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Create Beads Orchestration

Community
AvivK5498
create-beads-orchestration

Bootstrap lean multi-agent orchestration with beads task tracking. Use for projects needing agent delegation without heavy MCP overhead.

Overview

PublisherAvivK5498
RepositoryThe-Claude-Protocol
Skill namecreate-beads-orchestration
Stars
348
Forks
25
Bundled files
50
LicenseMIT
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.

  • 50 bundled files

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

  • Open source

    Published by AvivK5498 on GitHub. Read the source before you install it.

Installation

Install the Create Beads Orchestration 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.
  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/AvivK5498/The-Claude-Protocol.git \
  .claude/skills/create-beads-orchestration
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Create Beads Orchestration 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 Create Beads Orchestration 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 Create Beads Orchestration 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.

Create Beads Orchestration

Set up lightweight multi-agent orchestration with git-native task tracking for Claude Code.

What This Skill Does

This skill bootstraps a complete multi-agent workflow where:

  • Orchestrator (you) investigates issues, manages tasks, delegates implementation
  • Supervisors (specialized agents) execute fixes in isolated worktrees
  • Beads CLI tracks all work with git-native task management
  • Hooks enforce workflow discipline automatically

Each task gets its own worktree at .worktrees/bd-{BEAD_ID}/, keeping main clean and enabling parallel work.

Beads Kanban UI

The setup will auto-detect Beads Kanban UI and configure accordingly. If not found, you'll be offered to install it.


Step 0: Detect Setup State (ALWAYS RUN FIRST)

Check for bootstrap artifacts:

bash
ls .claude/agents/scout.md 2>/dev/null && echo "BOOTSTRAP_COMPLETE" || echo "FRESH_SETUP"

If BOOTSTRAP_COMPLETE:

  • Bootstrap already ran in a previous session
  • Skip directly to Step 4: Run Discovery
  • Do NOT ask for project info or run bootstrap again

If FRESH_SETUP:

  • This is a new installation
  • Proceed to Step 1: Get Project Info

Workflow Overview

The setup is NOT complete until Step 4 (discovery) has run.


Step 1: Get Project Info (Fresh Setup Only)

  1. Project directory: Where to install (default: current working directory)
  2. Project name: For agent templates (will auto-infer from package.json/pyproject.toml if not provided)
  3. Kanban UI: Auto-detect, or ask the user to install

1.1 Get Project Directory and Name

Ask the user or auto-detect from package.json/pyproject.toml.

1.2 Detect or Install Kanban UI

bash
which bead-kanban 2>/dev/null && echo "KANBAN_FOUND" || echo "KANBAN_NOT_FOUND"

If KANBAN_FOUND → Use --with-kanban-ui flag. Tell the user:

Detected Beads Kanban UI. Configuring worktree management via API.

If KANBAN_NOT_FOUND → Ask:

AskUserQuestion(
  questions=[
    {
      "question": "Beads Kanban UI not detected. It adds a visual kanban board with dependency graphs and API-driven worktree management. Install it?",
      "header": "Kanban UI",
      "options": [
        {"label": "Yes, install it (Recommended)", "description": "Runs: npm install -g beads-kanban-ui"},
        {"label": "Skip", "description": "Use git worktrees directly. You can install later."}
      ],
      "multiSelect": false
    }
  ]
)
  • If "Yes" → Run npm install -g beads-kanban-ui, then use --with-kanban-ui flag
  • If "Skip" → do NOT use --with-kanban-ui flag

Step 2: Run Bootstrap

bash
# With Kanban UI:
npx beads-orchestration@latest bootstrap \
  --project-name "{{PROJECT_NAME}}" \
  --project-dir "{{PROJECT_DIR}}" \
  --with-kanban-ui

# Without Kanban UI (git worktrees only):
npx beads-orchestration@latest bootstrap \
  --project-name "{{PROJECT_NAME}}" \
  --project-dir "{{PROJECT_DIR}}"

The bootstrap script will:

  1. Install beads CLI (via brew, npm, or go)
  2. Initialize .beads/ directory
  3. Copy agent templates to .claude/agents/
  4. Copy hooks to .claude/hooks/
  5. Configure .claude/settings.json
  6. Create CLAUDE.md with orchestrator instructions
  7. Update .gitignore

Verify bootstrap completed successfully before proceeding.


