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GitHub - astefanutti/shaderbang: Shebang for Shaders Show HN: Generate Claude Code Workflows using Spec Driven Development approach Show HN: AI agents for UK GDAD PCF roles and their skills The Two Pillars: Mixer Mode and Meta-Software in the Reorganization of Software Work After AI GitHub - JaiCode08/teleport-env What 1,000+ Harness Experiments Taught Me About Self-Improving Agents Show HN: Liiists, a Markdown-first, iOS and CLI list app SwiperTab – Get this Extension for 🦊 Firefox (en-US) GitHub - kouhxp/fftext: Summarize, explain, fact-check, or translate any text, URL, or file. No GPU. No cloud. One command GitHub - sweetpad-dev/sweetpad: Develop Swift/iOS projects using VSCode GitHub - dogmaticdev/IRON: IRON a.k.a. Intermediate Representation Object Notation is a Interpreter/Database that is used to create Programming Languages. GitHub - sjhalani7/vaen: Package your AI coding harness into a portable .agent file, and share it across repos, teams, & the community without ever having to copy-paste instructions, skills, MCP config, or secrets. Show HN: Gandalf the Grader Show HN: Citadeld – replay any CI failure locally from a single file GitHub - tdortman/cuSBF: High-Performance GPU Super Bloom Filter coral-ai/claude-code-token-xray at main · Coral-Bricks-AI/coral-ai GitHub - ulyssestenn/funes: Funes is a Git-based framework for LLM-managed knowledge work: an AI Librarian ingests raw sources, builds an interlinked Markdown knowledge base, and uses it to produce cited reports, analyses, and other outputs. GitHub - ThatXliner/gah: Git Add Hunk, built for agents to use GitHub - harmont-dev/harmont-cli: Command-line client for the Harmont CI platform GitHub - brooksmcmillin/mcp-authflow: OAuth 2.0 Authorization Server framework for MCP servers GitHub - javaid-codes/audit-supply-chain-agents GitHub - amorey/gochan: A small library of common channel architectures for Go, inspired by Rust GitHub - arifozgun/OpenGem: Free, Open-Source AI API Gateway with Gemini, OpenAI & Anthropic Compatibility in 1 file GitHub - Pranesh950/BioPetals: 🌸 Run BIOxAI models at home, BitTorrent-style. Fine-tuning and inference up to 10x faster than offloading GitHub - cnguyen14/bounty-doctor: Diagnose a GitHub bounty issue before you waste hours: detects honeypot scam repos, AI-bot attempt swarms, and stale contests. Show HN: CoreMCP – MCP Server for On-Prem DBs Show HN: KittyHTML – Render HTML/CSS as an inline image in your terminal GitHub - bingud/filemat: Web-based file manager Show HN: TruthLens – Free multi-signal deepfake image detector GitHub - apexlocal-jz/claude-usage-tray: Windows system-tray app showing your Claude Code rate-limit usage at a glance. Zero deps, ~300 lines of PowerShell. Cross-IDE (works regardless of VS Code, Cursor, plain terminal).
Zaxy - event-sourced memory for agent work
syndicalt · 2026-06-01 · via Show HN

Event-sourced memory for agent work

Zaxy keeps multi-agent projects replayable: parent missions, isolated worker sessions, cited findings, purpose-conditioned checkout, conflict review, and accepted merge-back into one durable project history.

runtimeembedded Kuzu default

sourceEventloom append-only JSONL

checkoutcited, purpose-conditioned context

PyPI 1.1.2 embedded local runtime Harvey LAB 10/10 tasks Harvey LAB mean 0.788 purpose-v1 passed CoordinationBench gate passed StateRecoveryBench gate passed Harvey LAB external signal same-harness comparison discipline external verification requested

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.

Missionobjective and parent state

Workersisolated Eventloom sessions

Findingsevidence, confidence, citations

Reviewconflicts, stale claims, approvals

Checkoutaccepted cited prompt state

Eventloom source of truth remains the append-only project record. The default local runtime is embedded Kuzu, 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 now carries purpose through retrieval, checkout diagnostics, feedback, compaction, and Coordinate accepted state. This is still framed as project-local agent work memory, not a broad Company Brain claim.

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, required action, and memory_feedback guidance 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 artifacts separate external benchmark evidence, internal release gates, and unsupported comparative claims. Zaxy now has a full Harvey LAB external memory-ablation run across all ten pinned legal agent tasks: mean criterion pass rate 0.788, +0.184 versus regular/no-memory, +0.081 versus the article-best task rows, 9/10 task wins, and a head-to-head win over the strongest GBrain task rows. CoordinationBench v1 still passes accepted-finding precision and recall, conflict handling, stale rejection, proof-backed synthesis, and parent answerability. Larger memory-system comparisons against Mem0, Agent Memory, Zep/Graphiti, and MemPalace remain disclosure-only until pinned same-harness adapters produce locally scored, fingerprinted results.

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.

Purpose Benchmark

10/10 lanes passed

Purpose recall, ontology shift, outcome feedback, evidence discipline, and neutral-substrate projection are covered by purpose-v1.

CoordinationBench

1.000 gate metrics

Accepted-state synthesis, non-authoritative leakage, citation coverage, parent answerability, and Eventloom replayability pass.

Comparison posture

Evidence first, claims second

Harvey LAB is published as scoped external evidence. Larger memory-system comparisons stay disclosure-only until same-harness audits are complete.

Current Evidence Boundary

These rows are release evidence and disclosure status, not a universal memory leaderboard.

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.
purpose-v1 passed Purpose-conditioned retrieval, checkout, feedback, and compaction contract. External superiority claims against larger memory systems without pinned same-harness adapters.
public-derived purpose holdout diagnostic Representative pressure cases with citation coverage and frozen fingerprint. Release gate or outside-user validation.
CoordinationBench real-v1 passed Accepted parent state, conflict handling, stale rejection, proof-backed synthesis. Generic RAG, open-domain QA, or all memory workflows.
Semantic Reach / Quarq blocked Small-project unsupported disclosure rows retained for audit completeness. Headline competitive positioning or completed competitor scoring.
BM25 worker logs 0.666667 precision Same-harness local baseline over rendered worker findings. Accepted project state, conflict recall, stale rejection, or citation coverage.
Markdown notes 0.636364 precision Same-harness local baseline without promotion or conflict semantics. Authoritative parent checkout or proof-backed merge-back.
Flat transcript 0.272727 precision Contamination baseline that treats all worker output as accepted state. Reliable accepted-state precision, stale rejection, or conflict review.
Mem0 / Agent Memory / Zep-Graphiti / MemPalace / GBrain not_run Primary external comparison set: memory-system disclosures plus Harvey LAB GBrain task rows. Same-harness memory-system scores until pinned runner manifests exist.

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.

Operator and internals reference