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ATLAS — AI Cockpit

An auditable AI operator cockpit for developers and power users.
One runtime for missions, agents, tools, knowledge, approvals, and operational state.

npm version MIT License Platform: Windows x64 CI status

Install · Architecture · Operations · Known limitations · Security

npm install --global @systemsl2/atlas

Open research preview. The repository and Windows x64 npm package are public. Independent clean-machine feedback is welcome; do not use the preview with sensitive production data.


What ATLAS is

ATLAS is a local workspace for running AI agents as part of real, organized work. Instead of keeping your conversations, tools, tasks, files, and results in separate places, ATLAS brings them together in one system.

You give ATLAS a goal. It can break that goal into work, use the tools you allow, coordinate more than one agent, keep useful context between sessions, and show you what happened. Important actions can require your approval, and ATLAS keeps a record of the request, the action, the result, and the checks that followed.

ATLAS is built for work that lasts longer than a single chat. It is closer to an AI operations desk than a chatbot: the chat is one way to control the system, while the missions, saved knowledge, tools, approvals, and history continue behind it.

The ATLAS cockpit — Observatory view

What problem it solves

Most AI tools are good at answering one message. Longer work is harder:

  • the agent forgets why a decision was made;
  • work is split across chats and terminal windows;
  • tool calls happen without a clear review trail;
  • restarting the app can interrupt an unfinished task;
  • several agents can duplicate work or lose track of ownership;
  • useful project knowledge stays buried in old conversations.

ATLAS gives those pieces a shared home. A mission has a goal, runs, messages, artifacts, approvals, and a visible history. This makes it easier to continue work, inspect a result, recover after a failure, and understand what the AI actually did.

What ATLAS can do

  • Run goal-based missions — Start with an outcome instead of managing every prompt. Missions can pause, resume, and continue until their completion checks are satisfied.
  • Keep conversations and work state — Messages, runs, results, and relevant knowledge can survive restarts instead of disappearing with one terminal session.
  • Coordinate agents and teams — Create focused agents, give them separate work, steer active work, and collect their results in one place.
  • Use tools with approval controls — Read-only work can flow quickly while sensitive or changing actions can wait for an operator decision.
  • Record what happened — ATLAS keeps an audit trail for missions, tool requests, approvals, outputs, failures, and verification.
  • Connect to different model providers — Use supported cloud providers, local models, or operator-installed runtimes such as Codex without tying the whole system to one model company.
  • Build useful project memory — Ingest documentation and notes into a searchable wiki and knowledge graph, with source information kept alongside the content.
  • Work from the cockpit or terminal — The browser cockpit, terminal interface, and command-line tools use the same runtime and saved state.

A simple example

Suppose you ask ATLAS to prepare a software release.

  1. ATLAS creates a mission for the release outcome.
  2. It reads the project state and gathers the relevant checks.
  3. Separate agents can inspect tests, installation, documentation, and release files.
  4. A risky action, such as publishing or deleting data, waits for approval.
  5. Test results and produced files are attached to the run.
  6. If the process stops, the mission can resume from saved state.
  7. The ledger shows what was requested, what ran, what changed, and whether the final verification passed.

The same structure can support research, company operations, knowledge maintenance, content work, or any other workflow that benefits from clear goals and traceable actions.

How it fits together

ATLAS has four main parts:

Part In plain language
Runtime Runs missions, agents, tools, approvals, and background work
Saved state Stores goals, runs, messages, configuration, and the audit history
Knowledge Turns approved sources into a wiki and searchable project memory
Surfaces Lets you control the same system from the browser, terminal, or scripts

The Rust gateway handles the local API and new infrastructure. Python remains where the Hermes-based agent and model integrations need it. The installer ships the required runtime pieces together, so normal users do not need to assemble each part by hand.

Main capabilities

Durable actors
Agents that survive interruptions
ATLAS tracks active agents and their results so work can recover cleanly after a restart or process failure.
Goal-driven missions
Goal-driven missions
Use /goal to work toward an outcome with clear completion checks, pause and resume support, and a visible mission history.
Audit ledger
Audit ledger
Review missions, runs, tool approvals, files, results, and failures in one traceable record.
Three surfaces
One system, three surfaces
Use the browser cockpit, terminal interface, or scriptable CLI without creating three separate sources of truth.
Provider mesh
Choice of AI providers
Connect API-key, sign-in, local, and separately installed model providers. Optional Claude and Codex support stays separate from the base install.
Module framework
Modules you can keep
A module declares commands, pages, doctrine, typed records and MCP servers in one manifest. Yours live under ATLAS_HOME/modules and remain in place when ATLAS updates.
  • Persistent knowledge — wiki/codex ingestion, provenance, a queryable knowledge graph the agent can read and write, and configurable graph scopes.
  • Optional modules with real capability — activating a module gives the agent its doctrine (injected into runs, budgeted), its typed records, its workflows and its MCP servers; deactivating retracts all of it without deleting the data. Bundled: GSD/L2 execution doctrine and evidence-gated Outreach.
  • Working memory that survives a reset — the agent keeps plans, findings and drafts in a scratchpad with an expiry, and a run resuming the same session is handed them back automatically instead of re-deriving them.
  • Disposable tools, with the reason attached — when a missing capability blocks it, the agent can write a bounded one-off script to an ATLAS-owned scratch directory and run it out of process under the normal permission rules. It cannot do so silently: it must state what it searched and why this is disposable, and that reasoning is recorded permanently even after the tool expires. It expires on the next restart unless you keep it; Control → Tools shows everything it is holding and why.
  • Native direction — the gateway and new infrastructure are Rust-first; the Hermes plugin surface and LLM adapters remain Python where that boundary is useful.

