Skip to content

chernistry/bernstein

Use this GitHub action with your project
Add this Action to an existing workflow or create a new one
View on Marketplace

Folders and files

NameName
Last commit message
Last commit date

Latest commit

 

History

1,686 Commits
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
Bernstein

Orchestrate any AI coding agent. Any model. One command.

Bernstein in action — parallel AI agents orchestrated in real time

CI codecov GitHub stars PyPI npm VS Marketplace Python 3.12+ License MCP Compatible A2A Compatible Share on X

Documentation · Getting Started · Glossary · Limitations

Wall of fame

"lol, good luck, keep vibecoding shit that you have no idea about xD"PeaceFirePL, Reddit


Bernstein takes a goal, breaks it into tasks, assigns them to AI coding agents running in parallel, verifies the output, and merges the results. You come back to working code, passing tests, and a clean git history.

No framework to learn. No vendor lock-in. Agents are interchangeable workers — swap any agent, any model, any provider. The orchestrator itself is deterministic Python code. Zero LLM tokens on scheduling.

pip install bernstein
bernstein -g "Add JWT auth with refresh tokens, tests, and API docs"

Also available via pipx, uv tool install, brew, dnf copr, and npx bernstein-orchestrator. See install options.

Supported agents

Bernstein auto-discovers installed CLI agents. Mix them in the same run — cheap local models for boilerplate, heavy cloud models for architecture.

Agent Models Install
Claude Code opus 4.6, sonnet 4.6, haiku 4.5 npm install -g @anthropic-ai/claude-code
Codex CLI gpt-5.4, gpt-5.4-mini npm install -g @openai/codex
Gemini CLI gemini-3.1-pro, gemini-3-flash npm install -g @google/gemini-cli
Cursor sonnet 4.6, opus 4.6, gpt-5.4 Cursor app
Aider Any OpenAI/Anthropic-compatible pip install aider-chat
Ollama + Aider Local models (offline) brew install ollama
Amp, Cody, Continue.dev, Goose, Kilo, Kiro, OpenCode, Qwen, Roo Code, Tabby Various See docs
Generic Any CLI with --prompt Built-in

Any adapter also works as the internal scheduler LLM — run the entire stack without any specific provider:

internal_llm_provider: gemini            # or qwen, ollama, codex, goose, ...
internal_llm_model: gemini-3.1-pro-preview

Tip

Run bernstein --headless for CI pipelines — no TUI, structured JSON output, non-zero exit on failure.

Quick start

cd your-project
bernstein init                    # creates .sdd/ workspace + bernstein.yaml
bernstein -g "Add rate limiting"  # agents spawn, work in parallel, verify, exit
bernstein live                    # watch progress in the TUI dashboard
bernstein stop                    # graceful shutdown with drain

For multi-stage projects, define a YAML plan:

bernstein run plan.yaml           # skips LLM planning, goes straight to execution
bernstein run --dry-run plan.yaml # preview tasks and estimated cost

How it works

  1. Decompose — the manager breaks your goal into tasks with roles, owned files, and completion signals
  2. Spawn — agents start in isolated git worktrees, one per task. Main branch stays clean.
  3. Verify — the janitor checks concrete signals: tests pass, files exist, lint clean, types correct
  4. Merge — verified work lands in main. Failed tasks get retried or routed to a different model.

The orchestrator is a Python scheduler, not an LLM. Scheduling decisions are deterministic, auditable, and reproducible.

Capabilities

Core orchestration — parallel execution, git worktree isolation, janitor verification, quality gates (lint + types + PII scan), cross-model code review, circuit breaker for misbehaving agents, token growth monitoring with auto-intervention.

Intelligence — contextual bandit router learns optimal model/effort pairs over time. Knowledge graph for codebase impact analysis. Semantic caching saves tokens on repeated patterns. Cost anomaly detection with Z-score flagging.

Enterprise — HMAC-chained tamper-evident audit logs. Policy limits with fail-open defaults and multi-tenant isolation. PII output gating. OAuth 2.0 PKCE. SSO/SAML/OIDC auth. WAL crash recovery — no silent data loss.

Observability — Prometheus /metrics, OTel exporter presets, Grafana dashboards. Per-model cost tracking (bernstein cost). Terminal TUI and web dashboard. Agent process visibility in ps.

Ecosystem — MCP server mode, A2A protocol support, GitHub App integration, pluggy-based plugin system, multi-repo workspaces, cluster mode for distributed execution, self-evolution via --evolve.

Full feature matrix: FEATURE_MATRIX.md

How it compares

Feature Bernstein CrewAI AutoGen LangGraph
Orchestrator Deterministic code LLM-driven LLM-driven Graph + LLM
Works with Any CLI agent (18+) Python SDK classes Python agents LangChain nodes
Git isolation Worktrees per agent No No No
Verification Janitor + quality gates No No Conditional edges
Cost tracking Built-in No No No
State model File-based (.sdd/) In-memory In-memory Checkpointer
Self-evolution Built-in No No No
Declarative plans (YAML) Yes Partial No Yes
Model routing per task Yes No No Manual
MCP support Yes No No No
Agent-to-agent chat No Yes Yes No
Web UI No Yes Yes Partial
Cloud hosted option No Yes No Yes
Built-in RAG/retrieval No Yes Yes Yes

Last verified: 2026-04-07. See full comparison pages for detailed feature matrices.

Monitoring

bernstein live       # TUI dashboard
bernstein dashboard  # web dashboard
bernstein status     # task summary
bernstein ps         # running agents
bernstein cost       # spend by model/task
bernstein doctor     # pre-flight checks
bernstein recap      # post-run summary
bernstein trace <ID> # agent decision trace
bernstein run-changelog --hours 48  # changelog from agent-produced diffs
bernstein explain <cmd>  # detailed help with examples
bernstein dry-run    # preview tasks without executing
bernstein dep-impact # API breakage + downstream caller impact
bernstein aliases    # show command shortcuts
bernstein config-path    # show config file locations
bernstein init-wizard    # interactive project setup
bernstein fingerprint build --corpus-dir ~/oss-corpus  # build local similarity index
bernstein fingerprint check src/foo.py                 # check generated code against the index

Install

Method Command
pip pip install bernstein
pipx pipx install bernstein
uv uv tool install bernstein
Homebrew brew tap chernistry/bernstein && brew install bernstein
Fedora / RHEL sudo dnf copr enable alexchernysh/bernstein && sudo dnf install bernstein
npm (wrapper) npx bernstein-orchestrator

Editor extensions: VS Marketplace · Open VSX

Contributing

PRs welcome. See CONTRIBUTING.md for setup and code style.

Support

If Bernstein saves you time: GitHub Sponsors · Open Collective

License

Apache License 2.0


"To achieve great things, two things are needed: a plan and not quite enough time." — Leonard Bernstein