by chunxiaoxx
Reliability layer for multi-agent setups — keep agents coordinating without an orchestrator. Cross-dialog contracts + drift detection + black-box memory (no LLM extraction).
# Add to your Claude Code skills
git clone https://github.com/chunxiaoxx/nautilus-compassGuides for using ai agents skills like nautilus-compass.
Last scanned: 9/25/2026
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"file": "skills/compass-integrity/SKILL.md",
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"type": "dangerous-command",
"message": "Dangerous command (reverse-shell shape): \"nc 127.0.0.1 9876` ping |\"",
"severity": "medium"
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"status": "PASSED",
"scannedAt": "2026-09-25T09:25:17.770Z",
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}See how nautilus-compass compares with popular alternatives.
nautilus-compass is an open-source ai agents skill for AI coding assistants such as Claude Code, Codex CLI, and ChatGPT, built by chunxiaoxx. Reliability layer for multi-agent setups — keep agents coordinating without an orchestrator. Cross-dialog contracts + drift detection + black-box memory (no LLM extraction). It has 462 GitHub stars.
Yes. nautilus-compass passed SkillsLLM's automated security scan — a dependency vulnerability audit plus prompt-injection heuristics — with no high-severity issues. You can read the full report in the Security Report section on this page.
Clone the repository with "git clone https://github.com/chunxiaoxx/nautilus-compass" and add it to your Claude Code skills directory (see the Installation section above).
nautilus-compass is primarily written in Python. It is open-source under chunxiaoxx on GitHub, so you can review or fork the full source.
Yes. SkillsLLM lists many other AI Agents skills you can browse and compare side by side. Open the AI Agents category from the badge at the top of this page, or use the Related Skills and comparison links further down to weigh nautilus-compass against similar tools.
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Open-source memory & reliability layer for AI agents. Long-term memory that now beats mem0 on all three LongMemEval-S metrics while staying fully local & 14× cheaper — plus drift detection and cross-agent contracts that no other memory layer ships.
Plugin for Claude Code / Desktop · Cline · Cursor · Continue.dev · Zed · any MCP client.
Built by Nautilus Platform · open agent ecosystem · join as agent →
🇬🇧 English (this file) · 🇨🇳 中文
Three pillars, one plugin:
1 · Black-box long-term memory — now with SOTA retrieval.
Raw text embedded locally with BGE-m3. No extraction LLM at ingest, no graph,
no data leaving your machine. In Aug 2026 we added utterance-routed chunk
retrieval: single-session and knowledge-update questions route to
turn-window chunks (the answer usually lives in ONE user turn; whole-session
embedding dilutes it), everything else uses session-level hybrid
(BM25 + dense RRF). Result on LongMemEval-S full 500 questions,
same-question head-to-head vs mem0 2.0.19 (both sides infer=False,
each on its own default embedder — bge-m3 vs vertexai text-embedding-005 —
our reproduction):
| LongMemEval-S · n=500 | P@1 | P@5 | MRR |
|---|---|---|---|
| compass | 0.890 | 0.978 | 0.929 |
| mem0 2.0.19 | 0.774 | 0.916 | 0.834 |
One-command reproduction (retrieval-only, no LLM calls, CPU works / GPU recommended for the full 500):
bash scripts/reproduce_lmes_retrieval.sh # full 500
SUBSET=12 bash scripts/reproduce_lmes_retrieval.sh # smoke
The same utterance ammo overtakes mem0 on its own home benchmark
(LOCOMO-10, n=1986: 0.644 / 0.890 vs 0.592 / 0.802) and fixes the
single-session collapse on LongMemEval-M (0.20 → 1.00). Full evidence chain
with per-type breakdowns and every config flag:
docs/evidence/headhead_mem0_full500_20260826.json
— including the experiments that failed (cross-encoder reranking hurts on
this corpus; candidate-pool K is a no-op; Qwen3-0.6B swap is a wash).
2 · Drift detection — the half nobody else solves. Memory recalled doesn't stop the AI from breaking the rule this time. compass scores every prompt against an anchor set of real failure patterns (25 positive + 35 negative) before the agent acts. AUC 0.83 held-out, p95 latency <50 ms, fire rate 0.5% in production traffic. White-box layers abstract prompts into facts before drift becomes checkable — structurally out of their reach.
3 · Cross-agent contracts + governance.
When you run multiple agents (or multiple Claude dialogs) on shared files,
compass derives implicit contracts from handoff files, tracks closure, and
audits for fake-closure / red drift. A 4-dialog 28-hour field study lives in
docs/case_study_4dialog_compass.md.
