home / skills / plurigrid / asi / say-ducklake-xor
This skill discovers and cross-references say or say mcp usage across DuckDB sources using bounded parallel XOR-based exploration with deterministic uniqueness.
npx playbooks add skill plurigrid/asi --skill say-ducklake-xorReview the files below or copy the command above to add this skill to your agents.
---
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
## SDF Interleaving
This skill connects to **Software Design for Flexibility** (Hanson & Sussman, 2021):
### Primary Chapter: 7. Propagators
**Concepts**: propagator, cell, constraint, bidirectional, TMS
### GF(3) Balanced Triad
```
say-ducklake-xor (○) + SDF.Ch7 (○) + [balancer] (○) = 0
```
**Skill Trit**: 0 (ERGODIC - coordination)
### Secondary Chapters
- Ch6: Layering
- Ch4: Pattern Matching
- Ch10: Adventure Game Example
### Connection Pattern
Propagators flow constraints bidirectionally. This skill propagates information.
## 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.This skill performs maximally parallel discovery across threads and DuckDB sources using XOR-derived seeds to guarantee deterministic uniqueness. It locates "say" and MCP-related patterns, cross-references findings with DuckDB lakes, and enforces GF(3) conservation checks to validate parallel merges. The implementation uses bounded parallelism and reproducible seed fan-out for deterministic behavior.
Given a root gay_seed, the skill fans out seed ⊕ i for i in [0, bound) and launches bounded parallel tasks to inspect threads and .duckdb files. Each worker searches for thread patterns ("say", "say mcp", voice flags) and runs lightweight DuckDB scans (SHOW TABLES, metadata cross-refs). Results include a trit value per source; the aggregator asserts Σ(trits) % 3 == 0 before committing merged records to avoid GF(3) drift.
How does XOR guarantee uniqueness?
XOR cancellation ensures seed ⊕ i = seed ⊕ j implies i = j, so distinct indices produce distinct derived seeds within the index space.
What happens if the GF(3) check fails?
A failing Σ(trits) % 3 assertion flags a conservation drift; the merge is aborted and results must be inspected for inconsistent trit assignments.