multi-model-orchestrator

SkillDocs & knowledge

Use when coordinating complex tasks across multiple AI agents with a centralized handoff document for planning, execution tracking, and feedback fusion.

Available today. Use it from your connected AI after setup.

Connect ahel once, and every AI you use reads what you have installed.

Then ask your AI: use the multi-model-orchestrator skill

What this skill tells your AI

The instructions your AI receives, as published by majiayu000/spellbook in skills/multi-model-orchestrator/SKILL.md and read by ahel’s review.

Decompose. Execute. Synthesize.

A lightweight skill for coordinating work across multiple AI agents (Claude, Opus, Haiku, Codex, or any agent) using a single handoff document as the source of truth.

Why This Skill

Complex work often requires:

  1. High-level planning — breaking down a big goal into concrete subtasks
  2. Parallel execution — different agents handling different task types simultaneously
  3. Feedback synthesis — collecting results and iterating intelligently
  4. Full traceability — understanding who did what, why, and what changed

This skill provides the structure and templates to do this cleanly.

Operating Contract

Direct actions: create or update one handoff document as the source of truth, decompose the goal into executor-ready subtasks, assign explicit dependencies, record execution results, and synthesize feedback into next steps.

Escalate before: starting execution when the goal, constraints, executor choice, writable scope, or done criteria are ambiguous.

Evidence-backed pushback: reject unverified completion claims, vague agent outputs, missing acceptance criteria, or parallel assignments that touch shared writable files without explicit ordering.

Feedback loop: after each execution round, update the handoff with result, evidence, blockers, and next action before assigning follow-up work.

When to Use

Use when:

  • A single-agent conversation would be too long or unfocused
  • You want to parallelize work across multiple specialized agents
  • You need to decompose a vague goal into specific, executor-ready tasks
  • You want to track decisions, changes, and feedback in one place
  • You're exploring multiple approaches simultaneously (A/B/C branches)

Don't use when:

  • The task is simple and one agent can handle it end-to-end
  • You don't need to track who did what
  • Execution is strictly sequential with no parallelization
  • The task is exploratory with no clear structure

Core Concepts

Handoff Document (Handoff)

A YAML file that serves as the single source of truth. It contains:

  • Goal — what are we trying to accomplish?
  • Subtasks — who does what, and what does success look like?
  • Context — code references, prior decisions, constraints
  • Execution Tracking — who executed, what was the result, what blockers?
  • Feedback — iterations, changes, and learnings

Agent Roles

You choose which agents execute which subtasks. Examples:

AgentBest For
Claude (or Fable)Planning, decomposition, architecture review, high-level strategy
OpusComplex reasoning, deep analysis, novel problem-solving
HaikuFast iteration, simple fixes, quick validation
CodexCode generation, refactoring, technical implementation
Claude CodeInteractive development, running code, verification

The Loop

1. Define Goal
    ↓
2. Fable/Claude decomposes into Handoff subtasks
    ↓
3. You assign subtasks to agents
    ↓
4. Agents execute in parallel or sequence
    ↓
5. You record results in Handoff
    ↓
6. Review, iterate, or complete

Quick Start

The full five-step walkthrough with copy-paste templates lives in references/quick-start.md. Summary:

  1. Create handoff — copy templates/handoff-template.yaml to .claude/handoffs/my-task.yaml.
  2. Decompose — ask Fable/Claude to break the goal into 3-5 subtasks; paste into subtasks.
  3. Execute — give each subtask's input to its assigned executor.
  4. Record — append the result to execution.rounds.
  5. Iterate or complete — update metadata.status toward complete.

Field-by-field reference: references/handoff-structure.md.

Complete Example

See references/add-auth-to-api.yaml for a real-world multi-agent execution walkthrough.

Using with Claude Code

  1. Save your handoff to .claude/handoffs/task.yaml
  2. Run: cat .claude/handoffs/task.yaml to load it in conversation
  3. Ask Claude to execute a subtask
  4. When done, update the handoff manually or using a script

For automation, see references/advanced-sync.md.

Using with Codex

Codex does not have handoff-specific subcommands. Use codex exec with a focused prompt that names the handoff file and the exact subtask:

codex exec "Read .claude/handoffs/task.yaml. Execute subtask task-1 only. Return the result, blockers, files changed, and verification evidence."

For decomposition:

codex exec "Read .claude/handoffs/task.yaml. Propose 3-5 YAML subtasks using goal.summary, goal.context, and goal.acceptance_criteria. Do not edit files."

Resources


Status: Production ready · License: MIT

Signals

GitHub stars
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Last commit
Sep 2026
Advanced
Catalog kind
skill
Gateway key
multi-model-orchestrator
Source
github.com/majiayu000/spellbook