cross-agent-delegation

Route engineering changes to Codex, Kimi, or Claude by complexity and risk.

705|56|Updated Dec 26, 2025
One-click install
npx skills add https://github.com/alinaqi/maggy --skill cross-agent-delegation
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: cross-agent-delegation
Source: https://github.com/alinaqi/maggy/tree/main/skills/cross-agent-delegation
Command: npx skills add https://github.com/alinaqi/maggy --skill cross-agent-delegation

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

This Skill reduces end-to-end turnaround time for engineering changes by routing work to the most effective AI tool (Codex, Kimi, or Claude) while enforcing pre-task and post-task quality gates through iCPG and Mnemos.

Core Features & Use Cases

  • Tool-aware delegation with complexity scoring: Chooses between Kimi solo, Kimi + Codex auto-review, or Claude direct handling based on bounded risk dimensions (depth, fan-out, security boundary crossings, concurrency, and invariants).
  • Codex stop-hook auto-review: Runs an automatic Codex review after tests pass and feeds high-severity findings back to Claude.
  • Mandatory iCPG + Mnemos context transfer: Enforces duplicate checks, constraints, and risk queries before changes, and records drift/status after changes while transferring state across delegated agents via Mnemos checkpoints.
  • Use Case: When you ask to “review the auth middleware for timing attacks” or “push to git,” the system routes to the right model, injects the right invariants, runs TDD/test loops, and ensures recorded symbol/risk tracking across tool boundaries.

Quick Start

Tell Claude to perform your repo change (for example, “review and fix the timing attack risk in the authentication middleware”), and let it delegate to the appropriate agent(s) automatically.

Frequently Asked Questions about cross-agent-delegation

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

FAQPage Schema
How do I route coding tasks across multiple AI agents safely?

Multi-model orchestration routes engineering changes by scoring complexity and risk to select Codex, Kimi, or Claude. It applies quality gates through iCPG pre-task queries and transfers state across delegated agents via Mnemos checkpointing.

When do I need multi-model orchestration for code review?

You need multi-model orchestration when changes involve depth, fan-out, security boundary crossings, or invariants. It selects between Kimi solo, Kimi plus Codex auto-review, or Claude direct handling based on bounded risk dimensions.

How does cross-agent delegation preserve context between AI tools?

Cross-agent delegation preserves context by enforcing mandatory iCPG pre-task queries and Mnemos checkpointing. This records drift and status after changes while transferring goals, constraints, and state across tool boundaries.

Can I use Claude to delegate git push operations to another AI agent?

Yes, you can ask Claude to perform a repo change like pushing to git, and it delegates to the appropriate agent automatically. The system injects the right invariants, runs TDD test loops, and ensures recorded risk tracking across tool boundaries.

What is the best way to run an automated code review after TDD tests pass?

The best way to run automated code review after tests pass is using a Codex stop-hook auto-review mechanism. It feeds high-severity findings back to Claude to ensure multi-tool development workflows maintain quality.

Does cross-agent delegation work without setting up dependencies?

Yes, cross-agent delegation works without setting up external dependencies. It uses internal complexity scoring to choose between Kimi solo, Kimi plus Codex auto-review, or Claude direct handling based on bounded risk dimensions.