# Zaxy: Event-Sourced Temporal Knowledge Graph Fabric

## Problem Statement

Markdown files + vector DBs are the dominant approach for agent persistent context, but they are fundamentally lossy and inefficient:

- **No relational reasoning**: Vector similarity can't do multi-hop traversal or follow causal chains.
- **No temporal awareness**: Can't answer "What was true then vs. now?" — facts overwrite each other silently.
- **Non-replayable**: Context is chunked and flattened; you can't reconstruct how the agent arrived at a decision.
- **Un-auditable**: No provenance chain for compliance or debugging.

> **Current architecture (read this first).** The controlling architecture docs
> are [docs/architecture.md](docs/architecture.md) and [README.md](README.md).
> The default projection backend is the **embedded LadybugDB** store (in-process,
> no external service); Neo4j, pgGraph, and LatticeDB are optional backends
> selected via `PROJECTION_BACKEND`, behind one pluggable projection contract.
> Some ADRs below predate the embedded-default move and are kept as historical
> decision records — where an older note says "Neo4j", read "the projection
> backend (embedded by default)".

## Architecture Decision Record

### ADR-1: Event-Sourced Foundation

**Decision**: Use Eventloom's append-only JSONL as the immutable source of truth.

**Rationale**:
- Hash-chain integrity (tamper-evident).
- Deterministic replay.
- Zero write overhead (local file append).
- Cross-process locking already solved.

**Trade-off**: Single-writer per file. For multi-agent distributed setups, shard by session or add a log aggregation layer later.

### ADR-2: Hybrid Extraction (Rule-Based + LLM Fallback)

**Decision**: Extract entities/relations from events using registered rule-based extractors first, LLM fallback only for unstructured events.

**Rationale**:
- Eventloom events are strongly typed (`goal.created`, `task.proposed`, etc.).
- Typed events map deterministically to graph schema.
- Reduces LLM extraction cost by 60–80%.
- Faster ingestion (<50ms vs 500ms–2s for LLM).

**Trade-off**: New event types require writing an extractor. This is intentional — it forces schema discipline.

### ADR-3: Direct Neo4j Cypher vs. Graphiti Abstraction

**Decision**: Use the official `neo4j` Python driver with custom Cypher rather than Graphiti's high-level `add_episode` API.

**Rationale**:
- Full control over bi-temporal schema (`valid_from`, `valid_to`).
- Our extraction engine already produces structured `ExtractedEntity`/`ExtractedEdge` objects.
- Graphiti's LLM-based extraction is redundant with our hybrid extractor.
- Graphiti's hybrid search (vector + BM25 + traversal) can be replicated with native Neo4j indexes.

**Trade-off**: We maintain more Cypher. Mitigated by keeping queries simple and tested.

**Update**: the projection layer is now a pluggable contract. Embedded LadybugDB
is the default backend; Neo4j-direct-Cypher is one optional backend among several
(pgGraph, LatticeDB).

### ADR-4: Hybrid Retrieval (Exact + Keyword + Traversal)

**Decision**: Query router fuses three strategies with configurable weights.

**Rationale**:
- **Exact**: Fast lookup when the query is an entity name.
- **Keyword/BM25**: Full-text for semantic similarity on names/summaries.
- **Traversal**: Multi-hop expansion from top keyword hits.
- Each covers blind spots of the others.

**Trade-off**: Fusion adds ~10–50ms latency. Acceptable for agent context quality.

### ADR-5: Pathlight for Observability (Not Storage)

**Decision**: Pathlight can trace every memory operation when enabled, but does not store context itself.

**Rationale**:
- Eventloom = durable history.
- Projection backend (embedded LadybugDB by default) = structured reasoning layer.
- Pathlight = execution tracing + breakpoints + diff.
- Clean separation of concerns.

**Trade-off**: Extra network call per traced operation. Mitigated by async batching and optional disabling.

### ADR-6: MCP as Primary Interface

**Decision**: Expose memory via MCP tools (`memory_append`, `memory_query`, `memory_replay`, `memory_invalidate`).

**Rationale**:
- Framework-agnostic (LangGraph, CrewAI, AutoGen, Claude Desktop, etc.).
- Standardized schema discovery and type safety.
- One-click integration via `mcpServers` config.

