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say-ducklake-xor

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
10
Hot score
84
Updated
March 20, 2026
Overall rating
C3.8
Composite score
3.8
Best-practice grade
A88.0

Install command

npx @skill-hub/cli install plurigrid-asi-say-ducklake-xor

Repository

plurigrid/asi

Skill path: skills/say-ducklake-xor

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

Works across

Claude CodeCodex CLIGemini CLIOpenCode

Favorites: 0.

Sub-skills: 0.

Aggregator: No.

Original source / Raw SKILL.md

---
name: say-ducklake-xor
description: Parallel thread/DuckLake discovery with XOR uniqueness from gay_seed. Finds "say" or MCP usage, cross-refs with all DuckDB sources, launches bounded parallel ops.
version: 1.0.0
---


# Say-DuckLake XOR Discovery

**Maximally parallel discovery with deterministic uniqueness guarantees.**

## Core Invariants

```
∀ i,j ∈ [0, bound): i ≠ j ⟹ seed ⊕ i ≠ seed ⊕ j   (XOR uniqueness)
∀ parallel ops: same gay_seed ⟹ same colors        (SPI guarantee)
Σ(trits) ≡ 0 (mod 3)                                (GF(3) conservation)
```

## Usage

```bash
# Find all "say" usage in threads, cross-ref with DuckLakes
python scripts/say_ducklake_xor.py

# With explicit seed and parallelism bound
python scripts/say_ducklake_xor.py --seed 1069 --bound 27

# XOR verification mode
python scripts/say_ducklake_xor.py --verify-xor
```

## Architecture

```
┌─────────────────────────────────────────────────────────────┐
│                    gay_seed (root)                          │
├─────────────────────────────────────────────────────────────┤
│  XOR Fan-Out (bounded)                                      │
│  ┌─────────┐ ┌─────────┐ ┌─────────┐     ┌─────────┐       │
│  │seed⊕0   │ │seed⊕1   │ │seed⊕2   │ ... │seed⊕n-1 │       │
│  │(thread) │ │(duck_0) │ │(duck_1) │     │(duck_n) │       │
│  └────┬────┘ └────┬────┘ └────┬────┘     └────┬────┘       │
│       │           │           │               │             │
│       ▼           ▼           ▼               ▼             │
│  ┌─────────────────────────────────────────────────────┐   │
│  │              Parallel Executor (async)               │   │
│  │  - Thread search: find_thread("say" OR "say mcp")   │   │
│  │  - DuckDB scan: SHOW TABLES for each .duckdb        │   │
│  │  - Cross-reference: match concepts/timestamps       │   │
│  └─────────────────────────────────────────────────────┘   │
│                           │                                 │
│                           ▼                                 │
│  ┌─────────────────────────────────────────────────────┐   │
│  │              GF(3) Conservation Check                │   │
│  │  Σ(trits) mod 3 = 0 ⟹ valid parallel merge         │   │
│  └─────────────────────────────────────────────────────┘   │
└─────────────────────────────────────────────────────────────┘
```

## XOR Uniqueness Proof

For bound `n` parallel operations from `seed`:

```python
def xor_unique(seed: int, bound: int) -> bool:
    """XOR with distinct indices yields distinct seeds."""
    seen = set()
    for i in range(bound):
        derived = seed ^ i
        if derived in seen:
            return False  # Collision!
        seen.add(derived)
    return True

# Always true for i,j < 2^64 and i ≠ j:
# seed ⊕ i = seed ⊕ j ⟹ i = j (XOR cancellation)
```

## DuckLake Sources

Auto-discovered from `~/ies/**/*.duckdb`:

| Source | Purpose | Trit |
|--------|---------|------|
| `pigeons_spi.duckdb` | Derivation chains, GF(3) invariants | 0 |
| `unified_thread_lake.duckdb` | Amp thread archive | +1 |
| `ananas.duckdb` | Book/paper downloads | -1 |
| `hatchery.duckdb` | Scheme eggs metadata | 0 |
| `bib.duckdb` | Bibliography entries | +1 |

## Thread Patterns

Searches for threads containing:
- `say` - macOS TTS usage
- `say mcp` - MCP tool with speech
- `say-narration` - Skill usage
- `say -v` - Voice specification

## Integration with PigeonsGayBridge

```julia
using .PigeonsGayBridge

# XOR fan-out with SPI guarantee
seeds = [GAY_SEED ⊻ UInt64(i) for i in 0:26]
chains = [unworld_chain(s, 10) for s in seeds]

# All chains have deterministic colors
# Cross-machine reproducibility via SPI
```

## Cross-Reference Schema

```sql
CREATE TABLE say_ducklake_xor (
    xor_index INTEGER PRIMARY KEY,
    seed UBIGINT NOT NULL,
    source_type VARCHAR(10),  -- 'thread' or 'duckdb'
    source_id VARCHAR(64),
    trit TINYINT,
    hex VARCHAR(7),
    matched_at TIMESTAMP DEFAULT CURRENT_TIMESTAMP,
    UNIQUE(seed)  -- XOR guarantees uniqueness
);
```

## Bounded Parallelism

```python
import asyncio
from concurrent.futures import ThreadPoolExecutor

async def parallel_xor_discovery(seed: int, bound: int):
    """Launch bounded parallel ops with XOR uniqueness."""
    loop = asyncio.get_event_loop()
    
    with ThreadPoolExecutor(max_workers=min(bound, 8)) as executor:
        futures = [
            loop.run_in_executor(executor, discover_one, seed ^ i, i)
            for i in range(bound)
        ]
        results = await asyncio.gather(*futures)
    
    # Verify GF(3) conservation
    trits = [r['trit'] for r in results]
    assert sum(trits) % 3 == 0, "GF(3) drift detected"
    
    return results
```

## References

- [PigeonsGayBridge.jl](file:///Users/bob/ies/PigeonsGayBridge.jl) - SPI via unworld dynamics
- [ducklake_discover.py](file:///Users/bob/ies/music-topos/scripts/ducklake_discover.py) - Discovery patterns
- [SUBOBJECT_CLASSIFIER_RECURRENCES.md](file:///Users/bob/ies/SUBOBJECT_CLASSIFIER_RECURRENCES.md) - Recurrence types



## 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.
say-ducklake-xor | SkillHub