By name: datalog-fixpoint description: Datalog bottom-up fixpoint iteration for recursive queries version: 1.0.0
Datalog Fixpoint Skill
Bottom-up fixpoint iteration for recursive Datalog queries without explicit recursion.
Core Concept
Datalog computes fixpoints via iterative saturation:
T^0(∅) → T^1 → T^2 → ... → T^ω (fixpoint)
Where T is the immediate consequence operator.
Scientific Skill Interleaving
This skill connects to the K-Dense-AI/claude-scientific-skills ecosystem:
Dataframes
- polars [○] via bicomodule
- High-performance dataframes
Bibliography References
algorithms: 19 citations in bib.duckdb
Cat# Integration
Fixpoint computation maps to Cat# via coalgebraic semantics:
Trit: 0 (ERGODIC - iterative bridge)
Home: Prof (profunctors/bimodules)
Poly Op: ⊗ (parallel saturation)
Kan Role: Adj (Kleisli adjunction)
GF(3) Naturality
Datalog fixpoint iteration is inherently ERGODIC:
- Each iteration step is a natural transformation
- Convergence = reaching the terminal coalgebra
- The fixpoint IS the bicomodule equilibrium