**Trade-off**: Requires MCP client support. Major frameworks already have it (2025+).

## Tech Stack

| Layer | Technology | Version |
|-------|-----------|---------|
| Language | Python | 3.11+ |
| Graph projection (default) | embedded LadybugDB | pinned |
| Optional graph backends | Neo4j / pgGraph / LatticeDB | — |
| Validation | Pydantic | 2.7+ |
| MCP Server | mcp (official Python SDK) | 1.0+ |
| Observability | pathlight (Python SDK) | 0.1+ |
| CLI | typer | 0.12+ |
| Testing | pytest + pytest-asyncio + pytest-cov | 8.0+ |
| Lint/Format | ruff | 0.4+ |
| Types | mypy | 1.10+ |

## Directory Structure

```
zaxy/
├── pyproject.toml              # Project config, deps, tool settings
├── docker-compose.yml          # Neo4j + test services
├── AGENTS.md                   # This file
├── src/zaxy/
│   ├── __init__.py             # Public API exports
│   ├── __main__.py             # CLI entrypoint (`python -m zaxy`)
│   ├── core.py                 # MemoryFabric orchestrator
│   ├── event.py                # Eventloom JSONL I/O + hash chain
│   ├── extract.py              # Hybrid extraction engine + registry
│   ├── embedded_graph_store.py # Embedded LadybugDB backend (default)
│   ├── graph.py                # Neo4j projection backend (optional)
│   ├── query.py                # Hybrid retrieval router
│   ├── mcp_server.py           # MCP stdio/sse server
│   └── trace.py                # Pathlight observability hooks
├── tests/
│   ├── conftest.py             # Shared fixtures
│   ├── test_event.py           # Event log I/O + integrity
│   ├── test_extract.py         # Rule-based extractors
│   ├── test_graph.py           # Neo4j operations (mock + integration)
│   ├── test_query.py           # Query routing + fusion
│   ├── test_mcp.py             # MCP protocol compliance
│   └── test_trace.py           # Pathlight span emission
├── examples/
│   └── langgraph_memory.py     # Full LangGraph integration demo
└── scripts/
    └── setup_neo4j_indexes.cypher  # Manual index setup
```

## Development Workflow

1. **Write the test first** (Karpathy rule). Every public function must have a test before the implementation is considered complete.
2. **Unit tests mock external deps** (projection backends, Pathlight, filesystem).
3. **Integration tests use Docker** (marked `@pytest.mark.integration`).
4. **Coverage gate: ≥90%** (enforced by CI).
5. **Lint/format with ruff**, type-check with mypy.

## Testing Strategy

| Test Type | Scope | External Deps | Marker |
|-----------|-------|---------------|--------|
| Unit | Single function/class | Mocked | `unit` (default) |
| Integration | Cross-module + real DB | optional backend (e.g. Neo4j) Docker | `integration` |
| E2E | Full agent run | Full Docker stack | `e2e` (future) |

Run unit tests: `pytest`
Run integration tests: `pytest -m integration`
Run with coverage: `pytest --cov` (default in pyproject.toml)

## Integration Points

### Eventloom (Bottom Layer)
- **Input**: Zaxy reads `.eventloom/*.jsonl` files.
- **Output**: Zaxy appends projection metadata back to Eventloom (optional).
- **Contract**: `Event` Pydantic model matches Eventloom JSONL schema.

### Projection backend (Core Memory)
- **Default**: embedded LadybugDB (in-process; no external service).
- **Optional**: Neo4j (`bolt://localhost:7687`, auth `neo4j/testpassword` local dev), pgGraph, LatticeDB — selected via `PROJECTION_BACKEND`.
- **Schema**: `Entity(name, entity_type, valid_from, valid_to, ...)` + `RELATES(relation_type, valid_from, valid_to)`
- **Indexes**: Vector index (embedding), Fulltext index (BM25)

### Pathlight (Top Layer)
- **Collector**: `http://localhost:4100`
- **Dashboard**: `http://localhost:3100`
- **Traced Operations**: `append`, `query`, `replay`, `invalidate`
- **Eventloom Panel**: Pathlight renders Eventloom exports natively.

