------|-------------|-------------|
+| **Temporal Attractors** | Networks that evolve toward stable states | `cargo run -p ruvector-mincut --release --example temporal_attractors` |
+| **Strange Loop** | Self-aware systems that monitor and repair themselves | `cargo run -p ruvector-mincut --release --example strange_loop` |
+| **Causal Discovery** | Trace cause-and-effect chains in failures | `cargo run -p ruvector-mincut --release --example causal_discovery` |
+| **Time Crystal** | Self-sustaining periodic coordination patterns | `cargo run -p ruvector-mincut --release --example time_crystal` |
+| **Morphogenetic** | Networks that grow like biological organisms | `cargo run -p ruvector-mincut --release --example morphogenetic` |
+| **Neural Optimizer** | ML that learns optimal graph configurations | `cargo run -p ruvector-mincut --release --example neural_optimizer` |
+
+See the full [Examples Guide](https://github.com/ruvnet/ruvector/tree/main/examples/mincut) for detailed explanations and real-world applications.
+
+---
+
 ## 💡 Key Features & Benefits
 
 ### Core Features