CodeZaiku

CodeZaiku

A coding and development harness that runs on local models or hosted APIs. It is an AI coding agent for your terminal, like Claude Code or aider, that works with a small model on Ollama, llama.cpp, LM Studio or any OpenAI-compatible server. It also reviews git diffs, repairs a broken docker compose stack with rollback when you allow it, reports security problems in a server's Docker containers, researches questions with cited sources, and runs as an MCP server, an ACP agent or a command that prints JSON for other agents.

Most agents like this assume a frontier model behind someone else's API. CodeZaiku is built the other way round — a 9B on hardware you own — and the harness does the work that makes that viable: deterministic evidence instead of model guesses, a guard stack around anything that acts, and verification with rollback on every change.

It runs against any OpenAI-compatible server and ships no weights. The reference tier is a 9B.

→ ARCHITECTURE.md — how it works → LIMITATIONS.md — the measured numbers

Quick start

You need an OpenAI-compatible model server, and a JDK 21+ unless you take a build that carries its own Java runtime (from 0.3.2, one per platform; the installer picks one when Java is missing). CodeZaiku ships no weights.

Linux is the supported platform. macOS runs the coding and research surfaces (and can operate remote Linux hosts over ssh); Windows works under WSL2. There is a container image. See PLATFORMS.md.

Three ways to use it

At a terminal, for yourself — carry on below; the commands are in What you can do with it.

Underneath another agent or orchestrator — CodeZaiku is a backend as well as a tool. It speaks a CLI-subprocess contract (codezaiku run), ACP (codezaiku acp) and MCP (codezaiku mcp). The contract, the result shape and the failure modes are in DEPLOYING_AS_A_BACKEND.md; start there rather than here.

Underneath Wyrdsekai — CodeZaiku is released under the Wyrdsekai umbrella and is one of the coding backends Wyrdsekai can summon: you ask the companion for something, it hands the work to CodeZaiku. WITH_WYRDSEKAI.md is the short version of the page above — just the wiring, and the two things that trip people up. Nothing here depends on it; CodeZaiku runs standalone.

Installing

There is one binary artifact and it is platform-independent. CodeZaiku is JVM bytecode with no native parts, so the same tarball installs on Linux, macOS and Windows — there is no .pkg or .msi to look for, and none is needed.

Linux is the reference platform. macOS and native Windows are measured too, and the installer is verified on all three from a clean unpack. On Windows, install from Git Bash — the harness shells out through bash, and Git for Windows supplies it. See PLATFORMS.md for per-platform steps and for what does and does not work on each.

Linux and macOS:

curl -fsSL https://codezaiku.org/install | sh

Windows, from PowerShell (you also want Git for Windows — the harness shells out through its bash):

irm https://codezaiku.org/install.ps1 | iex

Only the script comes from codezaiku.org; the artifact and the checksums both come from the same GitHub release. What that URL serves is scripts/install-remote.sh (and scripts/install.ps1) from this repository, verbatim — read them here first if you would rather, and diff them against what the site serves. Both installers fetch the release tarball and verify it against the release's own SHA256SUMS before installing anything — a mismatch refuses rather than proceeds. Only the script comes from the URL above; the artifact and the checksums both come from the same GitHub release, so the script cannot hand you a payload those checksums do not match. Piping a script into a shell is worth being wary of in general: fetch it, read it, then run it if you would rather.

They install to ~/.local (or %LOCALAPPDATA%\Programs on Windows). CODEZAIKU_PREFIX puts it somewhere else, CODEZAIKU_VERSION pins a release.

No JRE on the machine yet? On Debian or Ubuntu, take the .deb from the latest release instead — it declares a JRE dependency, so apt installs one for you:

sudo apt install ./codezaiku_0.1.1_all.deb

The one-liners deliberately do not install a JRE themselves: a script piped into a shell should not be reaching for sudo. They check for one; when it is missing they install the build for the platform that carries its own runtime (codezaiku-<version>-<platform>.tar.gz, from 0.3.2; CODEZAIKU_RUNTIME=1 asks for it outright), and codezaiku update keeps such an install on its own kind.

