Coding
PromptBeginner5 minmarkdown
planz
Manage hierarchical project plans in SQLite. Tree-based structure with phases and tasks. Multiple output formats (text, JSON, XML, markdown).
0
Explore
Find agent skills by outcome
5,281 skills indexed with the new KISS metadata standard.
Showing 24 of 5,281Categories: Research, Coding, Creative, Data
Coding
PromptBeginner5 minmarkdown
AGENTS.md
This document defines **strict behavioral, architectural, and coding constraints** for OpenAI Codex when contributing to this repository.
0
Coding
PromptBeginner5 minmarkdown
**Overview**
This repo’s core is a TypeScript DSL that transpiles directly into executable, type‑safe RxJS code. Agents will ultimately generate DSL programs and orchestrate sub‑agents, but today the DSL → transpilation → generated code pipeline is the mature foundation.
0
Coding
PromptBeginner5 minmarkdown
Ultracite Code Standards
This project uses **Ultracite**, a zero-config Biome preset that enforces strict code quality standards through automated formatting and linting.
0
Coding
PromptBeginner5 minmarkdown
CLAUDE.md
This file provides guidance to Claude Code (claude.ai/code) when working with code in this repository.
0
Coding
PromptBeginner5 minmarkdown
AGENTS.md (repo root)
本ファイルはリポジトリ全体に適用される**共通ルール**を定義します。
0
Coding
PromptBeginner5 minmarkdown
CLAUDE.md
This file provides guidance to Claude Code (claude.ai/code) when working with code in this repository.
0
Coding
PromptBeginner5 minmarkdown
Tool contracts for agents: schema versioning beats prompt tweaks
generic skill
0
Coding
PromptBeginner5 minmarkdown
Summary: AGENTS.md
Agent development guide providing build commands, code style guidelines, and development workflow instructions for the Terraphim AI project.
0
Coding
PromptBeginner5 minmarkdown
Agents
This project uses lightweight, role-based agent guidance to keep work focused and consistent.
0
Coding
PromptBeginner5 minmarkdown
Remix Component - Agent Guide
This guide provides a comprehensive overview of the Remix Component API, its runtime behavior, and practical use cases for building interactive UIs.
0
Coding
PromptBeginner5 minmarkdown
AGENTS.md
This file provides guidance to LLM agent when working with code in this repository.
0
Coding
PromptBeginner5 minmarkdown
Agents
This project uses lightweight, role-based agent guidance to keep work focused and consistent.
0
Coding
PromptBeginner5 minmarkdown
AGENTS.md
owLSM is a project for protecting linux machines.
0
Coding
PromptBeginner5 minmarkdown
Repository Guidelines
All TypeScript sources live in `src/` (advanced/basic/Claude/SSE/bridge servers plus shared helpers) and compile into `dist/`. Browser assets and dashboards belong in `web/` and `extension/`, while OS-native glue code is grouped under `macos/`, `windows/`, and `native/`. Automation scripts, version
0
Coding
PromptBeginner5 minmarkdown
Agent Instructions
* Responses may be in **Russian** or **English**, as appropriate.
0
Coding
PromptBeginner5 minmarkdown
Guidance for Codex Contributors
This repository contains a Next.js 15 application written in TypeScript with Tailwind CSS and shadcn/ui components. The
0
Coding
PromptBeginner5 minmarkdown
AGENTS.md - Open Sunsama
AI-agent-friendly task management + time blocking app. TypeScript monorepo with Bun, Turborepo, PostgreSQL, Drizzle ORM.
0
Data
PromptBeginner5 minmarkdown
Adding Airports
When adding airports that are NOT in `aerolineas-airports.json`:
0
Coding
PromptBeginner5 minmarkdown
Code Style Guidelines
Focus on code style during code review. Make the code style comments priority P2,
0
Coding
PromptBeginner5 minmarkdown
AGENTS.md
This file is for **AI coding agents**.
0
Coding
PromptBeginner5 minmarkdown
Agent Instructions for mq
Instructions for AI coding agents contributing to this repository.
0
Coding
PromptBeginner5 minmarkdown
Dojo.js Agent Guide
- Primary package manager: install deps via `bun install`.
0
Coding
PromptBeginner5 minmarkdown
Hooplytics — AI Agent Guide
Hooplytics is an AI-powered NBA assistant that combines **Google Gemini 2.5 Flash** (LLM), **Model Context Protocol** (MCP) for real-time NBA data, and a **PyTorch neural network** (96.2% accuracy) for player performance tier classification. Users ask basketball questions via a React chat UI, and th
0