Gino onigetoc

Set up these as real Codex lifecycle hooks by following the official documentation: https://learn.chatgpt.com/docs/hooks

Important: use ~/.codex/hooks.json and a PreToolUse command hook. Do not implement this only as a ~/.codex/rules/*.rules execution-policy file.

First inspect any existing hooks and preserve them. Then:

Create or merge ~/.codex/hooks.json with a PreToolUse matcher for Bash.
Create ~/.codex/hooks/destructive_commands.py.
The script must read the hook JSON payload from stdin and inspect tool_input.command.

generation_date: 2025-12-17 10:44 received_date: 2025-12-17 10:44 updated_date: 2025-12-24 tags:

git/track
scope/work
source/telegram
status/resource
topic/ai/claude

Opencode plugin development guide

Generated with LLM assistance on 2 Nov 2025 with minimal human verification.

Overview

Opencode plugins extend the functionality of the Opencode AI assistant by allowing you to add custom tools, authentication providers, event handlers, and hooks into the core system. This guide covers how to create, configure, and distribute plugins.

Source files:

LLM Wiki

A pattern for building personal knowledge bases using LLMs.

This is an idea file, it is designed to be copy pasted to your own LLM Agent (e.g. OpenAI Codex, Claude Code, OpenCode / Pi, or etc.). Its goal is to communicate the high level idea, but your agent will build out the specifics in collaboration with you.

The core idea

Most people's experience with LLMs and documents looks like RAG: you upload a collection of files, the LLM retrieves relevant chunks at query time, and generates an answer. This works, but the LLM is rediscovering knowledge from scratch on every question. There's no accumulation. Ask a subtle question that requires synthesizing five documents, and the LLM has to find and piece together the relevant fragments every time. Nothing is built up. NotebookLM, ChatGPT file uploads, and most RAG systems work this way.

Create a modern web application starter template using the following feature.

Tech Stack

TypeScript
Tailwind CSS
Lucide icons
shadcn/ui
next-themes
Radix UI components
React

💍 agentic.js

One Ai library to rule them all

agentic.js is a modern, secure, and scalable JavaScript/TypeScript library designed for Deno and Node.js environments.

It provides a unified interface to interact with multiple AI language model providers like OpenAI and Anthropic. Incorporating agentic capabilities through LangChain.js integration, agentic.js allows for advanced AI applications, including custom tool creation and dynamic agent architectures.

The library supports multiple models and providers using dynamic configurations and offers optional support for PostgreSQL/Supabase as a database backend for caching and data storage.

Key Features

Instructions for Gemini: Task-Oriented Workflow

You are an AI assistant expert in React, TypeScript, Python development. Your primary goal is to break down each user request into a clear action plan and execute it step by step. Every time you create a todo in relation to the user request, you must update the Update todos in Markdown in the "./.gemini\todos.md file". If this .gemini folder or todos.md file do not exist, create it. Update and show in the terminal this Todos list after every news task is to do and show where we are now in the task todos list.

Your Methodology

Analysis and Planning:
- Before anything else, analyze the user's request.

Create a detailed plan in the form of a task list in Markdown. Each task should represent a concrete and verifiable step.

	javascript: Promise.all([import('https://unpkg.com/turndown@6.0.0?module'), import('https://unpkg.com/@tehshrike/readability@0.2.0'), ]).then(async ([{
	default: Turndown
	}, {
	default: Readability
	}]) => {

	/* Optional vault name */
	const vault = "";

	/* Optional folder name such as "Clippings/" */

	<context>
	# Overview
	[Provide a high-level overview of your product here. Explain what problem it solves, who it's for, and why it's valuable.]

	# Core Features
	[List and describe the main features of your product. For each feature, include:
	- What it does
	- Why it's important
	- How it works at a high level]