To upgrade, run codezaiku update now, or the same install command again. update now takes the latest release, checks it against the release's SHA256SUMS and swaps it in; the next start runs it. When ResearchZosho is installed, it then asks ResearchZosho's own updater to do the same, and says what came of each. Each program's own updater replaces its files, so two programs updating at once never collide: the second finds the first at work and leaves it alone. On Windows, CodeZaiku cannot replace its own files while it runs, so there you run the install command again. The installers resolve the latest release each time and replace the old install rather than writing over it, so nothing stale is left behind. Your config and data in ~/.codezaiku are untouched. The .deb upgrades in place with sudo apt install ./codezaiku_<new>_all.deb and keeps /var/lib/codezaiku; if you enabled codezaiku.service, the upgrade does not restart it, it tells you to when it suits you.

tar xzf codezaiku-0.1.1.tar.gz          # unpacks a ready-to-run ./codezaiku./codezaiku/bin/codezaiku --version     # works immediatelysudo mv codezaiku /opt/codezaikusudo ln -s /opt/codezaiku/bin/codezaiku /usr/local/bin/codezaiku

From source, if you want to build it yourself or work on it:

git clone https://github.com/Wyrdsekai/codezaiku.git && cd codezaiku
# 1. install — builds and puts `codezaiku` on your PATH (~/.local by default;#    --system for /usr/local, --prefix DIR for anywhere else)scripts/install.sh
# 2. point it at your model server (install.sh already wrote a starter config)codezaiku setup               # the first ten minutes: the model (found, served on demand, or a hosted key), web search, your editor's agent over MCP, the library if wantedcodezaiku model serve install # this machine's memory, on demand: the measured model, llama.cpp behind a proxy that starts it when asked and stops it after 20 idle minutes (on Linux llama.cpp's container for the GPU it finds: NVIDIA, AMD or Intel; Metal on macOS, Vulkan on Windows)codezaiku model detect        # finds Ollama / llama.cpp / LM Studio / vLLM if runningcodezaiku model use http://localhost:8200codezaiku model add deepseek openrouter deepseek/deepseek-v4.1-flash --prices 0.032/0.144/0.002   # a hosted model under a name,codezaiku model key openrouter --file ~/openrouter-key.txt                                        # its key kept for its host,                              # chosen per job: codezaiku code . "…" --model deepseek; `codezaiku spend` says what the jobs cost
# 3. check the environment — names exactly what is missing and how to fix itcodezaiku doctor
# 4. confirm the model answers and can call a toolcodezaiku smoke

The install carries its own launcher, jars and knowledge library, and downloads nothing at runtime. It does not bundle a JVM — install.sh checks for a JDK 21+ and stops if it does not find one. No model weights are bundled either. scripts/install.sh --uninstall removes the program and keeps ~/.codezaiku — your config, learned cards, research findings and audit trail. --purge removes those too, after listing what will be lost and asking you to confirm.

To work in the repo without installing, bin/codezaiku runs from the checkout.

If you have no server yet:

docker run -d --name codezaiku-drive -p 8200:8200 \  -v /path/to/models:/models ghcr.io/ggml-org/llama.cpp:server-cuda \  -m /models/<your-model>.gguf --port 8200 --host 0.0.0.0 --jinja --ctx-size 32768

To use the models in your own AWS account (Amazon Bedrock) with your own AWS sign-in, see BEDROCK.md.

--jinja is required — without it the model returns tool calls as prose and nothing works. See MODELS.md for what the harness needs from a model, what we measured on, and why codezaiku smoke is the check that matters.

Debian / Ubuntu

sudo apt install ./codezaiku_0.1.1_all.deb     # build it: packaging/deb/build-deb.sh

Installs to /opt/codezaiku with /usr/bin/codezaiku. A systemd unit is included but not enabled — CodeZaiku can modify live systems, so starting it is a deliberate act.

Verifying what you downloaded

Every release asset ships with SHA256SUMS and a Sigstore bundle (<asset>.sigstore.json):

sha256sum -c SHA256SUMS --ignore-missinggh attestation verify codezaiku-0.1.1.tar.gz --repo Wyrdsekai/codezaiku \  --predicate-type https://codezaiku.org/attestation/release/v1

gh attestation needs GitHub CLI 2.49 or newer. An older gh reports unknown command with no hint why — check with gh --version before concluding the signature is bad.

The signature says the release workflow, running at that tag, blessed those exact bytes. It is an authenticity statement, not build provenance — the artifacts are built and validated on real hardware rather than in CI, because an artifact nobody ran is not one worth shipping. Release assets are immutable; a fix ships as a new version, never as a re-upload.

What you can do with it

codezaiku help                                  # all commands, grouped by intent

Talk to it

codezaiku chat ~/myproject

A coding assistant you talk to in your terminal — the same kind of tool as Claude Code, Codex CLI or aider, except the model behind it is yours to choose: one running on your own hardware, or a hosted API. You type what you want — "why does the login test fail?", "add a retry to the uploader", "find out how other projects handle this" — and it reads your code, makes changes, runs commands, or searches the web, then reports back. You steer it turn by turn.

