xiaohongshu
xiaohongshu
ducklake-walk
Ergodic random walks over DuckLake lakehouses with GF(3) triadic concurrent walkers. Society-of-mind coordination for schema exploration.
Full skill instructions
Ergodic random walk exploration of DuckDB/DuckLake schemas with concurrent Society-of-Mind walkers. Implements PageRank-style teleportation for irreducibility and GF(3)-balanced walker coordination.
| Stream | Trit | Role | Implementation |
|---|---|---|---|
| MINUS (-1) | Validator | Constraint verification, DuckLake semantics | duckdb-validator.sql |
| ERGODIC (0) | Coordinator | Random walk orchestration | ducklake-walk.clj |
| PLUS (+1) | Generator | Concurrent walker execution | mensi_walker.py |
Conservation: Σ trits = -1 + 0 + 1 = 0 (mod 3) ✓
| Gismu | Meaning | Component |
|---|---|---|
| pensi | think | PensiWalker - individual cognition |
| jimpe | understand | Jimpe - shared understanding |
| djuno | know | Djuno - knowledge units |
| mensi | sibling | Walker siblings in society |
| gunma | group | GunmaSociety - collective |
The walk follows a Markov chain with teleportation (PageRank-style):
P(teleport) = 0.15 # Random restart for ergodicity
P(follow_edge) = 0.85 × (has_neighbors ? 1 : 0)
P(forced_teleport) = 1 - P(teleport) - P(follow_edge)
Guarantees:
# Demo mode with in-memory schema
bb ducklake-walk.clj
# With existing DuckDB file
bb ducklake-walk.clj /path/to/lakehouse.duckdb
# Run concurrent walkers
python mensi_walker.py
# Interactive REPL
python jimpe_repl.py
LOAD ducklake;
ATTACH 'ducklake:metadata.duckdb' AS lake (DATA_PATH './data');
-- Create walk history table
CREATE TABLE lake.main.walk_history (
step_id INTEGER,
from_state VARCHAR,
to_state VARCHAR,
trit INTEGER,
walk_time TIMESTAMPTZ
);
-- Verify GF(3) conservation
SELECT SUM(trit) % 3 AS conservation FROM lake.main.walk_history;
-- Should return 0
| Metric | Target | Description |
|---|---|---|
| Coverage | >80% | Unique tables visited / total tables |
| Entropy | ~ln(N) | Shannon entropy of visit distribution |
| Edge ratio | ~38% | FK-following vs teleportation |
| GF(3) sum | 0 mod 3 | Conservation across all trits |
skills/ducklake-walk/
├── SKILL.md # This file
├── ducklake-walk.clj # Babashka ergodic walker
├── mensi_walker.py # Python concurrent walkers
├── jimpe_repl.py # Interactive REPL
└── demo_interleaving.py # Thread visualization
=== DuckLake Random Walk ===
GF(3) Color: ERGODIC (0) - Neutral Coordinator
Tables found: 8
Random restart probability: 0.15
Starting at: ducklake.products
Step 0: ducklake.products (rows: 4) -> ducklake.categories [edge]
Step 1: ducklake.categories (rows: 4) -> ducklake.products [edge]
Step 2: ducklake.products (rows: 4) -> ducklake.users [teleport]
...
=== Ergodicity Analysis ===
Coverage: 100.0%
Edge transitions: 38.0%
Teleportations: 62.0%
Entropy: 1.994 / 2.079 (max)
Ergodic: YES
class GF3Trit(IntEnum):
MINUS = -1 # Validator (cold hue 270°)
ERGODIC = 0 # Coordinator (neutral hue 180°)
PLUS = 1 # Generator (warm hue 30°)
# Role-specific behavior weights
PLUS: explore=0.7, validate=0.1, synthesize=0.2
MINUS: explore=0.2, validate=0.6, synthesize=0.2
ERGODIC: explore=0.3, validate=0.2, synthesize=0.5
duckdb-timetravel (trit: 0) - Temporal versioningduckdb-ies (trit: +1) - Interactome analyticsrandom-walk-fusion (trit: +1) - Skill graph navigationacsets (trit: 0) - Algebraic databasesThis skill connects to the K-Dense-AI/claude-scientific-skills ecosystem:
graph-theory: 38 citations in bib.duckdbThis 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
The skill participates in triads satisfying:
(-1) + (0) + (+1) ≡ 0 (mod 3)
This ensures compositional coherence in the Cat# equipment structure.
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