Encrypted, fully offline agentic memory. One click install, GUI w/ memory map, all OS and agents. Logically and mathematically sound storage and retrieval.
# Add to your Claude Code skills
git clone https://github.com/MaxFreedomPollard/CompartmentCompartment is an open-source ai agents skill for AI coding assistants such as Claude Code, Codex CLI, and ChatGPT, built by MaxFreedomPollard. Encrypted, fully offline agentic memory. One click install, GUI w/ memory map, all OS and agents. Logically and mathematically sound storage and retrieval. It has 50 GitHub stars.
Compartment's catalog security scan is still queued. You can run an instant dependency and prompt-injection check now with the "Scan for vulnerabilities" button above.
Clone the repository with "git clone https://github.com/MaxFreedomPollard/Compartment" and add it to your Claude Code skills directory (see the Installation section above).
Compartment is primarily written in Python. It is open-source under MaxFreedomPollard 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 Compartment against similar tools.
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Your AI agent forgets you the moment the session ends. Compartment ends that. With Compartment, your AI agent gets better with experience: it keeps every decision, preference and detail you give it, permanently, encrypted, on your own computer. Hermes, Claude, OpenClaw and other AI Agents can install in one command. One fully-transferable memory store is shared simultaneously by all agents on the computer. 100% offline: no network, no API key, no cloud account, no telemetry. The embedding model ships inside the package, and a full search returns in about 12 ms, beating the round-trip a hosted memory charges you for. Every byte at rest is AEAD-encrypted, the embedding vectors included, and only your passphrase opens it.
Unlike other agentic memory, we offer an option to start off with memory - 6,718 curated facts seeded at install: the physical constants and unit conversions, 800+ hardware facts with real specs (Apple silicon, PCs, CPUs and GPUs, phones, game consoles, Raspberry Pi, storage, displays, connectors) to provide a map of computer geography, operating system versions and release names, network ports and HTTP, file signatures, character encodings, shell and Unix internals, git, regex, SQL and hashing, ISO country, currency and time codes, and more. Allows an offline agent to operate better without internet, and an online agent to operate faster and more accurately.
More secure, by construction. Every byte at rest is authenticated-encrypted, the embedding vectors included (most tools leave those in the clear, and vectors can be inverted back toward text). Deletion is cryptographic: destroy the record's key and it is gone, unrecoverable. Tampering is detected, history is hash-chained, and the vault locks itself on restart or power loss. It runs fully offline: a runtime guard aborts on any network attempt, and CI proves it on three operating systems.
Not one step harder. One command installs it, creates the vault, and wires your agent. No API key, no cloud account, no daemon. Unlock when you want to use it; lock when you want it closed. By default an unlock stays open for weeks (until restart or you lock it), like any app you leave running. The security is free at the point of use because it falls out of the architecture, not out of your patience: keeping plaintext off disk forces the index into RAM, and a RAM-resident index is also the fastest one there is. Secure and fast are the same choice here, and neither costs you a configuration step.
One line install, works on all operating systems.
pip install compartment && compartment init
Then connect it to the agent you use:
compartment integrate claude
claude, hermes and openclaw are the three auto-connect targets. Each one
also gets the /compartmentalize skill installed into its own skills
directory.
/compartmentalize saves the conversation before it is thrown away. Every
agent eventually compacts or summarizes a long session, and the summary is
written by a pass that has no tools, so nothing can be stored from inside it:
whatever the model did not think to save is simply gone. Type
/compartmentalize and the whole conversation is swept into the vault first -
people and contacts, credentials and where they live, URLs and hosts, decisions
and the reasoning behind them, and a narrative of the session itself. Then
compact, and nothing is lost. It works on its own at any point too.
One click install (for people not good with command line). Download Compartment.pkg from the latest release and open it. Python, the embedding model and every dependency are inside it. macOS only.
After install, everything is managed from the app: the menu bar on macOS, the notification area on Windows, and a window from your applications menu on Linux.
Compartment is an MCP server, so it works with all MCP capable agentic AI out of the box. Every option is in Configuration.
Install it in one step
.pkg and you are done. Python, the embedding model
and every dependency are inside it./compartmentalize is installed into every agent it connects, so one command
banks a whole conversation before compaction throws it away.Remembers the right things
Search that beats a network call
Encrypted, offline, and yours
forget --shred destroys the record's key. The content is mathematically
unrecoverable, not marked deleted.lock --sign seals
it with an Ed25519 manifest anyone can verify without a credential.compartment dash puts the entire vault on a local page: 127.0.0.1 only,
random token, read-only.Full write-path, decision math, and comparisons in docs/MEMORY.md. The load-bearing ideas:
Nearly everything is stored; nothing important is buried. Only empty
turns are dropped. A bare "OK" is not noise, it is a decision: when the
agent asks "Want me to send this reply to the client now?" and the user
answers "OK", Compartment resolves the question from the conversation and
stores
[decision 2026-07-20] Approved (answered "OK"): Want me to send this reply to the client now? at the top importance tier. Asking "did the
user say to email the client?" later retrieves exactly that record.
Deterministic importance tiers rank recall: decisions/consent 0.90, personal facts and preferences 0.80, the user's machine and configuration 0.75, other substantive statements 0.55, pleasantries 0.20 (kept, ranked last). Importance multiplies a match rather than adding to it, so it settles near-ties in favour of what matters and can never surface a memory for a question it has nothing to do with. The whole scoring model, and the numbers it was chosen against, are in The mathematics. The agent learns the user and the computer first, the world second, and forgets nothing.
One memory, not two. Agent hosts increasingly ship a memory of their own - Claude Code keeps per-project Markdown files with an auto-loaded index. Two memories means facts land in whichever one the model happened to think of, and neither is complete. Compartment takes over on install: it imports what the file memory already holds, and both the MCP handshake and the managed CLAUDE.md block tell the model that Compartment supersedes it - write every new memory here, treat the files as a read-only archive. One vault, encrypted, shared by every agent and project on the machine. Nothing is deleted; the files stay exactly where they were.
Capture that does not depend on the model. Instructions are a request, and a host that declares its own memory in its system prompt outranks anything a tool says. So `compartment integrate clau