### MCP (Interface Layer)
- **Transport**: stdio (default) or SSE
- **Tools**:
  - `memory_append(event_type, actor, payload, thread?)`
  - `memory_query(query, temporal_filter?, limit?)`
  - `memory_replay(session_id, from_seq?)`
  - `memory_invalidate(entity_name, entity_type, invalid_at)`

## Performance Targets

| Metric | Target | Notes |
|--------|--------|-------|
| Event append | <50ms | Local JSONL write + lock |
| Rule-based extraction | <10ms | Pure Python dict mapping |
| Projection upsert | <100ms | MERGE + index lookup |
| Hybrid query | <200ms | Parallel exact + keyword + traversal |
| Total context retrieval | <300ms | End-to-end |
| Token reduction vs. chunk RAG | 70–90% (target; unvalidated) | Structured paths vs. raw text. Validate with `scripts/chunk_rag_token_compare.py` — quality-controlled (token reduction at *equal answer-bearing recall*, pinned chunk-RAG baseline) — driven by a gold-labeled QA dataset through the gated benchmark. |

## Current Status

- [x] Project scaffold (pyproject.toml, docker-compose.yml)
- [x] Eventloom JSONL I/O with hash-chain integrity
- [x] Hybrid extraction engine with rule registry
- [x] Neo4j graph store (schema, upsert, retrieval, invalidation)
- [x] Hybrid query router (exact + keyword + traversal)
- [x] Pathlight tracing integration
- [x] MCP server implementation
- [x] `MemoryFabric` orchestrator wiring
- [x] CLI entrypoint (`zaxy serve`, `zaxy replay`, `zaxy compact`)
- [x] LangGraph adapter example
- [x] CI/CD (GitHub Actions)
- [x] Operational runbooks
- [x] Configuration management (pydantic-settings, env vars)
- [x] Docker containerization (Dockerfile + compose + SSE production command)
- [x] Structured logging (console + JSON)
- [x] Graceful shutdown (SIGTERM/SIGINT handling)
- [x] Production secrets management (Docker secrets + `*_FILE` config)
- [x] TLS for Neo4j (generated certs + TLS compose service + integration test)
- [x] Multi-agent session sharding (SessionManager + MemoryFabric/MCP wiring + graph session isolation)
- [x] Prometheus metrics
- [x] Vector index and vector similarity search in query router
- [x] SSE transport for MCP daemon mode
- [x] Embedding generation pipeline (deterministic local provider + entity/query vectors)
- [x] True temporal versioning for reasserted facts and multi-version entity state
- [x] Remote MCP security (SSE bearer auth + per-client session scopes)
- [x] Operational backup/restore/log-rotation scripts backed by tests
- [x] Competitive benchmark suite vs. flat JSONL context baseline
- [x] Hosted embedding provider adapter with secret-managed credentials
- [x] Remote deployment environment validation for MCP/SSE
- [x] Go-live readiness checklist and release gate
- [x] Release packaging and versioned distribution artifacts
- [x] Public static site and expanded documentation set
- [x] Eventloom provenance citations on graph-backed retrieval results
- [x] Append-time secret redaction and payload classification
- [x] MMR diversity and explainable score metadata in query router
- [x] Filesystem document ingestion with source path and line citations
- [x] Sanitized transcript ingestion and replay-to-context assembly API
- [x] Query expansion and temporal-aware retrieval scoring policies
- [x] Configurable scoring profiles and local lexical reranker provider
- [x] Hosted OpenAI-compatible and local HTTP reranker providers
- [x] Graceful degradation for graph, embedding, vector, and reranker outages
- [x] Context lifecycle hooks for after-turn assembly, handoff bundles, and subagent cleanup
- [x] OIDC/JWKS remote MCP authentication for public multi-tenant deployments
- [x] Degraded-mode Prometheus metrics and alerting guidance
- [x] Extractor authoring templates and auditable schema migration tooling
- [x] Frozen benchmark workload fingerprints and external comparison disclosures
- [x] Representative benchmark suite for temporal, document, transcript, and mixed workloads
- [x] Geometry-aware consolidation roadmap for identity-preserving compaction
- [x] Consolidation-collapse benchmark lane and identity-recall metric
- [x] `zaxy compact --audit` safety checks for integrity, identity recall, and citations
- [x] Medoid/exemplar projection storage with Eventloom and source backpointers
- [x] Context assembly warnings for unsupported compacted/projection context
- [x] Projection artifact retrieval as cited local routing candidates
- [x] Okapi BM25 baseline in the live benchmark harness
- [x] Automatic compaction projection discovery under Eventloom directories
- [x] First-run MCP client config and framework handoff adapter helpers
- [x] Local-first embedding/reranker setup helpers
- [x] Extractor schema-pack examples for common agent event taxonomies
- [x] Remote MCP rate limiting and audit event export
- [x] Domain-separated MCP defaults to avoid cross-project `default` session bleed
- [x] File-level codebase mapping as Eventloom-backed graph projection
- [x] Symbol-level codebase mapping for functions, classes, types, and imports
- [x] Local code dependency mapping from resolved imports to source files
- [x] Python call-site mapping with resolved symbol call edges
- [x] Static Python test coverage links from tests to imported production symbols
- [x] JavaScript and TypeScript call-site mapping for same-file and imported local symbols
- [x] Go, Rust, and Java same-file call-site mapping
- [x] Go cross-file call resolution for local package-qualified imports
- [x] Rust cross-file call resolution for simple `use crate::module::symbol` imports
