Skip to main content

Developer Infrastructure Platform for AI-assisted development: knowledge-driven, multi-agent, stdlib-only.

Project description

NX AI Engineer

v1.0.0 · stdlib-only · zero runtime dependencies · 238 tests green · CHANGELOG · ROADMAP · RELEASE_NOTES

NX AI Engineer is a Developer Infrastructure Platform for AI-assisted software development. Its job is to organize knowledge, context and execution so that any AI model becomes dramatically more effective while building software.

NX AI Engineer does not replace Claude Code, GPT, Gemini or any other model. All intelligence belongs to the model. All organization belongs to NX.

It installs like any modern tool — a package from PyPI and a single nxai CLI — and works on any stack (Node, Python, Go, Rust, Java, Nx and other monorepos, …), which it discovers at runtime.

Guides: Installer · Upgrade · Architecture · SDK · Engine · Workflow · Plugin · Knowledge · Project Brain · Contributing

Install

pip install nx-ai-engineer
nxai version
nxai doctor

No manual file copying, ever. The platform code lives in the installed packages; your project's .ai-project-assistant/ holds data only.

Quickstart

From the root of any repository:

nxai init                      # scaffold .ai-project-assistant + audit + Brain + Knowledge + Vault
nxai plan "Add OAuth login"    # plan a goal into a task (agents, order, locks)
nxai execute "Add OAuth login" # full end-to-end flow (Dry Run -> Test -> Execute; dry-run by default)
nxai review                    # consolidated diff review
nxai knowledge status          # the three memories: Brain / Obsidian / Git
nxai docs                      # the bundled guides

Everything is safe by default: execution always runs Dry Run → Test → Execute and defaults to dry-run.

What it does

NX turns a single request into a disciplined flow — never "implement immediately":

audit → discover → impact → risk → plan → subtasks → agents → order →
implement → test → review → consolidate → document → report

It coordinates specialized agents (backend, frontend, database, ai, security, devops, qa, docs, plus read-only architect/planner/reviewer/delivery) that work safely on the same codebase via advisory locks and isolated git worktrees.

The three memories

Memory Component Role
Operational Project Brain (brain/) Structured knowledge — never code, never model output.
Organizational Obsidian Vault (obsidian/, folders 00 Dashboard14 Retrospectives) A navigable, auto-synced visual reflection of the Brain.
Historical Git (opt-in) Immutable snapshots of the knowledge over time.

The Knowledge Engine has exactly five responsibilities — discover, index, relate, update, deliver_context — and never reasons, learns programming, or interprets code. It only reduces the model's cognitive load: the richer the project history, the sharper the model's work, the fewer tokens spent.

The Engineering Contract

How knowledge reaches the agent. An agent doesn't get an ad-hoc prompt — it gets a contract: a declarative, predictable statement of what applies to a task.

Task → Engineering Contract → Context Builder → Model → Result → Knowledge Update

The contract assembles context (files/areas), knowledge (ADRs/patterns), engineering (the Engineering Packs that apply), constraints, requirements (mandatory tests/validations/checklists) and brain facets. Packs are contracts: they declare applies_to, so the Backend Agent automatically receives the Security, LGPD and Multi-Tenant contracts — without anyone remembering to ask. The contract is enforced at delivery (a gate blocks shipping untested code when an applicable pack mandates tests). See the Engineering Contract guide.

nxai contract --agent backend "Implement Google login" --files auth.py --areas api/auth

CLI

Command Purpose
nxai init Initialize .ai-project-assistant (scaffold + audit + Brain + Knowledge + Vault)
nxai audit Discover & persist the architecture
nxai plan "<goal>" Plan a goal into a task
nxai execute "<goal>" Full end-to-end flow (alias of pipeline)
nxai review Consolidated diff review
nxai knowledge <index|list|retrieve|sync|status|graph> Knowledge Engine + Providers
nxai obsidian <sync|status> Sync/inspect the Obsidian vault
nxai contract --agent <a> "<task>" Build the Engineering Contract for an agent + task
nxai pack <list|show|add|remove> Engineering Packs (domain knowledge bundles)
nxai scaffold [--stack ...] Lay open-source/GitHub repo standards into the project
nxai graph Show the project Knowledge Graph
nxai report Consolidated report (status + insights + metrics)
nxai docs [name] List the bundled guides, or print one
nxai doctor Health-check the install and project
nxai update Refresh template assets (keeps Brain/Vault/config/history)
nxai version Show version

…plus decide, dispatch, context, run, deliver, pipeline, metrics, insights, recommend, worktree, tasks, locks, unlock, status. (The legacy nx alias is also installed.)

Engineering Packs

Domain knowledge — not code — that makes the agents apply a domain's rules correctly:

nxai pack list                 # browse the catalog
nxai pack add lgpd             # install LGPD/privacy policies + checklists + context
nxai pack add security         # OWASP/ASVS-aligned application security

Built-in packs: lgpd, security, repo-standards (stable) plus scaffolds for owasp, ai, cloud, docker, multi-tenant, observability, testing, billing, authentication. Once installed, the Pack Provider feeds the pack's policies/checklists/context to the agents working in that domain. Packs contain no code and no AI. See the Packs Guide; third parties can publish their own (the pack Marketplace).

