mission-orchestrated

Orchestrates a three-agent Pathfinder, Builder, Inspector cycle for each feature task.

3|Updated Jan 14, 2026
One-click install
npx skills add https://github.com/thebrownproject/space-agents --skill mission-orchestrated
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: mission-orchestrated
Source: https://github.com/thebrownproject/space-agents/tree/main/skills/mission-orchestrated
Command: npx skills add https://github.com/thebrownproject/space-agents --skill mission-orchestrated

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

Automates end-to-end feature development by orchestrating a three-agent cycle (Pathfinder, Builder, Inspector) for each task within a feature.

Core Features & Use Cases

  • Orchestrated task execution: spawn dedicated Pathfinder, Builder, and Inspector agents per task to ensure focused exploration, implementation, and verification.
  • Deterministic workflow: manage feature lifecycle from load to close using explicit commands and status transitions.
  • Auditable progress: track task states and results via Beads-context and structured agent outputs for reproducibility.

Quick Start

Initialize a feature, activate it, and run through all tasks, spawning Pathfinder, Builder, and Inspector agents for each task.

Frequently Asked Questions about mission-orchestrated

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How does multi-agent orchestration automate feature development end-to-end?

Multi-agent orchestration automates feature development by cycling three specialized agents—Pathfinder, Builder, and Inspector—through each task, ensuring focused exploration, implementation, and verification before recording completion.

What is the three-agent cycle for orchestrated task management?

The three-agent cycle is a task management mechanism where a Pathfinder agent explores the task, a Builder agent implements it, and an Inspector agent verifies the results, creating a deterministic workflow from start to close.

How do I manage feature lifecycle states using task orchestration?

You manage feature lifecycle states by loading the feature, marking it in-progress, iterating through its tasks by spawning dedicated agents, and recording task completion to transition and ultimately close the feature.

Can I use Beads and bd for deterministic task orchestration?

Yes, this orchestration uses Beads for context management and bd for task management to implement deterministic task lifecycle commands, agent role templates, and explicit progress states for reproducible feature development.

What's the best way to track progress when orchestrating multi-agent tasks?

The best way to track progress is by using Beads-context and structured agent outputs to maintain auditable task states and results, ensuring reproducibility throughout the feature lifecycle.

When should I not use a multi-agent orchestration approach for feature development?

You should avoid multi-agent orchestration for simple, single-step modifications that do not require the deterministic Pathfinder, Builder, and Inspector cycle, as the overhead of managing task states and agent roles would outweigh the benefits.