- [x] Java cross-file call resolution for imported local classes
- [x] Workspace genesis entry process with profile discovery and write instructions
- [x] Workspace instruction bootstrap and drift events for agent guidance files
- [x] Initial lifecycle hook taxonomy for tool calls, command results, and file edits
- [x] Automatic redacted MCP tool-call lifecycle capture
- [x] Lifecycle capture for compaction, subagent completion, and session end
- [x] Minimal static Eventloom/session viewer for bootstrap and lifecycle inspection
- [x] Local onboarding doctor for Eventloom, MCP defaults, viewer, local profile, and config posture
- [x] Non-destructive temporal retention and decay-aware retrieval policies
- [x] Direct agent integration templates for LangGraph, CrewAI, and AutoGen
- [x] Retention metadata extraction and reinforcement events for decay-aware retrieval
- [x] Retrieval feedback events that reinforce used context
- [x] MCP tool support for retrieval feedback events
- [x] Observer hook config and lightweight hook-event capture
- [x] Hook protocol documentation and doctor onboarding guidance
- [x] Safe hook config write mode with no-overwrite default
- [x] Searchable hook checkpoint events with summary and reason metadata
- [x] Hook installation detection and supported-client matrix
- [x] Pruned stale direct-Neo4j demo scripts superseded by doctor, hooks, and MCP smoke coverage
- [x] Hook status and heartbeat health checks for observable lifecycle capture
- [x] Unified `zaxy init` onboarding orchestrator for MCP config, local profile, hooks, genesis, heartbeat, doctor, and hook status
- [x] Explicit `zaxy init --infra check|start` local Neo4j bootstrap actions
- [x] Structured onboarding next steps in text and JSON output
- [x] Pre-MCP CLI install guidance and resolved executable paths in generated MCP config
- [x] Installed `zaxy` console-script preference for generated MCP executable paths
- [x] `zaxy init --preset local-claude` shortcut for the explicit local onboarding path
- [x] MCP client install target verification matrix for Claude Code, Cursor, VS Code, and Codex
- [x] Safe project-local MCP config write-and-merge helpers for Claude Code, Cursor, and VS Code
- [x] Codex MCP install command rendering via `codex mcp add`
- [x] Explicit Codex TOML merge support for user and trusted-project config scopes
- [x] First-class Hermes Agent MCP config rendering and workspace-neutral YAML merge support
- [x] Claude Code local hook merge and parsed install detection coverage
- [x] Focused full-suite integration check helper that starts, requires, or skips Neo4j test services explicitly
- [x] Optional framework extras and install hints for LangGraph, CrewAI, and AutoGen
- [x] Framework integration support registry with maturity and native-adapter status discovery
- [x] LongMemEval public-memory benchmark workload for MemPalace-comparable identity recall
- [x] BM25 lexical fusion for Zaxy LongMemEval benchmark retrieval
- [x] MemPalace-comparable temporal recall benchmark lane with citation coverage reporting
- [x] MemPalace-comparable source recall benchmark lane with target/distractor source scoring
- [x] MemPalace-comparable graph traversal benchmark lane with goal-task-completion path scoring
- [x] MemPalace-comparable context-collapse benchmark lane with noisy transcript and checkpoint recovery scoring
- [x] First-class verbatim Eventloom retrieval with MCP and MemoryFabric access
- [x] Source-aware context assembly with reserved verbatim Eventloom retrieval lane
- [x] Configurable and observable context assembly source-recall policy
- [x] Read-only `zaxy memory status` for Eventloom session integrity and latest hashes
- [x] Read-only `zaxy memory log` for recent Eventloom events with JSON output
- [x] Read-only `zaxy memory diff` for Eventloom sequence ranges
- [x] Hash-linked Eventloom provenance path projected into Neo4j with `NEXT_EVENT`/`PREVIOUS_EVENT`
- [x] Eventloom-vs-Neo4j graph projection integrity status with lag and chain-link checks
- [x] Intelligent active memory working-set projection in context assembly
- [x] First-class Memory Checkout contract for current cited prompt state
- [x] Eventloom-backed memory refs and checkout-by-ref support
- [x] Normalized command and file-edit observation capture for hooks
- [x] Hook and doctor observation coverage reporting for automatic capture gaps
- [x] Hook-event sinks for tool-call and transcript-turn automatic capture
- [x] Native-preview LangGraph adapter for context projection, observations, and retrieval feedback
- [x] Native-preview CrewAI adapter for task context projection, task result capture, tool observations, and retrieval feedback
- [x] Codex in-session `/resume` duplicate MCP process troubleshooting guidance
- [x] Competitive positioning roadmap against MemPalace-style memory systems
- [x] LongMemEval workload chunking for hosted embedding input limits
- [x] Persistent embedding cache and progress output for long-running live benchmarks
- [x] Local onboarding happy-path infrastructure profile for plain localhost Neo4j with cleared TLS/password-file overrides
- [x] Model-facing memory capability manifest with ambient checkout/capture/feedback loop guidance
- [x] Deterministic capture as default onboarding mode with optional packet/hybrid capture and local Codex preset
- [x] Deterministic local Codex session JSONL capture into Eventloom transcript, tool-call, command, and file-edit observations
- [x] Deterministic local Claude Code session JSONL capture into Eventloom transcript, tool-call, command, and file-edit observations