Packs (knowledge) × Specialist Agents (execution)

The knowledge lives in the Pack; a Specialist Agent just executes using it — the agent is disposable, the knowledge is not. The Database category ships postgres and mongodb (full: rules, patterns, anti-patterns, performance, checklists, security) plus mysql/sqlserver/oracle/sqlite/redis/cassandra/elastic/ neo4j, with specialist agents database-relational, database-nosql and a read-only database-reviewer (never implements — it asks and blocks on duplicate tables, redundant indexes, anti-patterns). The Engineering Contract auto-attaches the right pack to each agent, so the same PostgreSQL knowledge serves the relational, reviewer and migration work without duplication.

nxai pack add postgres
nxai contract --agent database-relational "Add an orders table"   # postgres pack auto-attached

Standardize a repository

The repo-standards pack also ships concrete templates that nxai scaffold lays into a project's repo root — governance files, issue/PR templates and a CI workflow matched to the stack:

nxai scaffold --stack auto --dry-run   # preview
nxai scaffold --stack python           # CONTRIBUTING, CODE_OF_CONDUCT, SECURITY,
                                       # .github/ISSUE_TEMPLATE, PR template, CI, .gitignore

Idempotent — it never overwrites an existing file without --force.

Architecture

A monorepo of 9 acyclic, stdlib-only packages:

nx-core ← nx-workflow ← nx-sdk
nx-core ← nx-packs
nx-core ← nx-providers ← nx-obsidian ← nx-knowledge
{core, workflow, sdk, knowledge} ← nx-runtime ← nx-cli
Package Responsibility
nx-core Kernel (domain/states/lifecycle/engine), governance, observability, foundation
nx-workflow Reusable multi-step workflows
nx-sdk Public extension surface (agents/engines/workflows/adapters/plugins/tools)
nx-packs Engineering Packs catalog (domain knowledge bundles)
nx-providers Knowledge providers (filesystem, git, markdown, ADR, project-brain, packs) + the relate/graph primitive
nx-obsidian Obsidian provider + vault sync
nx-knowledge Knowledge Engine, registry, memory (Brain), evolution
nx-runtime Adapters, schedulers, intelligence, engines, composition-root pipeline
nx-cli The official nxai CLI + the deployable template

See docs/ARCHITECTURE.md. The acyclic graph is enforced by scripts/verify_packages.py; the full Quality Gate is scripts/quality_gate.py.

Extending

NX is built on an Open/Closed SDK — register agents, engines, workflows, adapters, plugins and tools without touching the core. See the SDK Guide and Plugin Guide.

Principles

  • All intelligence is the model's. NX organizes; it never reasons.
  • Stdlib-only core — zero third-party runtime dependencies.
  • Safe by default — Dry Run → Test → Execute; nothing destructive without intent.
  • The Brain never stores code — only structured knowledge.
  • Knowledge is leverage — more history ⇒ better context ⇒ fewer tokens.

License

MIT — see LICENSE.

Project details


Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

nx_ai_engineer-1.0.1.tar.gz (252.0 kB view details)

Uploaded Source

Built Distribution

If you're not sure about the file name format, learn more about wheel file names.

nx_ai_engineer-1.0.1-py3-none-any.whl (363.2 kB view details)

Uploaded Python 3

File details

Details for the file nx_ai_engineer-1.0.1.tar.gz.

File metadata

  • Download URL: nx_ai_engineer-1.0.1.tar.gz
  • Upload date:
  • Size: 252.0 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/6.1.0 CPython/3.13.12

File hashes

Hashes for nx_ai_engineer-1.0.1.tar.gz
Algorithm Hash digest
SHA256 ad88c9188d9cef07fb03e92c91108ecd488de86b6d6827bcf4739bf039d87c2d
MD5 e56eb392e12a644f9c164622b2a199df
BLAKE2b-256 c2ac5ccf8c8d1f9cf8645157d039c89e14c2714c3b57d6322f1c150e3a20a954

See more details on using hashes here.

File details

Details for the file nx_ai_engineer-1.0.1-py3-none-any.whl.

File metadata

  • Download URL: nx_ai_engineer-1.0.1-py3-none-any.whl
  • Upload date:
  • Size: 363.2 kB
  • Tags: Python 3
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/6.1.0 CPython/3.13.12

File hashes

Hashes for nx_ai_engineer-1.0.1-py3-none-any.whl
Algorithm Hash digest
SHA256 a7aeb53e31c59c6c0250fec588096ce9e043a14951b0e885f298079bb3a568cb
MD5 ae6adb6d62e132f2363709b30bbe5383
BLAKE2b-256 9502b00662c5a7de0cddd42dd272470b8d1e65e2dc0774c741d3e322f24f1e76

See more details on using hashes here.

Supported by

AWS Cloud computing and Security Sponsor Datadog Monitoring Depot Continuous Integration Fastly CDN Google Download Analytics Pingdom Monitoring Sentry Error logging StatusPage Status page