Who ATLAS is for

ATLAS is currently aimed at developers, technical operators, founders, researchers, and power users who want an AI system they can inspect and control. It is especially useful when work spans many steps, tools, agents, or sessions.

It is not yet a finished consumer assistant or a hosted service that hides every technical detail. This is an open research preview. You should expect to review approvals, inspect important outputs, and avoid sensitive production data until the remaining platform and clean-machine checks are complete.

Installation

Windows x64 preview:

npm install --global @systemsl2/atlas

The npm launcher installs a verified platform release, then delegates normal commands to it. Application versions live outside the source repository and outside live operator state. atlas update replaces the launcher/runtime version while preserving the database, configuration, credentials, wiki, logs, and user modules.

The published Windows package contains an embedded Python runtime, the Rust gateway, terminal UI, compiled WebUI, runtime services, and bundled modules. Node.js 20+ and npm are the only prerequisites; Git, Python, Go, and Rust are not required. Source developers can still use the PowerShell bootstrap:

$f="$env:TEMP\atlas-install.ps1"; (irm https://raw.githubusercontent.com/L2-ootm/L2-ATLAS-PROJECT/main/install/install.ps1) | Set-Content -Path $f -Encoding UTF8; powershell -ExecutionPolicy Bypass -File $f

The PowerShell URL is public and now uses the same npm release path by default. See the installation guide for source, release, update, rollback, and clean-machine details.

First run

atlas up --services gateway,cockpit
atlas doctor
atlas

atlas up starts the local gateway and cockpit. atlas opens the terminal surface. Mock Mode supports the core demo path without a provider API key.

What happens to your data

ATLAS separates the application files from your working data:

  • application versions are installed in a versioned application directory;
  • configuration, credentials, the database, logs, wiki content, and personal modules live under ATLAS_HOME;
  • updates install and verify a new application version before switching to it;
  • rollback can return to the previous verified application version;
  • uninstall keeps operator state unless you explicitly request a validated purge.

ATLAS is local-first, but model providers and connected tools may send the information needed for a request to their own services. Review each provider and tool before using private data.

Update model

npm launcher          npm global prefix
immutable releases    OS application-data/atlas/versions/<version>
active pointer        OS application-data/atlas/current
operator state        ~/.atlas (or ATLAS_HOME)
user modules          ~/.atlas/modules

Updates never target this development checkout. A failed download, checksum, or entrypoint validation cannot activate the new version; the previous verified version remains available to atlas rollback.

Repository map

Area Purpose
foundation/atlas-hermes/ Hermes-derived ATLAS foundation and divergence record
services/agent-runtime/ Runtime orchestration and CLI
native/atlas-core-rs/ Rust gateway and native infrastructure
services/web-ui-react/ WebUI operator cockpit
services/atlas-tui/ Current Go terminal surface
services/atlas-terminal/ Next terminal surface under gated evaluation
packages/atlas-cli/ npm installer, updater, rollback, and runtime launcher
modules/ Modules bundled with ATLAS releases
docs/ Architecture, operations, decisions, verification, and release material

Trust and project status

ATLAS is intentionally honest about unfinished work. Version 0.1.5 is public on npm for Windows x64 and as GitHub runtime bundles for Windows x64, Linux x64, Intel macOS, and Apple Silicon macOS. On 2026-07-29, the public npm launcher and Windows runtime were installed again from the anonymous registry into isolated application and state directories. The install reported 0.1.5, every packaged-file checksum matched, and the install-only doctor reported healthy. Linux and macOS bundles passed the automated build and test matrix but still need independent clean-machine acceptance before they should be treated as equally proven. Repository cleanup and the configured full-history secret scan are complete. Release status is tracked in docs/release/RELEASE_CHECKLIST.md; internal planning/session state is deliberately excluded from the public repository.

The foundation is vendored and evolved in place rather than treated as a black-box dependency. Provenance and changes are documented in foundation/ATTRIBUTION.md and foundation/DIVERGENCE_LOG.md.

Contributing

Read CONTRIBUTING.md, the Code of Conduct, and CLA.md before opening a contribution. Security issues should follow the private process in SECURITY.md.

License

ATLAS is available under the MIT License. Third-party licenses and derived code attribution are documented in THIRD_PARTY_LICENSES.md and ATTRIBUTION.md.

ATLAS governance seal
FOR THOSE WHO BUILD WHAT ENDURES.

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Auditable AI operator cockpit for missions, agents, tools, knowledge, approvals, and local operational evidence.

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