# Stage 140: E-Graph & Behavioral Hash (aq140_compile_egglog_and_behavioral_probes / DB-UNIT-05)

Deduplicates functionally identical code across languages via 32-input behavioral equivalence hashes and fuses verified DAG chains into fuel-capped Wasm macros.

- Atomic micro-queue: `aq140_compile_egglog_and_behavioral_probes` (visibility: `public_commons`)
- Backing database unit: `DB-UNIT-05` (`Typed Solution Graph & Pareto Composition Core`)
- Database cell: `graph-db.teleon.dev` (`teleon_core.teleon_weighted_graph_edges`, `teleon_core.verified_solution_dags`, `teleon_core.schema_bridge_adapters`)
- Claim row hydration: `single_self_contained_flat_task_row` (100% context inline, normalized writeback)
- Track 2 Sister queue (`SISTER-05`): `sq05-improve-composition-queue.teleon.dev` (Improve planner heuristics, promote recurring agentic subgraphs into cached deterministic macros, and add bridge tools.)
- Lanes: Bounded Equality Saturation, 32-Probe Behavioral Hash, WASI 0.3 Macro Fuse

## Execution engines & AI Agent freedom contract

- **Deterministic (0 model calls)**: `dijkstra_pareto_type_planner_v1` (Canonical 32-probe IO runner, affine port checker & macro packager (0 calls))
- **Hybrid (<=1 model call)**: `single_shim_bridge_synthesizer_v1`
- **AI Agent & Bot Fleet (1..6 calls)**: `novel_architecture_composer_v1` (Algebraic rewrite rule & cross-language equivalence author)
  - Contract: **Instructions + Resources + Freedom to search for new resources and new ways not bound by instructions**

## Database invariants

- Every executable vertex in a composed graph is a Loop; passive files never become model calls.
- Keep the no-extra-material baseline eligible in every Pareto comparison.

## External & internal bot fleet actions

- Cluster Python, Rust, JS, and Wasm implementations that produce identical outputs on 32 canonical probes
- Apply fuel-bounded algebraic rewrites before compiling hot component chains into single-hop macros
- Preserve exact typed port contracts and rollback pointers on every fused macro

## Sister self-tuning areas

- Promote high-traffic multi-node subgraphs into 0-model-call deterministic macro code_blocks
- Rebalance 6D Pareto cost weights (quality, tokens, latency, reliability, determinism, reuse)
- Add new algebraic port-shim templates and composition routines