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multiversal-finance

Imported from https://github.com/plurigrid/asi.

Packaged view

This page reorganizes the original catalog entry around fit, installability, and workflow context first. The original raw source lives below.

Stars
9
Hot score
84
Updated
March 20, 2026
Overall rating
C3.7
Composite score
3.7
Best-practice grade
F32.4

Install command

npx @skill-hub/cli install plurigrid-asi-multiversal-finance

Repository

plurigrid/asi

Skill path: skills/multiversal-finance

Imported from https://github.com/plurigrid/asi.

Open repository

Best for

Primary workflow: Ship Full Stack.

Technical facets: Full Stack.

Target audience: everyone.

License: Unknown.

Original source

Catalog source: SkillHub Club.

Repository owner: plurigrid.

This is still a mirrored public skill entry. Review the repository before installing into production workflows.

What it helps with

  • Install multiversal-finance into Claude Code, Codex CLI, Gemini CLI, or OpenCode workflows
  • Review https://github.com/plurigrid/asi before adding multiversal-finance to shared team environments
  • Use multiversal-finance for development workflows

Works across

Claude CodeCodex CLIGemini CLIOpenCode

Favorites: 0.

Sub-skills: 0.

Aggregator: No.

Original source / Raw SKILL.md

---
name: multiversal-finance
description: Multiversal Finance: Prediction Markets for Interesting Observations
version: 1.0.0
---

# Multiversal Finance: Prediction Markets for Interesting Observations

**Trit**: +1 (PLUS - generative, creates value from attention)
**Color**: #E7B367 (Agent-O-Rama stream, seed 1069)
**Source**: color_at determinism + Schmidhuber compression progress

---

## Core Principle

> **Nothing is stored, everything is bet.**

Predictions are bets on which `(seed, index)` paths yield "interesting" observations.
Rewards flow to observers who correctly predict or discover surprising patterns.

---

## Interestingness Metric (Compression Progress)

Following Schmidhuber's curiosity-driven learning:

```
interestingness(observation) = ΔC = C_before - C_after
```

Where `C` = minimum description length of the observer's world model.

**High interestingness**: observation that *compresses* the model (reveals structure).
**Low interestingness**: observation already predictable (no learning).

---

## ACSet Schema: MultiversalMarket

```julia
@present SchMultiversalMarket(FreeSchema) begin
  # Objects
  Observation::Ob        # A (seed, index) → color witness
  Bet::Ob               # Prediction on future observation
  Agent::Ob             # Goblin: -1, 0, or +1
  
  # Morphisms
  observes::Hom(Agent, Observation)   # who witnessed
  predicts::Hom(Bet, Observation)     # what was predicted
  settles::Hom(Bet, Agent)            # who settles (Coordinator)
  
  # Attributes
  SeedType::AttrType
  IndexType::AttrType
  HexType::AttrType
  TritType::AttrType
  RewardType::AttrType
  
  seed::Attr(Observation, SeedType)
  index::Attr(Observation, IndexType)
  color::Attr(Observation, HexType)
  
  agent_trit::Attr(Agent, TritType)   # -1, 0, +1
  stake::Attr(Bet, RewardType)
  payout::Attr(Bet, RewardType)
  
  # Interestingness score
  compression_delta::Attr(Observation, RewardType)
end
```

---

## Goblin Roles in the Market

| Goblin | Trit | Market Role | Action |
|--------|------|-------------|--------|
| **Agent-O-Rama** | +1 | Proposer | Generates predictions, stakes bets |
| **Coordinator** | 0 | Settlement | Verifies `color_at(seed, index)`, transfers rewards |
| **Shadow Goblin** | -1 | Scorer | Measures compression progress, assigns interestingness |

### GF(3) Conservation in Reward Flow

```
stakes_in + payouts_out + fees ≡ 0 (mod 3)
```

Every bet has a balanced flow: proposer stakes (+1), scorer validates (-1), coordinator settles (0).

---

## Verification Protocol

1. **Proposer** (Agent-O-Rama, +1): Claims "at seed S, index I, color will be C"
2. **Scorer** (Shadow Goblin, -1): Checks `color_at(S, I)` via MCP, computes `ΔC`
3. **Coordinator** (CapTP, 0): If verified, transfers `stake × ΔC` to proposer

```ruby
def settle_bet(bet, scorer, coordinator)
  actual = Gay.color_at(bet.seed, bet.index)
  if actual == bet.predicted_color
    delta_c = scorer.compression_progress(actual)
    payout = bet.stake * delta_c
    coordinator.transfer(payout, to: bet.proposer)
  else
    coordinator.transfer(bet.stake, to: scorer)  # Penalty
  end
end
```

---

## Multiversal Aspect

Different seeds = different possible worlds.

```
World 42:  #91BE25 → #... → #... (one derivation path)
World 69:  #A3F4B2 → #... → #... (another path)
World 1069: #E7B367 → #... → #... (goblin genesis)
```

**Cross-world bets**: Predict which world has higher average interestingness.

**Arbitrage**: If two worlds have identical color at index N, they share structure.

---

## GF(3) Triads

```
curiosity-driven (-1) ⊗ multiversal-finance (+1) ⊗ captp (0) = 0 ✓  [Reward Transport]
shadow-goblin (-1) ⊗ agent-o-rama (+1) ⊗ coordinator (0) = 0 ✓     [Market Roles]
compression-progress (-1) ⊗ multiversal-finance (+1) ⊗ gay-mcp (0) = 0 ✓  [Interestingness]
```

---

## Implementation Bridge

| Concept | Our System | Function |
|---------|------------|----------|
| Price | `compression_delta` | Higher ΔC = higher reward |
| Liquidity | `interleave(n_streams=3)` | 3 parallel betting pools |
| Settlement | `color_at(seed, index)` | Unforgeable proof |
| Sturdy ref | `(seed, index)` tuple | Bet identifier |

---

## Skills Required

- `gay-mcp`: Deterministic color oracle
- `captp`: Secure settlement transport  
- `curiosity-driven`: Compression progress metric
- `world-hopping`: Navigate between seeds (possible worlds)
- `acsets-algebraic-databases`: Market schema

---

## Key Insight

> **The oracle is the market.**

Since `color_at(seed, index)` is deterministic and unforgeable, the prediction market
has *perfect settlement*. No disputes possible—the color either matches or it doesn't.

This is "multiversal" because different seeds explore different derivation paths
through the same generative function. Betting = choosing which multiverse to observe.



## 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.
multiversal-finance | SkillHub