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jingkaihe
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kodelet

Automate software engineering tasks via an AI-assisted CLI.

16|1|Updated May 6, 2025
Search Tags:#workflow#integration#cli#tooling#ai-assistant#kodelet
One-click install
npx skills add https://github.com/jingkaihe/kodelet --skill kodelet
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: kodelet
Source: https://github.com/jingkaihe/kodelet/tree/main/skills/kodelet
Command: npx skills add https://github.com/jingkaihe/kodelet --skill kodelet

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

Kodelet provides an AI-assisted command-line interface to automate software engineering and production-operations tasks, streamlining workflows and reducing manual effort.

Core Features & Use Cases

  • One-shot and ACP modes for flexible interaction with AI agents.
  • Fragments/Recipes system for reusable prompts and command templates.
  • Agentic Skills with plugin-style extensibility and subagent workflows.
  • Git integration, image input support, and multi-modal capabilities.
  • Custom tools, hooks, MCP integration, and robust conversation management.

Quick Start

Install Kodelet and start using the CLI to run tasks and manage conversations.

Frequently Asked Questions about kodelet

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

FAQPage Schema
How do I automate software engineering tasks via an AI-assisted CLI?▼

You can automate software engineering tasks via an AI-assisted CLI by running one-shot queries or interactive chats. This allows you to streamline terminal workflows and reduce manual coding effort using configurable AI agents.

Can I use reusable prompts and command templates for terminal workflows?▼

Yes, you can use reusable prompts and command templates for terminal workflows through a dedicated fragments and recipes system. This enables consistent prompt execution and standardizes repetitive command sequences across projects.

Does the AI CLI support Git integration and image inputs for coding tasks?▼

The AI CLI supports Git integration and image inputs for coding tasks through its multi-modal capabilities. This enables direct repository management and visual context processing within your terminal-based development environment.

How do I extend AI agents with custom tools, hooks, and MCP integration?▼

You extend AI agents with custom tools, hooks, and MCP integration using a plugin-style extensibility system. This enables subagent workflows and robust conversation management, allowing tailored tool integrations for complex production operations.

What is the best way to manage AI conversations in a command-line environment?▼

The best way to manage AI conversations in a command-line environment is by using an AI assistant with robust conversation management. It supports interactive chats and one-shot queries to maintain context across terminal sessions.

Do I need specific configurations to run one-shot queries and interactive chats?▼

You need to configure your terminal environment to run one-shot queries and interactive chats using the AI-assisted CLI. The system satisfies configurability requirements, allowing you to adjust settings for secure and extensible workflow execution.

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