home / skills / plurigrid / asi / worldmat-tidar
This skill analyzes and explains Worldmat-Tidar's 3x3x3 TiDAR matrix to help you understand topological computation and triad dynamics.
npx playbooks add skill plurigrid/asi --skill worldmat-tidarReview the files below or copy the command above to add this skill to your agents.
---
name: worldmat-tidar
description: 'worldmat-tidar'
version: 1.0.0
---
# worldmat-tidar
> World Matrices via TiDAR Executions: 3×3×3 Parallel Triadic Computation
**Version**: 1.0.0
**Trit**: 0 (ERGODIC - coordinates execution)
**Color**: #55D9A0
## Overview
**Worldmat** is a 3×3×3 matrix of TiDAR executions where:
- **Rows**: MINUS/ERGODIC/PLUS polarities (GF(3) agents)
- **Columns**: PAST/PRESENT/FUTURE temporal phases
- **Depth**: OBSERVATION/ACTION/PREDICTION modalities
Each cell executes the TiDAR pattern:
1. **DIFFUSION**: Draft tokens in parallel (like SplitRng.split)
2. **AR VERIFY**: Verify sequentially (autoregressive)
## Architecture
```
TEMPORAL AXIS
PAST PRESENT FUTURE
↓ ↓ ↓
┌─────────────────────────────┐
│ ┌───┐ ┌───┐ ┌───┐ │
MINUS │ │-1 │ │ 0 │ │+1 │ ← GF(3)=0
│ └───┘ └───┘ └───┘ │
POLARITY │ ┌───┐ ┌───┐ ┌───┐ │
ERGODIC│ │ 0 │ │+1 │ │-1 │ ← GF(3)=0
│ └───┘ └───┘ └───┘ │
│ ┌───┐ ┌───┐ ┌───┐ │
PLUS │ │+1 │ │-1 │ │ 0 │ ← GF(3)=0
│ └───┘ └───┘ └───┘ │
└─────────────────────────────┘
↑ ↑ ↑
GF(3)=0 for each column
```
## Key Properties
| Property | Value | Guarantee |
|----------|-------|-----------|
| **GF(3) Conservation** | All slices sum to 0 | Row, Column, Depth |
| **SPI** | Same seed → Same result | Parallel or Sequential |
| **Spectral Gap** | 0.25 (1/4) | Ergodic mixing |
| **Cells** | 27 | 3³ TiDAR executions |
## TiDAR Pattern (arXiv:2511.08923)
```python
# Phase 1: DIFFUSION (parallel drafting)
def diffusion_draft(self, n_tokens: int = 8):
streams = self.rng.split(n_tokens)
return [stream.next()[0] for stream in streams]
# Phase 2: AR VERIFY (sequential verification)
def ar_verify(self):
prev = self.seed
for token in self.draft_tokens:
verified = mix64(prev ^ token)
self.verified_tokens.append(verified)
prev = verified
```
## Work Stealing
Idle agents steal work from busy agents:
```python
class WorkStealingScheduler:
def steal_work(self, thief: Polarity) -> Optional[TiDARCell]:
busiest = max(self.queues.keys(), key=lambda p: len(self.queues[p]))
if busiest != thief and self.queues[busiest]:
return self.queues[busiest].pop(0)
return None
```
## ACSet Export
```python
wm = Worldmat(master_seed=0x87079c9f1d3b0474)
wm.execute_parallel()
acset = wm.to_acset()
# Returns: {schema, parts, subparts, metadata}
```
## Commands
```bash
# Run demo
python worldmat.py
# Verify SPI
python worldmat.py verify
# Export ACSet
python worldmat.py acset > worldmat.json
```
## GF(3) Triads
```
worldmat-tidar (0) forms balanced triads:
three-match (-1) ⊗ worldmat-tidar (0) ⊗ gay-mcp (+1) = 0 ✓
spi-parallel-verify (-1) ⊗ worldmat-tidar (0) ⊗ triad-interleave (+1) = 0 ✓
tidar_streaming (-1) ⊗ worldmat-tidar (0) ⊗ gay_triadic_exo (+1) = 0 ✓
```
## Integration
### With OpenAI ACSet
```python
from worldmat import Worldmat
from openai_acset import build_openai_acset
# Process conversations through worldmat
wm = Worldmat(master_seed=conv_fingerprint)
wm.execute_parallel()
# Each message → cell in worldmat
# Role (user/assistant/tool) → polarity
# Time → temporal phase
# Type (obs/action/pred) → modality
```
### With Gay-MCP
```python
from gay import SplitMixTernary
# Worldmat colors from Gay-MCP
gen = SplitMixTernary(seed=worldmat.fingerprint())
palette = gen.palette_hex(n=27) # One color per cell
```
## Files
| File | Purpose |
|------|---------|
| `worldmat.py` | Core implementation |
| `SKILL.md` | This documentation |
## References
- TiDAR: arXiv:2511.08923
- Gay.jl/src/spc_repl.jl - Whale synergy matrix
- rio/gayzip/tidar_streaming.py - TiDAR ZIP implementation
- gay_triadic_exo.py - Triadic agent orchestration
Base directory: file:///Users/bob/.claude/skills/worldmat-tidar
This skill implements World Matrices via TiDAR executions: a 3×3×3 parallel triadic computation that organizes agents by polarity, time, and modality. It provides a deterministic, ergodic matrix of 27 TiDAR cells capable of parallel drafting and autoregressive verification. The goal is reproducible multi-agent coordination with GF(3) conservation and simple export to ACSet formats.
The system arranges 27 cells across three axes: polarity (MINUS/ERGODIC/PLUS), temporal phase (PAST/PRESENT/FUTURE), and modality (OBSERVATION/ACTION/PREDICTION). Each cell runs a two-phase TiDAR pattern: parallel DIFFUSION to draft tokens from split RNG streams, followed by AR VERIFY to sequentially mix and verify tokens. Work stealing balances load between idle and busy polarities, and the worldmat can export results as an ACSet for downstream processing.
What guarantees of reproducibility exist?
Using the same master seed guarantees SPI: parallel or sequential runs produce identical results.
How are tokens generated and verified?
Tokens are drafted in parallel via RNG splits during DIFFUSION, then AR VERIFY sequentially mixes each token with the previous verified value to produce a chain of verified tokens.
Can I change the mapping of roles or phases?
Yes. Role-to-polarity, time-to-phase, and type-to-modality mappings are configurable, but keep mappings consistent to preserve deterministic behavior.