fw-agent-skill

Orchestrate multi-agent coding workflows with durable GBrain context.

3|Updated Apr 24, 2026
One-click install
npx skills add https://github.com/fellwork/aihu --skill fw-agent-skill
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: fw-agent-skill
Source: https://github.com/fellwork/aihu/tree/main/.claude/skills/fw-agent-skill
Command: npx skills add https://github.com/fellwork/aihu --skill fw-agent-skill

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes references (resource) components.

What problem does it solve?

It solves the problem of getting Claude Code to reliably decompose and coordinate complex coding work across multiple specialized subagents, while maintaining durable context and preventing common orchestration failures.

Core Features & Use Cases

  • Multi-agent team orchestration as Team Lead across roles like Topic Director, Architect, Builder, Verifier, Investigator, Synthesizer, and Historian.
  • Mode-driven workflows for experiment loops, build/refactor arcs, and defect-fix loops with explicit iteration discipline.
  • Durable storage and retrieval via GBrain (Supabase + pgvector) to manage layered context (base/user/delta/local) and promotion discipline for earned findings.
  • Operational guardrails to prevent substance/orchestration conflation, unverified “PASS” claims, wrong-direction stalls, and Iron Law violations (investigate before fixing).

Quick Start

Use the fw-agent-skill when you want to run a multi-round build, refactor, or investigate-then-fix session in Claude Code as Team Lead with GBrain-backed durable context.

Frequently Asked Questions about fw-agent-skill

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

FAQPage Schema
How do I orchestrate multi-agent coding workflows in Claude Code?

Multi-agent coding workflows in Claude Code are orchestrated by a Team Lead role that dispatches specialized subagents for research, validation, and promotion steps across multiple rounds. This approach ensures strict separation between orchestration and substance execution.

How does durable context storage work for multi-agent code generation?

Durable context storage for multi-agent code generation uses Supabase and pgvector to manage layered context across base, user, delta, and local layers. This allows subagents to retrieve and promote earned findings throughout the build or refactor session.

What is the best way to structure investigate-then-fix defect loops with subagents?

Investigate-then-fix defect loops require an Iron Law discipline where agents must investigate root causes before attempting fixes. The Team Lead orchestrates specialized roles like Investigator and Verifier to execute mode-specific research and validation across iterations.

Does this multi-agent orchestration approach work with Supabase and pgvector?

Yes, this orchestration approach uses Supabase and pgvector as the GBrain backend to store and retrieve durable context. This integration supports layered context management and promotion discipline for earned findings during complex build sessions.

How do I prevent unverified PASS claims and orchestration failures during multi-agent builds?

To prevent unverified PASS claims and orchestration failures, apply operational guardrails that enforce verification discipline and strict separation of orchestration versus substance. The Team Lead must ensure subagents validate results before promoting any findings.

When do I need mode-driven workflows for multi-agent code refactoring?

Mode-driven workflows are needed for complex build and refactor arcs, experiment loops, and defect-fix loops. They provide explicit iteration discipline by matching operating modes to specific roles like Architect, Builder, and Verifier.