The trade that flipped: earlier versions traded −30 points on LongMemEval-S for local deployment and cost. As of 2026-08 there is no trade — full sweep at 1/14 the reproduction cost (~$3.50 per 500 questions vs $50+ for GPT-4o-judged stacks). Full argument: paper/BLACKBOX_VS_WHITEBOX.md.
| Package | What it is |
|---|---|
nautilus-compass |
this repo — CLI, MCP server, A2A adapter (3.2.0) |
assay-verify |
ed25519 signed receipts for AI outputs — attest-at-generation, verify-on-consume (Let's Encrypt for AI claims) |
jev-trust |
trust middleware for the Jev decision API — logs every call, measures calibration in your domain, signs the evidence |
| BC1 benchmark | 30-item organizational-memory exam — honest scoring (U never counts), machine-scored, our own 11/18 first self-test published in full — launching 9/27 |
pip install nautilus-compass
# ships the CLI, the MCP server, the A2A adapter and session tools:
# nautilus-compass · compass-mcp · compass-a2a
# compass-drift-history · compass-session-search · compass-session-writer
git clone https://github.com/chunxiaoxx/nautilus-compass ~/.claude/plugins/nautilus-compass
bash ~/.claude/plugins/nautilus-compass/install.sh
# start the BGE-m3 daemon (one-time per boot)
bash ~/.claude/plugins/nautilus-compass/daemon_start.sh
Deploy notes (field-verified pitfalls, 2026-08-28):
COMPASS_USE_INOTIFY=0disables new-file discovery — recalls won't see fresh writes, silently. Only set it if you know why; the daemon logs a WARNING when it's off.driftfails loudly now: ifanchors.jsonis missing from the plugin dir, responses carrydrift.anchors_error+should_alert: true(it used to silently return "no risk" — that was a security hole).- Token changes to
tokens.jsonhot-reload via mtime check (no systemd restart needed since v3.1.0).- First recall after daemon idle may take up to 90 s (model cold-load); the MCP client auto-retries once with the extended timeout.
The installer wires three hooks into ~/.claude/settings.json:
UserPromptSubmit → time-bucketed memory recall + drift checkPostToolUse → mid-session writerStop → end-of-session summary (writes a session battle-report to
~/.claude/.cache/compass-last-session.txt)Slash commands: /compass-verify · /compass-drift · /compass-recall ·
/compass-search · /compass-status.
python ~/.claude/plugins/nautilus-compass/scripts/install_to_agent.py
Auto-detects Claude Desktop, Cursor, Cline, Continue.dev, Zed and patches
their MCP config. Per-agent copy-paste configs:
docs/AGENT_ONBOARDING.md · raw protocol:
docs/mcp-usage.md.
The hosted gateway — MCP over HTTPS with scoped tokens and per-user memory
isolation — is open for self-serve registration: sign up at
https://compass.nautilus.social/signup,
then create a token in the web console (or POST /tokens). Scopes are
server-bound to your own space (read+write); cross-user access is denied and
verified by automated probes. Design:
docs/plans/2026-08-30-multi-tenant-memory-design.md.
MCP endpoint: https://compass.nautilus.social/mcp/ (Bearer token ·
streamable-http). Also listed in the official MCP Registry as
io.github.chunxiaoxx/nautilus-compass (remote + PyPI self-host, dual entry) —
registry-aware clients (Glama and other aggregators) can discover it from there.
A2A discovery:
curl https://compass.nautilus.social/.well-known/agent.json
For agents on machines with ssh access to your Nautilus cloud box —
generates a scoped token, wires the cloud MCP bridge, writes .mcp.json,
and runs an end-to-end self-check. Add --hud to install the fused status
line (live recall hit-counter 🧠, drift state, 5-min traffic).
bash ~/.claude/plugins/nautilus-compass/ops/agent_quickstart.sh my-agent
| Benchmark | Score | Honest compare |
|---|---|---|
| LongMemEval-S 500q full (utt-routed + hybrid, n=500) | P@1 0.890 · P@5 0.978 · MRR 0.929 | sweeps mem0 2.0.19 (0.774/0.916/0.834, our reproduction, each side on its own default embedder): +11.6/+6.2/+9.5pt. Largest flip: single-session-user P@1 0.90 vs 0.49 |
| LOCOMO-10 (n=1986 · mem0's home benchmark) | P@1 0.644 · P@5 0.890 · MRR 0.740 | overtakes mem0 (0.592/0.802/0.677, our reproduction) +5.2/+8.8pt |
| LongMemEval-M 500q full (~501 sessions/question) | P@5 0.888 | 12x larger session pools cost only 9pt vs S500; ssu collapse fixed at n=500 (0.20 → 0.93); ssp 0.53 newly exposed; no mem0 M head-to-head yet |
| EverMemBench-Dynamic (n=500) | 44.4% (Run 1) / 47.3% (Run 2) | tops the four published Table 4 baselines (Mem0 37.09, Zep 39.97, MemOS 42.55, MemoBase 34.27). Not claiming "industry SOTA" — OMEGA / Mem0g haven't reported publicly |
| **Lo |