- [x] Memory Checkout diagnostics for source lanes, citation coverage, retention exclusions, warnings, and feedback guidance
- [x] Memory Checkout guidance with trust/ignore instructions, follow-up checkout suggestions, and feedback payload templates
- [x] Memory Checkout quality scoring with answerability, confidence, reasons, and required actions
- [x] Memory Checkout degraded-state handling for missing, superseded-only, uncited, and warning-bearing context
- [x] Shared Memory Checkout policy module used by core and MCP interfaces
- [x] Coverage ratchet enforced in CI and release checks from generated coverage XML
- [x] First-class model-facing Memory Bootstrap contract for session-start capability, checkout, capture, and trust guidance
- [x] Workspace-neutral Codex MCP config with runtime workspace/Eventloom resolution and doctor leak detection
- [x] Beta readiness inventory with clean-repo UAT script and doctor gate
- [x] Maintained beta roadmap with post-UAT product work, release criteria, and doctor coverage
- [x] Benchmark guardrail comparison CLI for quality floors, latency budgets, and regression checks
- [x] Deterministic capture soak report with beta pass/fail criteria, latest seq/hash evidence, stale lane detection, and remediation steps
- [x] Source citation graph projection with `Source` nodes and deterministic `CITES_SOURCE` edges from entities and Eventloom events
- [x] Temporal entity version graph projection with deterministic `SUPERSEDED_BY` and `PREVIOUS_VERSION` edges
- [x] Explicit task lifecycle observation edges for commands, file edits, tool calls, and checkpoints
- [x] First-class inferred-edge audit metadata for graph projection confidence, method, and evidence
- [x] Explicit `inference.edge.generated` event projection for auditable inferred graph edges
- [x] Conservative cited-decision inferred-edge producer for task completion events
- [x] Read-only inferred-edge graph status for method, confidence, evidence, and source-event audit coverage
- [x] Source-aware inferred-edge retrieval scoring with trust multipliers and score explanations
- [x] Checkout-level inferred graph context diagnostics and prompt guidance
- [x] Local Neo4j UAT coverage for inferred-edge projection, retrieval scoring, and Memory Checkout diagnostics
- [x] Model-facing clean-repo UAT proving init, Memory Bootstrap guidance, cited Memory Checkout, feedback guidance, capture status, and capture-soak coverage
- [x] Dual clean-repo Codex and Claude Code UAT with isolated `zaxy init`, Memory Bootstrap, Memory Checkout, feedback guidance, doctor, hook status, capture status, and capture-soak checks
- [x] MemPalace-comparable benchmark inventory CLI for frozen lane fingerprints, product claims, and required release metrics
- [x] Full 500-question LongMemEval-compatible hash report with BM25 baseline and no-regression guardrails
- [x] Public benchmark report contract requiring same-harness BM25 latency and token tradeoffs in LongMemEval artifacts
- [x] Same-harness competitor adapter feasibility matrix for MemPalace, Mem0, and Agent Memory with blockers kept in external disclosures
- [x] Skill Memory procedural world-model layer with lifecycle events, checkout routing, MCP helper, docs, and full-set quality guardrail verification
- [x] Skill Memory outcome analytics for promotion candidates, rollback candidates, and contradiction diagnostics
- [x] Projection backend contract and Neo4j factory for pgGraph evaluation without changing the default backend
- [x] Experimental pgGraph adapter behind `PROJECTION_BACKEND=pggraph` for projection, exact search, keyword search, pgvector-backed vector search, invalidation, and traversal, with optional integration coverage
- [x] Initial same-harness pgGraph vs Neo4j LongMemEval-compatible 100-question comparison with BM25 baseline and pgvector-enabled Docker validation
- [x] Full 500-question pgGraph comparison archived with guardrail failure recorded, keeping pgGraph experimental until Recall@5 matches Neo4j-backed floors
- [x] Reproducible pgGraph benchmark reset with full-set same-harness Neo4j checkout control
- [x] Public benchmark guardrail script for cached LongMemEval artifacts and archived report floors
- [x] Common native-preview adapter contract chosen as the next model-facing UX hardening target, with AutoGen held at template-only until runtime hooks are validated
- [x] pgGraph operational rebuild path through `zaxy reproject --projection-backend pggraph --reset-projection` with backend cleanup on projection failure
- [x] Incremental `zaxy refresh-context` for document/code source deltas with Neo4j and pgGraph stale projection retirement
- [x] Memory Persistence / Agent Recall Hardening with reminder policy, lifecycle hook suggestions, checkout activity markers, dashboard status, and framework checkout middleware
- [x] Full-set LongMemEval synthesis improved without floor regression: archived hash checkout mean 0.724, Answer@5 0.628, R@5 0.972, citation coverage 1.000
- [x] LatticeDB backend candidate behind `PROJECTION_BACKEND=latticedb` with projection, exact search, native full-text search, native vector search, traversal, temporal invalidation, source retirement, Eventloom citation metadata, projection status, inferred-edge diagnostics, and backend shootout routing
- [x] CLI `zaxy memory append` twin of the MCP `memory_append` tool, writing byte-identical events through the shared `MemoryFabric.append` pipeline for trusted daemon/agent shims

