Event-sourced memory for agent work

# Zaxy

Zaxy turns agent work into durable, auditable memory: a hash-chained append-only log as the source of truth, cited Memory Checkout as the trust contract, salience-based forgetting that attenuates instead of deleting, compaction recovery for long sessions, and coordinated worker missions that merge back into one replayable project history.

Install locally What's new in 2.6
runtime embedded LadybugDB default
source Eventloom append-only JSONL
checkout cited, token-budgeted context
forgetting salience attenuation, replayable
PyPI 2.6.3 49 MCP tools, 8-tool core profile cognitive ranking default embedded local runtime Harvey LAB 10/10 tasks Harvey LAB mean 0.788 Headline 500 R@5 1.000 Harvey LAB external signal headline 500 checkout evidence external verification requested

Cognitive memory

## Forgetting is a ranking policy, not data loss.

Zaxy 2.x implements the memory literature as boring, testable scoring over an immutable log: retrieval strengthens, disuse decays, surprise gates encoding. Forgetting is pure projection policy — attenuated memories leave default ranking but stay one explicit query away, with a replayable record of why they faded. Every default in this list was flipped or held by an evaluation lane that ships in the repo.

`salience ranking`

Confirmed memories outrank stale ones; invalidated memories attenuate below a floor. Pinned and authority-reviewed memories are exempt. Cold-start ranking is byte-identical to plain retrieval — measured, not asserted.

`compaction recovery`

After a context compaction, a `session-resumed` hook hands the agent back its open tasks, accepted findings, and known unknowns — every line citing the exact log events it came from.

`memory_checkout(..., max_tokens=N)`

Token-budgeted packing with explicit elision reporting, and cache-stable packet ordering: consolidated content renders byte-identically across calls so provider prompt caching hits.

`tool profiles`

The default core profile lists 8 tools instead of 49 — an 83.7% smaller listing surface — while every tool stays callable by name. `--profile full` restores the complete listing.

`memory_feeling_of_knowing`

Experimental sub-millisecond metamemory pre-check: would checkout likely return something? Lets agents decide whether retrieval is worth the call before paying for it.

`zaxy memory mine-procedures`

Recurring successful tool sequences become review-pending procedure candidates with trace citations. Nothing becomes authoritative without review — the same gate as every generated abstraction.

Coordinate

## Worker-local claims are not project truth.

Spawning agents is easy. The hard part is turning isolated investigations into one trustworthy state of work. Zaxy records each worker in its own Eventloom session, reviews findings with evidence, marks stale and conflicting claims, and promotes only accepted facts into the parent mission.

### Parent mission

The coordinator owns accepted project history, decisions, handoff, and Memory Checkout state.

### Worker sessions

Agents investigate in isolated logs, so exploration does not contaminate authoritative memory.

### Approval packets

Human or coordinator-agent review accepts, rejects, defers, or promotes findings with cited provenance.

Architecture

## Eventloom is truth. The graph is a rebuildable projection.

Mission objective and parent state
Workers isolated Eventloom sessions
Findings evidence, confidence, citations
Review conflicts, stale claims, approvals
Checkout accepted cited prompt state

Eventloom source of truth remains the append-only project record. The default local runtime is embedded LadybugDB, launched and cleaned by `zaxy init` and `zaxy doctor`. Neo4j remains the sidecar control backend; pgGraph, LatticeDB, and Pathlight are advanced integration tracks for teams that need alternate deployment or observability posture.

Purpose control plane

## The same evidence can mean different memory for different work.

Zaxy carries purpose-conditioned checkout through retrieval, diagnostics, feedback, compaction, and Coordinate accepted state. This is still framed as project-local agent work memory, not a broad Company Brain claim.

`memory_checkout(..., purpose="coding")`

Applies deterministic purpose emphasis, recall floors, scoring profile selection, and checkout guidance.

`zaxy memory purpose status`

Replays active profile, checkout quality, accepted Coordinate state, and feedback posture without graph mutation.

`zaxy memory purpose lanes`

Shows purpose-specific checkout lanes, cited source groups, and suppression candidates.

`zaxy memory purpose feedback`

Surfaces positive and negative outcome history so future retrieval can prioritize useful purpose-specific memory.

