obstruction-learning
Obstruction Learning Skill
When & Why to Use This Skill
The Obstruction Learning Skill is a sophisticated diagnostic and verification tool designed for advanced agentic systems. It utilizes topological methods, specifically Čech cohomology and random walk detection on Ramanujan expanders, to identify 'obstructions'—irreducible elements that prevent local agent behaviors from forming a consistent global state. By enforcing GF(3) conservation laws across skill triads, it ensures mathematical coherence, evaluates system-wide spectral awareness, and optimizes coordination efficiency by minimizing World Extractable Value (WEV).
Use Cases
- Detecting and resolving logical inconsistencies in complex multi-agent skill compositions where local patches fail to glue into a globally consistent behavior.
- Evaluating the structural integrity and spectral mixing of AI models through random walk sampling on high-dimensional skill manifolds.
- Optimizing decentralized coordination by calculating and reducing World Extractable Value (WEV), which represents coordination loss within the system.
- Verifying the mathematical balance of agent triads (Validator, Coordinator, Generator) to ensure system-wide harmony and functional stability.
- Mapping and auditing the density of skills within a 23³ grid to identify 'unbalanced cells' that require complementary skill injection.
| name | obstruction-learning |
|---|---|
| description | Obstruction Learning Skill |
| version | 1.0.0 |
Obstruction Learning Skill
Learn topological ASI via random walk obstruction detection and Čech H⁰ cohomology.
Metadata
| Property | Value |
|---|---|
| Name | obstruction-learning |
| Trit | -1 (VALIDATOR) |
| Category | Topological Verification |
| Dependencies | sheaf-cohomology, ramanujan-expander, gay-mcp |
Core Concept
Obstructions are H⁰ generators - irreducible elements that block global consistency from local patches.
Čech Cohomology: H⁰(U, F) = ker(d₀: F(U) → ∏ᵢⱼ F(Uᵢ ∩ Uⱼ))
Obstruction detected when:
- GF(3) conservation violated (sum ≢ 0 mod 3)
- Voice triads don't harmonize
- Skill compositions conflict
- Local patches fail to glue globally
Random Walk Reconstruction
The 69-Skill Walk
Sample 69 skills from the 181-skill manifold:
# Execute random walk
just random-walk-69
# Verify GF(3) conservation
just verify-gf3
# Track cumulative obstructions
just random-walk-obstruction 69
Obstruction Detection
-- Find unbalanced cells in 23³ grid
SELECT cell_id, skill_count, trit_sum, gf3_status
FROM cell_density
WHERE gf3_status = 'UNBALANCED';
-- H⁰ generators by trit class
SELECT trit, COUNT(*) as generators
FROM skills
GROUP BY trit;
Mathematical Foundations
Čech Cohomology
For a covering U = {Uᵢ} of skill space:
H⁰(U, F) = { s ∈ F(U) | d₀(s) = 0 }
where d₀: F(U) → ∏ F(Uᵢ ∩ Uⱼ)
maps global sections to intersection restrictions
Obstruction = element of H⁰ that prevents gluing.
GF(3) as Cohomology
The GF(3) conservation law is a discrete cohomology:
Trit assignment: skill → {-1, 0, +1}
Coboundary: d(triad) = sum of trits mod 3
H⁰ = { triads | d(triad) = 0 } = balanced triads
Obstruction = triad with d ≠ 0
Ramanujan Mixing
Random walks on Ramanujan expanders mix optimally:
λ₂ ≤ 2√(d-1) [Alon-Boppana bound]
gap = d - λ₂ [Spectral gap]
τ_mix = O(log n / gap) [Mixing time]
Workflow
1. Pre-Interaction Sync
just pre-interaction
# Syncs plurigrid/asi arena + hdresearch/duck
# Loads GF(3) skill triad
# Computes spectral awareness
2. Random Walk Sampling
# Sample without replacement (maximal coverage)
just random-walk-69
# Sample with replacement (GF(3) conservation)
just random-walk 23
3. Obstruction Detection
# Find H⁰ generators
just obstruction-h0
# Detect unbalanced cells
just obstruction-detect
# Balance with complementary skill
just obstruction-balance -1 # Find validators to add
just obstruction-balance +1 # Find generators to add
4. Audio Generation
Convert obstruction traces to sound:
just audio-from-trace
Integration Patterns
With Voice Enforcement
# voice-enforcement.toml
[triads.obstruction]
validator = "Milena (Enhanced)" # -1: detects obstruction
coordinator = "Petra (Premium)" # 0: mediates resolution
generator = "Federica (Premium)" # +1: proposes fix
sum = 0
With Dune Orthogonalization
The 23×23×23 grid maps skills to:
| Axis | Dimensions |
|---|---|
| DATA | chain_indexing → real_time_streaming |
| INTERFACE | sql_query_engine → ai_copilot |
| INFRASTRUCTURE | kubernetes → multi_tenant_isolation |
With World Extractable Value
WEV = PoA - 1 = extractable coordination loss
Obstruction → WEV > 0
Resolution → WEV → 0
Global consistency → Optimal coordination
Commands
# Full ASI learning loop
just asi-learn
# Spectral bounds
just spectral-bounds
# World Extractable Value
just wev-compute
# Voice obstruction analysis
just voice-obstructions
Skill Triad
This skill belongs to the topological verification triad:
| Role | Skill | Trit |
|---|---|---|
| VALIDATOR | obstruction-learning | -1 |
| COORDINATOR | sheaf-cohomology | 0 |
| GENERATOR | persistent-homology | +1 |
Sum = 0 ✓ GF(3) conserved
References
- Bott & Tu, Differential Forms in Algebraic Topology
- Lurie, Higher Topos Theory
- Riehl-Shulman, Synthetic ∞-categories
- QRI, Symmetry Theory of Valence
Scientific Skill Interleaving
This skill connects to the K-Dense-AI/claude-scientific-skills ecosystem:
Graph Theory
- networkx [○] via bicomodule
- Universal graph hub
Bibliography References
general: 734 citations in bib.duckdb
Cat# Integration
This skill maps to Cat# = Comod(P) as a bicomodule in the equipment structure:
Trit: 0 (ERGODIC)
Home: Prof
Poly Op: ⊗
Kan Role: Adj
Color: #26D826
GF(3) Naturality
The skill participates in triads satisfying:
(-1) + (0) + (+1) ≡ 0 (mod 3)
This ensures compositional coherence in the Cat# equipment structure.