## Metrics

| Metric | Value |
|--------|-------|
| Tests | 1063 passed, 11 deselected |
| Coverage | 91.97% |
| Lint | ruff clean |
| Types | mypy clean |
| Python versions | 3.11, 3.12, 3.13 |
| LongMemEval 500 hash | Zaxy checkout mean 0.724, Answer@5 0.628, R@5 0.972, citation coverage 1.000, p95 1472.11 ms, p99 2652.55 ms |
| LongMemEval 500 pgGraph | Zaxy mean 0.698, Answer@5 0.698, R@5 0.958; checkout mean 0.714, Answer@5 0.632, R@5 0.958; same-harness Neo4j checkout control mean 0.714, Answer@5 0.626, R@5 0.958; citation coverage 1.000 |

## Next Steps

1. Build the zero-friction embedded graph runtime path further by
   running the same-harness backend shootout at meaningful scale, reporting
   projection throughput, checkout latency, traversal latency, returned tokens,
   injected tokens, LongMemEval Answer@5/Recall@5, citation coverage, dashboard
   graph load time, memory footprint, and rebuild recovery for embedded,
   LatticeDB, Neo4j, pgGraph, and BM25.
2. Build the Memory Activation Layer so `zaxy init` and a launcher path such as
   `zaxy activate codex` make checkout/context injection the default session
   behavior, while CLI and dashboard surfaces expose last checkout, last
   capture, stale checkout, no-memory-use warnings, and token-efficiency
   diagnostics.
3. Keep Neo4j as the release default and quality control backend until the
   embedded graph path preserves temporal semantics, citations, inferred-edge
   metadata, session isolation, dashboard graph rendering, and published
   LongMemEval guardrails.
4. Continue the pgGraph collaboration track for Postgres-native deployments and
   embedded packaging or library-mode options, but do not make pgGraph the
   default unless it beats the same gates without sidecar friction.
5. Continue LatticeDB evaluation as a first-class embedded candidate. Do not
   make it the default until the adapter passes the same contract, benchmark,
   and operations gates at representative scale.