Interfaces

## CLI, MCP, dashboard, and adapters share the same contracts.

`coordination_checkout` accepted parent state plus diagnostic worker-local findings `coordination_approval_packet` reviewable accept/reject/defer/promote payloads `memory_checkout` answerability, current_citation_count, salience diagnostics, budget reporting, and memory_feedback guidance `memory_feeling_of_knowing` experimental likely/possible/unlikely pre-check with calibration markers `CoordinationAdapter` dependency-light Python wrapper with LangGraph and CrewAI helper paths `dashboard --enable-coordinate-review` opt-in human review controls over replay-backed state; read-only remains the default

Benchmark evidence

## Public claims stay inside the evidence boundary.

Current public benchmark evidence is intentionally narrow: the headline 500-question LongMemEval-compatible checkout diagnostic and the Harvey LAB external legal-agent memory-ablation report. Older backend shootouts, partial slices, suite gates, and debug reports are archived as development history rather than current claims.

Harvey LAB

### 0.788 mean criterion pass rate

Full ten-task external legal-agent memory-ablation run, +0.184 versus regular/no-memory and 9/10 task wins versus article-best rows.

Headline 500

### R@5 1.000 with citations 1.000

Full 500-question LongMemEval-compatible checkout diagnostic: mean 0.956, Answer@5 0.910, Recall@5 1.000.

Claim boundary

### Checkout diagnostic, not official LME

The headline 500 is a Zaxy same-harness checkout run, not an official LongMemEval end-to-end assistant score.

Comparison posture

### Evidence first, claims second

Archived reports remain useful for engineering history, but public benchmark claims now route through the benchmark hub.

Vector search (internal)

### Defaults bounded to the measured envelope

The 2.2 ANN engagement rule ships exactly as far as internal lane evidence extends: HNSW engages at 100k+ vectors up to 64 dimensions, where it measured recall 1.0 with 12.9x faster index builds. Above that envelope, exact search remains the recommendation — the negative results ship in the same paper.

### Current Evidence Boundary

Artifact | Status | What it supports | What it does not support
--- | --- | --- | ---
Harvey LAB external memory-ablation | complete | Full 10-task legal-agent benchmark evidence: 0.788 mean criterion pass rate, +0.184 vs regular/no-memory, +0.081 vs article-best rows, 9/10 task wins. | Same-harness full-suite scores for non-Zaxy systems beyond the article-published matrix.
LongMemEval-compatible checkout 500 | current headline | Same-harness checkout diagnostic: mean 0.956, Answer@5 0.910, Recall@5 1.000, citation coverage 1.000. | Official LongMemEval end-to-end assistant accuracy or external memory-system leaderboard ranking.

Harvey LAB result Full external run and publishable stats Headline 500 Full checkout diagnostic and claim boundary External verification Public request and report contract ANN engineering paper Baseline-gated vector-search optimization, evidence and negative results

Install

## Initialize a local embedded runtime, then expose memory through MCP.

    pipx install zaxy-memory
    zaxy init
    zaxy memory log --eventloom-path .eventloom --limit 5
    zaxy memory bootstrap --eventloom-path .eventloom
    zaxy doctor --eventloom-path .eventloom

    zaxy coordinate start "ship auth refactor" --mission auth-main
    zaxy coordinate worker create --mission auth-main --worker auth-api
    zaxy coordinate assign --mission auth-main --worker auth-api "trace failures"
    zaxy coordinate brief --mission auth-main
    zaxy coordinate checkout --mission auth-main

### What happens when you run init

Zaxy writes `.env.local`, records session genesis and heartbeat, checks graph posture, and prints the MCP command or config path.

### What stays local

Session history lives in `.eventloom/` as append-only JSONL. The graph is a rebuildable projection.

### How to prove capture

`memory log`, `memory bootstrap`, `doctor`, and `hook-status` expose Last checkout, capture, and stale-memory posture.

Documentation

## Start with Coordinate and purpose. Keep the rest as operator reference.

Zaxy 2.6 release Zaxy 2.1.0 release Migration guide (2.0 to 2.6) Coordinate roadmap Benchmarks Research paper ANN engineering paper Essay: memory consolidation that keeps the receipts External verification request Getting started MCP quickstart Coordinate quickstart First-run validation Zaxy Collaborate demo media Architecture MCP interface Framework integrations Why Zaxy
Operator and internals reference
Zaxy 2.6 X article Zaxy 2.5.0 X article Zaxy 2.4.0 X article Zaxy 2.3.0 X article Zaxy 2.2.0 X article Zaxy 2.1.0 release Zaxy 1.0.0 release Zaxy 1.0.0 X article Zaxy 1.1.0 X article Zaxy Coordinate announcement Zaxy 0.4.0 archive Configuration MCP install targets Eventloom contract Agent events Hook protocol Codebase mapping Graph schema Retrieval Embeddings Security Operations Deployment Testing Consolidation Python API API inventory Stability commitment Migration guide Packet analyzer Workspace genesis