delegate

Delegate prompts to external LLMs like Gemini or Kimi via stdin.

Updated Mar 4, 2026
One-click install
npx skills add https://github.com/pablontiv/praxis --skill delegate-pablontiv
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: delegate
Source: https://github.com/pablontiv/praxis/tree/main/.claude/skills/delegate
Command: npx skills add https://github.com/pablontiv/praxis --skill delegate-pablontiv

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes references (resource) components.

What problem does it solve?

This Skill allows you to offload complex or lengthy tasks to other AI models like Gemini or Kimi, preserving Claude's token quota and leveraging specialized AI strengths.

Core Features & Use Cases

  • Multi-LLM Delegation: Send prompts to Gemini (for deep analysis) or Kimi (for parallel research/tool use).
  • Automated Routing: The skill intelligently chooses between Gemini and Kimi based on task characteristics.
  • Verification Mode: Use it to get a "second opinion" on Claude's work from another AI.
  • Use Case: You need a comprehensive security review of a large codebase. Delegate this to Gemini to ensure thorough analysis without consuming your Claude tokens.

Quick Start

Ask the delegate skill to use gemini to evaluate the tradeoffs of Flux CD versus ArgoCD for a small homelab Kubernetes cluster.

Frequently Asked Questions about delegate

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

FAQPage Schema
How do I delegate tasks from Claude to other LLMs like Gemini or Kimi?

You can delegate tasks to Gemini or Kimi by sending direct prompts or file-based inputs via stdin. This preserves Claude's token quota while routing tasks to external models based on their specific strengths.

Can I use another AI to verify or cross-review Claude's output?

Yes, verification mode allows you to get a second opinion on Claude's work from another AI. You can delegate the existing output to an external model to cross-review and validate the analytical results.

How does multi-LLM delegation choose between Gemini and Kimi?

Multi-LLM delegation intelligently routes tasks based on model strengths. It selects Gemini for deep analysis and Kimi for parallel research or tool usage, matching task characteristics like context window size to the appropriate model.

Does delegating large codebase security reviews to Gemini save my Claude tokens?

Yes, delegating large codebase security reviews to Gemini saves Claude tokens. The task processes entirely on the external model, leveraging its large context window for thorough analysis without consuming your local quota.

What is the best way to pass large files for multi-LLM delegation?

The best way to pass large files for multi-LLM delegation is through file-based input via stdin. This method transfers extensive data directly to the external model, avoiding manual prompt length limits and ensuring complete context delivery.

When should I not use LLM delegation for my software engineering tasks?

You should avoid LLM delegation for tasks requiring deep integration with your current local environment or when external models lack the necessary tool usage capabilities for your specific software engineering workflow.