Agents
Manage Liongard agents with bulk operations and installer generation.
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Manage Liongard agents with bulk operations and installer generation.
- `npm run dev` - Build in development mode with watch
This document collects ideas and instructions for implementing future improvements. Follow these when adding features or refactoring the code.
CLI forensic tool for Telegram Desktop artifact analysis. Extracts and analyzes data from `tdata` directory.
Learn how to interact with Mastra AI agents, including generating responses, streaming interactions, and managing agent tools using the client-js SDK.
generic skill
This file contains essential information for agentic coding assistants working in this repository.
generic skill
TODO: Add service description.
- `app/` — Next.js App Router routes, layouts, and API handlers (`app/api/**`).
- **Indentation**: 4 spaces
- [Remix](https://remix.run)
These instructions define how GitHub Copilot should assist with this Go project. The goal is to ensure consistent, high-quality code generation aligned with Go idioms, the chosen architecture, and our team's best practices.
- `src/pages/` 负责声明 Astro 路由,只保留轻量页面逻辑并组合 `layouts/` 与 `components/`。
This repository contains `mnvkd`, a C server-authoring toolkit built around a virtual kernel with coroutine, actor, service and application frameworks.
This document outlines key information needed by coding agents to work in this repository. It outlines the rules to follow during work, and provides helpful commands and tips to facilitate development.
`docker compose up` to run the docker container
- `pages/` drives Nuxt 4 routing, while shared UI lives in `components/`; drop reusable logic in `libs/` and server handlers under `server/api/`.
This project generates structured ground truth data for validating calculations used in machine learning framework by using PyTorch for executing and the gradienttracer framework. The data is stored in GGUF format for use in neural network testing and validation.
We are a team of Pokémon trainers utilizing PokeAPI (https://pokeapi.co/) as the primary source
This file defines agents and their respective roles for the `scjson` project. Each agent is responsible for a specific transformation, validation, or extraction task.
`naeural_core/` houses the runtime: `main/` orchestrates startup, `business/` contains pipeline plugins and the testing harness, `comm/` handles transports, and `serving/` wraps model execution. Runtime artifacts land in `_local_cache/`, created on demand. Optional packages live under `extensions/`,
LoRA Prep is a macOS-first toolkit that prepares LoRA training images. It ships both a SwiftPM CLI executable (`LoRAPrep`) and a SwiftUI desktop app; both surfaces share the same Vision/Core Image pipeline and should remain feature-parity replacements for the legacy `loraPrep.sh` script (which now s
- `cmd/`: Cobra-based CLI commands (`build`, `serve`, `init`, `freeze`, `test`, etc.).