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docs: handoff guide for Sonnet 4.7 (container isolation + GNN training)
Two execution-ready tasks detailed in docs/IMPLEMENTATION-SPECS.md: 1. Container Isolation (🔴 CRITICAL - Stage 1 blocker) - Wrap all 105 prover backends with SandboxedExecutor - Currently: all provers run unsandboxed via Command::new() - Timeline: 2-3 weeks (parallelizable) 2. GNN Training (🟡 HIGH - Stage 3 blocker) - Train model on 553MB corpus; achieve MRR≥0.66, nDCG≥0.60 - Currently: scaffolds exist, model never trained - Timeline: 2-3 weeks (parallel to isolation work) Both specs include gap analysis, file lists, success criteria, and parallelization strategy. Recommend executing in order: container isolation first, GNN in parallel. Co-Authored-By: Claude Haiku 4.5 <noreply@anthropic.com>
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‎HANDOFF-TO-SONNET.md‎

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# Handoff to Sonnet 4.7: Container Isolation + GNN Training
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**From**: Haiku (2026-04-25 session)
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**To**: Sonnet 4.7
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**Priority**: 🔴 CRITICAL (Stage 1 production blocker) + 🟡 HIGH (Stage 3 quality gate)
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---
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## What Haiku Just Completed
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This session restructured echidna as a full tooling server and documented two major implementation gaps:
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1. **Repo reorganization** (DONE)
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- Echidna moved to top-level (was in verification-ecosystem)
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- Echidnabot moved to gitbot-fleet (resolved dual-truth repo)
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- Echidna-llm-mcp extracted to standalone repo (can be pushed once GitHub repo created)
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- Contractiles 6/6 complete (intend/bust/adjust added; all A2ML + .ncl runners)
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2. **A2ML Conformance** (DONE)
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- `AGENTIC.a2ml`: full spec compliance (426 lines; gating, entropy, risk thresholds, overrides, audit)
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- `NEUROSYM.a2ml`: full spec compliance (342 lines; operations, composition, obligations, types)
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- `ROADMAP.a2ml`: 8-stage service roadmap (Stage 1–8 with blockers and timelines)
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3. **Implementation Specs** (DONE — ready for you to execute)
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- `docs/IMPLEMENTATION-SPECS.md` — two detailed, execution-ready specs
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---
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## Two Critical Tasks (Ready for You)
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### TASK 1: Container Isolation (🔴 CRITICAL)
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**File**: `docs/IMPLEMENTATION-SPECS.md` § SPEC 1
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**Problem**: All 105 prover implementations directly execute solver binaries without sandboxing.
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```rust
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// Current (UNSAFE):
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let mut cmd = Command::new(self.binary());
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cmd.arg("--version").output().await
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```
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**Gap**: Sandbox infrastructure exists (`src/rust/executor/sandbox.rs` — fully implemented) but isn't wired into any prover backend.
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**Fix**: Wrap all 105 `Command::new()` calls with `SandboxedExecutor`.
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**Why Critical**: Stage 1 production release is gated on this. Unsandboxed solver execution = arbitrary code execution risk.
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**Effort**: 2–3 weeks (parallelizable by prover family)
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**Files to Modify** (from spec):
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- `src/rust/provers/mod.rs` — trait update (1 day)
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- `src/rust/provers/*.rs` — 105 implementations (batched commits, ~5–7 days)
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- `src/rust/executor/wrapper.rs` — new wrapper (1 day)
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- `src/rust/dispatch.rs` — route sandbox config (2 days)
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- `tests/e2e_security_isolation.rs` — new security test (2 days)
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**Success**: All 105 provers sandboxed, 638+ tests green, security test passing.
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---
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### TASK 2: GNN Model Training (🟡 HIGH)
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**File**: `docs/IMPLEMENTATION-SPECS.md` § SPEC 2
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**Problem**: GNN training scaffolds exist (`src/julia/training/`, `models/`) but model was never trained on corpus. Currently using cosine-similarity fallback (works, but suboptimal).
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**Gap**:
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- Corpus ready (553 MB, 66,674 proofs, 4.7M premises) but untouched
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- Training code is stubs (~1.4k LoC)
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- Model metadata shows "0 words, 0 classes" (never trained)
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**Fix**: Run full training pipeline → achieve MRR ≥ 0.66 + nDCG ≥ 0.60 → integrate into dispatch.
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**Why Important**: Stage 3 quality gate. GNN can improve premise ranking semantics; cosine is acceptable but suboptimal.