By default it asks before changing or running anything, and shows you the exact change first. You answer once, or "always" for that command. /undo reverses what it did, step by step. Conversations are saved and can be resumed later, and /remember keeps a fact available in every future conversation in that project. /switch <project> moves the chat to another project in the same terminal and tells it where you were. /help inside the chat lists everything else — background tasks, delegating work to a second agent, switching models, cost tracking.

codezaiku v1 ~/myproject serves the same assistant as an OpenAI-compatible API (/v1/chat/completions), so a chat UI like Open WebUI can be the front end. Over that wire it can only read, never change anything — an API cannot ask you for permission, so it is not given anything that would need it.

codezaiku web is the chat in the browser, for several projects under one server: open http://127.0.0.1:7072/, pick a project or add one by its folder, and talk. It is the same chat as the terminal's, so it asks before it writes or runs anything, and you answer with buttons on the page. Each project keeps its own conversation. Moving to another project is a click, and "switch" also carries where you were, so the next thing you say there starts from it. It listens on this machine only unless you say --host 0.0.0.0, which opens it to your network; it then prints a token and the addresses to type, and the browser asks for the token once. On this machine it carries out a form only from its own page and answers only to 127.0.0.1 or localhost, so another web page you have open cannot work it. From the menu's People page you can name others: a viewer sees every page and every chat as it runs and can type nothing, an owner can do all you can. Each signs in with a name and a password.

Research a question

codezaiku research "your question" broadcodezaiku research "your question" fan

It searches the web, reads pages, and writes an answer that cites its sources. broad is one researcher working alone. fan splits the question into parts, researches them in parallel, has a critic check whether the coverage is actually sufficient, and then writes the combined answer — slower, and much better on questions with many parts.

Search works out of the box, and works better with a backend you configure. Without one, web_search falls back to Wikipedia plus the scholarly literature (Crossref and OpenAlex): reference pages and papers by DOI, not the whole web. Every research run also has scholar_search, the literature by DOI, whatever the backend. For the whole web, two options, the first recommended:

codezaiku config set CODEZAIKU_BRAVE_KEY <key>        # recommended: Brave Search APIcodezaiku config set CODEZAIKU_SERPER_KEY <key>       # Google's own results, paid per search (serper.dev); or CODEZAIKU_SERPAPI_KEYcodezaiku config set CODEZAIKU_FIRECRAWL_KEY <key>    # pages a plain fetch cannot read, through Firecrawl's browser, paid per pagecodezaiku config set CODEZAIKU_SEARXNG http://host:8888   # or: your own SearXNG instance

The Brave Search API has a free tier (2,000 queries/month) and gives markedly better results — a search tool is only as good as what it searches. SearXNG is fully self-hosted and needs no account, but it aggregates public engines that rate-limit under sustained use. With both configured, Brave is used first and SearXNG is the fallback. Setting either one is also what enables web search inside chat.

What a research run finds is kept. The research memory in ~/.codezaiku/research holds each finding with its source, and the next run on a related question starts from it instead of from zero. That is the built-in tier: it works with nothing else installed.

For real research, the kind that takes hours and comes back with a report you can check, there is ResearchZosho, a separate program from the same family. codezaiku install researchzosho fetches it, verifies it and runs its setup. From then on the chat's /research files runs with it, /librarian asks what it holds, and what it holds is pushed into every turn. The questions in the research memory are handed to it as open questions. codezaiku doctor and the chat say when a newer ResearchZosho is released; codezaiku update now has ResearchZosho's own updater install it, and the library and settings stay.

Work on a codebase

codezaiku code ~/myproject "add pagination to the /items endpoint"codezaiku decompose ~/myproject "add an admin dashboard with login and audit view"codezaiku review ~/myproject HEAD~3             # read-only review -> findings

code keeps one conversation going until the goal is met. Use it when the model can hold the whole job at once. decompose splits the goal into ordered slices first, then runs the same loop with that plan pinned as a TODO it re-injects every turn — so you have a running program after the first slice, and it grows from there. Use it when the job is big enough that the model would otherwise lose the thread. loop is an older name for code and still works.

