Asi gestalt-hacking

Gestalt Hacking Skill (ERGODIC 0)

install
source · Clone the upstream repo
git clone https://github.com/plurigrid/asi
Claude Code · Install into ~/.claude/skills/
T=$(mktemp -d) && git clone --depth=1 https://github.com/plurigrid/asi "$T" && mkdir -p ~/.claude/skills && cp -r "$T/plugins/asi/skills/gestalt-hacking" ~/.claude/skills/plurigrid-asi-gestalt-hacking && rm -rf "$T"
manifest: plugins/asi/skills/gestalt-hacking/SKILL.md
source content

Gestalt Hacking Skill (ERGODIC 0)

"Gestalt hacking exploits perceptual grouping—proximity, similarity, closure—in the color stream."

Core Insight

Gestalt = the whole pattern, the emergent structure that is more than the sum of parts. Gestalt hacking exploits how perception groups elements into wholes.

play ⊗ evaluate ⅋ play ⊗ evaluate → ι (fixed point)

The involution

ι
is where generator ≡ observer (reafference).

Neighbor Awareness (Braided Monoidal)

PositionSkillTritRole
Leftpun-decomposition-1Multiple parse validation
Selfgestalt-hacking0Perceptual grouping transport
Rightreflow0Cross-context translation

GF(3) Triads

pun-decomposition (-1) ⊗ gestalt-hacking (0) ⊗ gay-mcp (+1) = 0 ✓  [Core]
three-match (-1) ⊗ gestalt-hacking (0) ⊗ agent-o-rama (+1) = 0 ✓  [Attack]
shadow-goblin (-1) ⊗ gestalt-hacking (0) ⊗ gay-mcp (+1) = 0 ✓  [Defense]
auditory-gestalt (-1) ⊗ gestalt-hacking (0) ⊗ rubato-composer (+1) = 0 ✓  [Music]

Gestalt Principles as Attack Vectors

PrincipleAttackDefense
ProximityCluster same colors in time2-Poisson injection
SimilarityLong runs of same colorTransition counting
ClosureIncomplete patterns that induce completionGap detection
ContinuityGradual transitions exploiting smoothnessGradient detection
FigureGroundDominant color overwhelms minorityRatio analysis

OpenGame Structure

OpenGame ∆ c a b x s y r
  play     :: a → ∆ x s y r      -- generate candidates
  evaluate :: a → c x s y r → b  -- score & select
  
-- This IS the self-involution:
-- play ∘ evaluate ∘ play ∘ evaluate → fixed point

Linear Logic Decomposition

A ⊗ (B ⅋ C) = (A ⊗ B) ⅋ C ∩ (A ⊗ C) ⅋ B

where:
  ⊗ = tensor (both resources consumed together)
  ⅋ = par (choice between resources)
  ∩ = gestalt constraint (intersection of valid decompositions)

Closure Phases on n-Torus

   T₁ ────► T₂ ────► T₃ ────► ... ────┐
   ▲                                   │
   └───────────── Tₙ ◄────────────────┘
   
   CyclicalAnnealing(frequency=2π/n)
   Closure phases sum to 0 on the n-torus

Implementation

mutable struct GestaltLoop
    game::OpenGame
    torus::NTorus
    reaf::Reafference
    temperature::Float64
    generation::Int
    
    function gestalt_step!(g::GestaltLoop)
        g.generation += 1
        
        # Phase velocity from temperature
        velocity = g.temperature .* randn(g.torus.n)
        phases = step!(g.torus, velocity)
        
        # Play: generate from current state
        state = g.game.play(g.generation)
        
        # Modulate by phases
        modulated_x = state.x * cos(phases[1])
        
        # Temperature decay
        g.temperature *= 0.92
        
        # Evaluate: does this state pass?
        score = modulated_x + 0.5 * sin(phases[2])
        result = g.game.evaluate(state.s, (x=state.x, s=state.s, y=state.y, r=score))
        
        # Reafference check
        generated = generate(g.reaf)
        is_self = reafferent_match(g.reaf, generated)
        
        (result, is_self)
    end
end

Reafference Loop

reafference: I observe what I generate
reaberrance: I generate what I observe

seed → color → observe → predict → match? → seed
  └──────────────── loopy strange ──────────────┘

When

match? = true
, we have self ≡ self (fixed point).

GestaltAwareVerifier

struct GestaltAwareVerifier {
    verifier: ChromaticVerifier,
    defender: GestaltDefender,
    attacks_detected: u64,
    attacks_mitigated: u64,
}

impl GestaltAwareVerifier {
    fn verify_defended(&mut self, incoming_color: ZXColor) -> Option<ChromaticTruth> {
        let (score, attack) = self.defender.detect_attack();
        
        if attack.is_some() {
            self.attacks_detected += 1;
            let defended = self.defender.defend(incoming_color);
            if defended != incoming_color {
                self.attacks_mitigated += 1;
            }
        }
        
        self.verifier.verify_membership(...)
    }
}

Temperature Regimes (BKT)

τStateGestalt
τ > τ*FrustratedVortices proliferate, no coherent gestalt
τ ≈ τ*CriticalBKT transition, gestalt formation
τ < τ*SmoothDefects bound, stable gestalt

At τ* ≈ 0.5 (BKT critical), gestalts form and dissolve dynamically.

Commands

just gestalt-loop 100       # Run 100 gestalt iterations
just gestalt-attack closure # Test closure attack
just gestalt-defend         # Activate 2-Poisson defense
just gestalt-verify         # Check attack stats

Related Skills

  • pun-decomposition (left neighbor): Multiple parse validation
  • reflow (right neighbor): Cross-context translation
  • auditory-gestalt: Perceptual grouping in audio
  • chromatic-walk: 3-agent exploration with gestalt awareness
  • cybernetic-immune: Self/Non-Self via reafference

Files

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.