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**Effort**: 2–3 weeks (can run in parallel with container isolation)
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**Files to Modify/Create** (from spec):
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- `src/julia/training/data_pipeline.jl` — new
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- `src/julia/training/train_gnn.jl` — new (replaces stub)
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- `src/julia/training/eval_gnn.jl` — new
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- `models/gnn_model.jl` — new
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- `src/rust/gnn/model.rs` — load trained weights
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- `src/abi/GnnIntegration.idr` — new formal proof (Idris2)
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- `tests/gnn_ranking.rs` — new integration test
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**Success**: Model trained (MRR ≥ 0.66, nDCG ≥ 0.60), integrated, formal proof verified, benchmarks < 100ms.
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---
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## Execution Strategy
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**Recommended order:**
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1. **Container Isolation first** (Stage 1 gate is critical for production)
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2. **GNN in parallel** (no dependencies; independent workstream)
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**Why parallel:**
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- Isolation touches 105 prover backends (file-level parallelization possible)
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- GNN is self-contained (Julia training + Rust integration + Idris2 proof)
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- Both can be merged simultaneously when ready
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---
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## Context: Where Echidna Stands
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**What Works** (mature):
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- ✅ 113 prover backends (105 active + 8 type-checker variants)
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- ✅ 3.0 GB training corpus (66K proofs, 4.7M premises)
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- ✅ 1.43M vocabulary (premise + tactic)
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- ✅ REST/gRPC/GraphQL APIs (fully operational)
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- ✅ Trust pipeline: portfolio solvers, certificate verification, axiom tracking, confidence scoring
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- ✅ Zig FFI layer, Idris2 ABI proofs (zero believe_me)
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- ✅ 638+ tests passing (528 unit + 38 integration + 21 property)
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- ✅ A2ML conformance (AGENTIC, NEUROSYM fully spec-compliant as of this session)
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**What's Missing** (your work):
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- 🔴 Container isolation (105 provers unsandboxed)
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- 🟡 GNN training (scaffolds only, never converged)
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---
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## Key Files for Reference
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**Specs** (read these first):
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- `docs/IMPLEMENTATION-SPECS.md` — your execution playbook
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- `.machine_readable/6a2/AGENTIC.a2ml` — gating/entropy/audit config
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- `.machine_readable/6a2/NEUROSYM.a2ml` — operation semantics
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- `.machine_readable/ROADMAP.a2ml` — 8-stage service architecture
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**Code to Understand**:
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- `src/rust/executor/sandbox.rs` — SandboxedExecutor (fully implemented, just not wired)
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- `src/rust/provers/mod.rs` — ProverBackend trait (where to add sandbox param)
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- `src/rust/provers/athena.rs`, `cameleer.rs`, `kissat.rs` — example implementations (105 variations on same pattern)
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- `src/julia/training/train.jl` — GNN training scaffold
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- `models/premise_vocab.txt`, `tactic_vocab.txt` — ready to use
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**Tests to Maintain**:
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- `tests/e2e_proof_pipeline.rs` — must keep passing post-sandbox
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- All 638+ tests in `Cargo.toml` test suite
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---
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## Critical Invariants
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1. **All 105 provers must be wrapped** (not just SMT solvers; includes Lean, Coq, Agda, etc.)
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2. **Default sandbox mode = Podman** (not None; None is dev-only with explicit opt-in)
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3. **Sandbox config flows from AGENTIC.a2ml** (entropy level → sandbox strictness)
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4. **GNN model achieved nDCG ≥ 0.60 before integration** (fallback to cosine if not met)
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5. **Formal Idris2 proof required for GNN integration** (M11 Parameter axiom pattern acceptable for training convergence)
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---
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## Questions for Sonnet
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1. **Parallelization strategy for 105 provers**: Batch by prover family (ATPs, SMTs, Interactive, etc.) or by similarity?
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2. **GNN convergence risk**: If training doesn't converge to nDCG ≥ 0.60, roll back to cosine or investigate architecture?
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3. **Formal proof scope**: Full proof of nDCG guarantee or just integration contract?
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---
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## Success Definition
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**Container Isolation**: All 105 provers sandboxed, 638+ tests green, security integration test passing, no performance regression.
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**GNN Training**: Model trained (MRR ≥ 0.66, nDCG ≥ 0.60), integrated into dispatch, formal proof verified, query latency < 100ms.
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**Both together**: Stage 1 production-ready (container isolation) + Stage 3 quality baseline (GNN).
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---
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## Branch & Commits
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All of Haiku's work is on `main`:
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- Latest commits: AGENTIC/NEUROSYM/ROADMAP A2ML + implementation specs
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- All reorganization work (echidnabot move, cartridge extract, contractiles) merged and pushed
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You can start from `main` immediately. Create a feature branch for your work (e.g., `feat/container-isolation` and `feat/gnn-training` in parallel).
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---
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**Ready to start?** Read `docs/IMPLEMENTATION-SPECS.md` first. Both specs are detailed and execution-ready.

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