Operate a stack — sense, localize the failing service, fix, verify, roll back on failure

codezaiku fix myproject propose                 # diagnose and propose (default, safe)codezaiku fix myproject guarded                 # act, behind the full guard stackcodezaiku watch myproject propose 60            # continuous: fix on degraded, else reportcodezaiku investigate myproject                 # diagnose only — capped at localize, never acts

Scope can be local (myproject), remote (ssh://host/myproject) or a container (docker://name). Everything else — the health endpoint, the verify command — is auto-discovered.

Operate a whole machine — the same operator, with the boundary set to the box instead of one stack

codezaiku triage local                          # enumerate the box, report what is brokencodezaiku triage local "" 20 guarded            # ...and repair the unhealthy compose stackscodezaiku watch-machine local 300               # the same sweep on a loop, as a daemon

triage enumerates everything it can see — compose stacks, failed systemd units, host disk and memory — runs the SRE operator against each unhealthy stack, and surfaces the systemd and host findings for a human. Each stack is still bound by blast-radius and the authority ladder, so widening the boundary does not widen what any single fix may touch.

Note the difference in defaults, because it is the one place where a whole-machine command is less conservative than a per-stack one: triage reports unless you pass guarded or unattended, while watch-machine defaults to guarded — it is a daemon meant to keep a box healthy, so it acts. Pass a ceiling explicitly if you want it to only watch: codezaiku watch-machine local 300 "" propose. Run it under systemd on a real box.

Review security posture — report only, never auto-remediates

codezaiku secure local

Research a question against live sources

codezaiku research "what changed in the Foo API in v3" depth

Drive it from another agent

codezaiku run --text "add pagination" --output-format json   # one task, one JSON resultcodezaiku acp                                   # Agent Client Protocol v1 agent on stdiocodezaiku mcp                                   # MCP server on stdio, all surfaces exposednpx -y @wyrdsekai/codezaiku-mcp                 # the same, from any client that runs npm packages; installs the release if neededcodezaiku serve 7070                            # HTTP: POST /fix, GET /health, GET /audit

Safety

The operator can change your systems, so the defaults are conservative and the guards are not optional.

• Authority ladder — observe < localize < propose < guarded < unattended. Default propose: it tells you the command, it does not run it. An unproven fix never auto-applies.
• Blast radius 1 — a fix may touch the service it localized and nothing else.
• Rollback — snapshot before a destructive change, verify after, restore if verification fails. This has a counterfactual: with it on, a model that corrupted a database config was rolled back and the stack came back green; with it off, the same failure left the service dead.
• Harm check — a fix that repairs its target but breaks a healthy dependency is a failure.
• Kill switch — CODEZAIKU_OPS_HALT=on forces observe immediately.
• Security findings are report-only at every rung. A wrong reliability fix restarts a service; a wrong containment action firewalls your own load balancer.

Untrusted input is treated as untrusted: container logs are attacker-writable, and a measured injection through them steered the operator 40/40 on both model tiers before it was fixed structurally. See ARCHITECTURE.md §6.

What this is not

• Not a frontier coding agent. SWE-bench Lite ≈1/8 on the 9B; refactoring 0/8. It is not a replacement for tools built on much larger models.
• Not production-hardened. No long-running soak evidence yet.
• Not a multi-agent framework. One loop, good tools, hard measurement. An earlier blackboard/agent architecture was designed, partly built, and removed.

The full accounting is in LIMITATIONS.md.

Repository layout

bench/ is shipped on purpose. The rigs are how every number in LIMITATIONS.md was produced, including the ones that came out badly.

Documentation

• ARCHITECTURE.md — design
• LIMITATIONS.md — the measured numbers
• MODELS.md — choosing and running a model server
• PLATFORMS.md — Linux, Docker, macOS, Windows
• CONFIGURATION.md — the six settings that matter, and the rest
• DEPLOYING_AS_A_BACKEND.md — running it under another agent or orchestrator
• WITH_WYRDSEKAI.md — wiring it up as a Wyrdsekai coding backend
• ROADMAP.md — what is next, ordered by what measurement says is holding it back
• CONTRIBUTING.md — including the measurement rules
• SECURITY.md — reporting, and the agent's own threat model

Getting in touch. Bugs and feature requests belong in issues, where other people can see them and the answer. For anything else, [email protected]. Vulnerabilities go to [email protected] or a private advisory — see SECURITY.md; conduct concerns to [email protected].

The family

CodeZaiku is part of Wyrdsekai, and its sibling is ResearchZosho, the research library: it keeps what research runs find, checks the claims against their sources, and answers questions from what it holds. codezaiku install researchzosho puts it beside CodeZaiku, and the two share a model server, so one on-demand model on a machine serves both.

License

Apache 2.0 — see LICENSE.