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Bernstein Run

OrganizationPopular
sipyourdrink-ltd
bernstein-run

Run a verified multi-agent goal with Bernstein. Use when a task is too large for a single agent session: Bernstein decomposes the goal into tasks, spawns CLI coding agents in parallel git worktrees, verifies their output, and merges results. Also use to check run status, costs, and to verify a finished run against its lineage and audit chain.

Overview

Publishersipyourdrink-ltd
Repositorybernstein
Skill namebernstein-run
Stars
1.2K
Forks
178
Bundled files
1
LicenseApache-2.0
Links
  • Markdown instructions

    A SKILL.md file the model loads on demand, so it only costs tokens when a request actually matches.

  • Works with any LLM

    AI skills are plain Markdown, not provider-specific code, so this works with GPT, Claude, Gemini, Grok, or a local model.

  • 1 bundled files

    Scripts, templates, and references the model can read while it works. Files are read-only and never executed.

  • Open source

    Published by sipyourdrink-ltd on GitHub. Read the source before you install it.

Installation

Install the Bernstein Run AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

1

Install in TypingMind

TypingMind installs a skill straight from its GitHub folder — it reads SKILL.md, bundles the resource files, and stores the result locally.

  1. Open the app and go to Plugins → Skills.
  2. Choose "Install from GitHub".
  3. Paste the skill folder URL below and confirm.
    https://github.com/sipyourdrink-ltd/bernstein/tree/main/skills/bernstein-run
  4. Enable the skill in any chat where you want it available.
Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.
2

Install in another agent

Any agent that reads the Agent Skills format can use this skill — copy the folder into that agent's skills directory.

Claude Code — .claude/skills
git clone --depth 1 https://github.com/sipyourdrink-ltd/bernstein.git /tmp/bernstein
mkdir -p .claude/skills
cp -r /tmp/bernstein/skills/bernstein-run .claude/skills/bernstein-run
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Bernstein Run in any TypingMind chat and the model takes it from there. Its name and description sit in the system prompt, and the moment a request matches, the model loads the full instructions itself — you never invoke it by hand, and it costs no tokens until it is actually used.

The model loads Bernstein Run on its own as soon as a request matches it.

Works with any AI model

AI skills are plain Markdown instructions rather than provider-specific code, so Bernstein Run is not tied to the model it was written for. Install it once in TypingMind and use it with GPT-5, Claude, Gemini, Grok, DeepSeek, Mistral, Llama, or a local model you run yourself — all on your own API keys.

  • Loaded only when it is needed

    The system prompt carries just the name and description. The instructions are fetched on the first matching request, so an idle skill costs nothing.

  • Switch models mid-chat

    Because the skill is instructions rather than code, changing model does not break it — the next model reads the same SKILL.md.

Skill instructions

This is the SKILL.md content the model loads. Read it before installing — a skill is instructions your model will follow.

Run a verified multi-agent goal

Bernstein is the open-source governance layer for AI agents, with a deterministic multi-agent scheduler. This skill wraps the three-step operator loop: submit a goal, monitor progress, and verify the finished run against its Merkle-chained lineage journal and HMAC audit chain.

Prerequisites

  • bernstein on PATH (pip install bernstein or uv tool install bernstein).
  • Run commands from the project root (the directory holding .sdd/ after the first run).
  • First-time setup: bernstein init scaffolds config and templates.

Workflow

1. Submit

bash
bernstein run -g "<goal>"
  • The goal is a plain-English description of what to build or fix.
  • Bernstein plans tasks, assigns roles (backend, frontend, qa, security, devops), and spawns agents in isolated git worktrees.
  • Preview without spending: bernstein run --dry-run -g "<goal>".

2. Monitor

bash
bernstein status
bernstein cost
  • status shows task summary and agent health.
  • cost shows the spend so far against configured budgets.

3. Verify

bash
bernstein lineage verify <run_id>
bernstein audit verify
  • lineage verify recomputes the run's Merkle hash chain and every HMAC tag; exit 0 means the chain is intact and non-empty.
  • audit verify checks the HMAC audit chain and Merkle tree across the whole workspace; run it before trusting or shipping the result.

Report the run as complete only when both verifications exit 0.

Verifying this skill's own install

Installs of this skill are receipt-backed. To confirm bernstein is on PATH and the bundled skill asset resolves in this session:

bash
bernstein skills package show

To prove the skill content the session is driving matches what was installed:

bash
bernstein skills package verify --dest <path-to-this-skill-directory>

Exit 0 means the installed tree's content address matches a receipt anchored in the lineage spine and audit chain. These two commands are the self-check contract the multi-host conformance sweep replays per agent host (bernstein skills package conformance).

Notes

  • Never mark a goal done from agent output alone; the lineage and audit verifications are the completion evidence.
  • If bernstein is not installed, say so and point at the prerequisites above; do not attempt to reimplement orchestration inline.
  • See references/worked-examples.md for end-to-end transcripts and per-host invocation notes.

Bundled files

The model reads these on demand while the skill is loaded. They are exposed as readable files and are never executed.

Frequently asked questions

What does the Bernstein Run AI skill do?

Run a verified multi-agent goal with Bernstein. Use when a task is too large for a single agent session: Bernstein decomposes the goal into tasks, spawns CLI coding agents in parallel git worktrees, verifies their output, and merges results. Also use to check run status, costs, and to verify a finished run against its lineage and audit chain.

Why use Bernstein Run on TypingMind?

Because you install it once and use it with any model. Bernstein Run is plain Markdown rather than provider-specific code, so the same skill runs on GPT-5, Claude, Gemini, Grok, or a local model — and you can switch model mid-chat without it breaking. TypingMind runs on your own API keys, so you pay providers directly instead of a per-seat subscription, and your skills and chats stay in your own storage.

How do I install Bernstein Run in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/sipyourdrink-ltd/bernstein/tree/main/skills/bernstein-run. TypingMind reads its SKILL.md and bundles its files and installs it as a skill you can enable per chat.

Which AI models can use Bernstein Run?

Any model you connect in TypingMind. AI skills are plain Markdown instructions rather than provider-specific code, so GPT, Claude, Gemini, Grok, and local models can all load this skill when a request matches it.

How many AI models can I use with Bernstein Run?

As many as you like. As long as a model supports skills, you can use Bernstein Run with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.

Is the Bernstein Run AI skill free?

Yes. It is published on GitHub by sipyourdrink-ltd under the Apache-2.0 license. You only pay your own AI provider for the tokens you use.

What are AI skills?

An AI skill is a reusable instruction bundle that teaches an AI model how to do one specific task. It follows the open Agent Skills format: a SKILL.md file with a name and description, plus any scripts, templates or reference files the model may need. The model reads the instructions only when your request matches the skill, so an installed skill costs nothing until it is used.

How are AI skills different from plugins or MCP servers?

A plugin or MCP server gives a model new tools to call — code that runs somewhere and returns a result. An AI skill gives the model knowledge and process instead: how to approach a task, which steps to follow, what good output looks like. Skills are plain Markdown, so they need no server, no API key and no runtime, and they work with any model.

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