From asi
Explores DuckDB/DuckLake schemas using ergodic random walks with GF(3) triadic concurrent walkers in Clojure/Babashka, Python, and SQL for coverage and conservation checks.
npx claudepluginhub plurigrid/asi --plugin asiThis skill uses the workspace's default tool permissions.
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.
Injects context via chaotic random walks between and within four clusters of local DuckDB databases modeled as coupled quadruple pendula, maintaining GF(3) conservation.
Executes raw SQL or natural language queries against attached DuckDB databases or ad-hoc files. Manages session state, schema retrieval, and result size estimation.
Builds and runs OpenDuck distributed DuckDB with differential storage via Postgres/object store, hybrid local/remote query execution, and transparent ATTACH for remote databases. Scales DuckDB for distributed workloads.
Share bugs, ideas, or general feedback.
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.