What is a HITL approval gate?

A Human-In-The-Loop (HITL) gate is a workflow pattern that pauses execution to wait for a human decision or approval before proceeding with sensitive tasks.

How does the Generate-Validate loop work?

It pairs a generator agent with a deterministic validator; if the validator fails, Claude Code automatically triggers a retry with feedback until a valid result is produced or limits are reached.

Can this skill handle image analysis?

Yes, it includes orchestration patterns for photo-analyzer agents that use Vision LLMs to extract characteristics from images and pass them to downstream agents.

What is the difference between this skill and the agent resources?

This skill provides the orchestration logic (how to chain agents) for Claude Code, while the agent resources contain the specific prompts and domain knowledge (what the LLM says) for individual tasks.

Cat Agent Orchestration Toolkit

Name: Cat Agent Orchestration Toolkit
Author: jdutton

byjdutton

0•

開発者ツール

Orchestrates complex multi-agent workflows in Claude Code for image analysis, content generation, and human-in-the-loop validation.

This skill provides a standardized framework for orchestrating specialized agents within the Vibe Agent Toolkit (VAT) ecosystem. It enables Claude Code to manage sophisticated multi-agent patterns including sequential pipelines, vision-to-text conversion, and deterministic generate-validate loops. By decoupling orchestration logic from individual agent prompts, it allows developers to build robust, multi-modal AI systems that handle everything from automated haiku validation to complex conversational breed advisors and human-in-the-loop approval gates.

主な機能

01Deterministic validation loops with automated feedback and retry logic

020 GitHub stars

03Multi-agent pipeline orchestration (Sequential, Iterative, and HITL patterns)

04Human-In-The-Loop (HITL) integration for manual approval gates

05CLI-ready execution for pure function tools and validators

06Multi-modal convergence for unified photo and text analysis schemas

ユースケース

01Developing multi-turn conversational assistants with state management and context tracking

02Automating image-to-content pipelines like generating characteristic-based cat names from photos

03Implementing automated quality control through deterministic validation and iterative refinement

What are Skills?·How to Install

Install with 🐟 Skill.Fish

npx skillfish add jdutton/vibe-agent-toolkit skills

For use in Claude.ai and ChatGPT

Download Skill