Step 3: STOP - User Must Restart

Tell the user:

Setup phase complete. You MUST restart Claude Code now.

The new hooks and MCP configuration will only load after restart.

After restarting:

  1. Open this same project directory
  2. Tell me "Continue orchestration setup" or run /create-beads-orchestration again
  3. I will run the discovery agent to complete setup

Do not skip this restart - the orchestration will not work without it.

DO NOT proceed to Step 4 in this session. The restart is mandatory.


Step 4: Run Discovery (After Restart OR Detection)

  1. Verify bootstrap completed (check for .claude/agents/scout.md) - already done in Step 0
  2. Run the discovery agent:
python
Task(
    subagent_type="discovery",
    prompt="Detect tech stack and create supervisors for this project"
)

Discovery will:

  • Scan package.json, requirements.txt, Dockerfile, etc.
  • Fetch specialist agents from external directory
  • Inject beads workflow into each supervisor
  • Write supervisors to .claude/agents/
  1. After discovery completes, tell the user:

Orchestration setup complete!

Created supervisors: [list what discovery created]

You can now use the orchestration workflow:

  • Create tasks with bd create "Task name" -d "Description"
  • The orchestrator will delegate to appropriate supervisors
  • All work requires code review before completion

What This Creates

  • Beads CLI for git-native task tracking (one bead = one worktree = one task)
  • Core agents: scout, detective, architect, scribe, code-reviewer (all run via Claude Task)
  • Discovery agent: Auto-detects tech stack and creates specialized supervisors
  • Hooks: Enforce orchestrator discipline, code review gates, concise responses
  • Worktree-per-task workflow: Isolated development in .worktrees/bd-{BEAD_ID}/

With --with-kanban-ui:

  • Worktrees created via API (localhost:3008) with git fallback
  • Requires Beads Kanban UI running

Without --with-kanban-ui:

  • Worktrees created via raw git commands

Epic Workflow (Cross-Domain Features)

For features requiring multiple supervisors (e.g., DB + API + Frontend), use the epic workflow:

When to Use Epics

Task TypeWorkflow
Single-domain (one supervisor)Standalone bead
Cross-domain (multiple supervisors)Epic with children

Epic Workflow Steps

  1. Create epic: bd create "Feature name" -d "Description" --type epic
  2. Create design doc (if needed): Dispatch architect to create .designs/{EPIC_ID}.md
  3. Link design: bd update {EPIC_ID} --design ".designs/{EPIC_ID}.md"
  4. Create children with dependencies:
    bash
    bd create "DB schema" -d "..." --parent {EPIC_ID}              # BD-001.1
    bd create "API endpoints" -d "..." --parent {EPIC_ID} --deps BD-001.1  # BD-001.2
    bd create "Frontend" -d "..." --parent {EPIC_ID} --deps BD-001.2       # BD-001.3
  5. Dispatch sequentially: Use bd ready to find unblocked tasks (each child gets own worktree)
  6. User merges each PR: Wait for child's PR to merge before dispatching next
  7. Close epic: bd close {EPIC_ID} after all children merged

Design Docs

Design docs ensure consistency across epic children:

  • Schema definitions (exact column names, types)
  • API contracts (endpoints, request/response shapes)
  • Shared constants/enums
  • Data flow between layers

Key rule: Orchestrator dispatches architect to create design docs. Orchestrator never writes design docs directly.

Hooks Enforce Epic Workflow

  • enforce-sequential-dispatch.sh: Blocks dispatch if task has unresolved blockers
  • enforce-bead-for-supervisor.sh: Requires BEAD_ID for all supervisors
  • validate-completion.sh: Verifies worktree, push, bead status before supervisor completes

Requirements

  • beads CLI: Installed automatically by bootstrap (via brew, npm, or go)

More Information

See the full documentation: https://github.com/AvivK5498/The-Claude-Protocol

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 Create Beads Orchestration AI skill do?

Bootstrap lean multi-agent orchestration with beads task tracking. Use for projects needing agent delegation without heavy MCP overhead.

Why use Create Beads Orchestration on TypingMind?

Because you install it once and use it with any model. Create Beads Orchestration 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 Create Beads Orchestration in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/AvivK5498/The-Claude-Protocol/tree/main. 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 Create Beads Orchestration?

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 Create Beads Orchestration?

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

Is the Create Beads Orchestration AI skill free?

Yes. It is published on GitHub by AvivK5498 under the MIT 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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