Agent-Rules is a structured system for defining how AI coding agents behave within software projects. It provides a framework of rules and knowledge files that shape an agent's interpretation of tasks and its interactions with code, serving as a configuration layer for agent behavior guidelines.
Les fonctionnalités principales de steipete/agent-rules sont : Agent Behavioral Configuration, AI Coding Agent Platforms, Behavioral Guideline Configuration, Agent Instruction Formats, Static Markdown Documentation, Agent Knowledge Formats, AI Coding Assistant Rules, Markdown File Systems.
Les alternatives open-source à steipete/agent-rules incluent : agentsmd/agents.md — Agents.md is a configuration framework designed to standardize how AI coding assistants interact with a repository. It… instructa/ai-prompts — This project provides a centralized repository and configuration framework for managing system instructions,… dontriskit/awesome-ai-system-prompts — This project is a comprehensive library of structured system prompts and configuration templates designed to define… freecodexyz/free-code — Free Code is a terminal-native AI coding agent that edits files, runs shell commands, and answers questions through… affaan-m/ecc — ECC is an LLM agent orchestration framework and cross-platform AI tooling suite designed to coordinate multi-model… cloudflare/sandbox-sdk — The sandbox-sdk is a development kit designed for building secure, isolated execution environments on a global edge…
Agents.md is a configuration framework designed to standardize how AI coding assistants interact with a repository. It provides a structured format for defining project context, behavioral guidelines, and operational instructions, ensuring that AI tools maintain consistency and adhere to project-specific standards throughout the development process. The system distinguishes itself through a hierarchical configuration approach, allowing developers to define settings that inherit and override instructions across different subdirectories. By utilizing markdown-based files, it enables the injecti
This project provides a centralized repository and configuration framework for managing system instructions, behavioral constraints, and coding standards within AI-assisted development environments. It serves as a library of curated prompts and rules designed to standardize the output of autonomous coding agents, ensuring that generated code consistently adheres to project-specific architectural patterns and technical requirements. The tool distinguishes itself by employing an agent-agnostic schema that allows behavioral guidelines to be interpreted across various development platforms. It su
This project is a comprehensive library of structured system prompts and configuration templates designed to define the behavior, persona, and operational boundaries of autonomous artificial intelligence agents. It serves as a framework for prompt engineering, providing modular instructions that help models parse complex tasks, maintain consistent interaction tones, and adhere to specific domain constraints. The repository distinguishes itself by offering specialized configurations for agent safety and security, including protocols to prevent prompt injection and unauthorized data access. It
ECC is an LLM agent orchestration framework and cross-platform AI tooling suite designed to coordinate multi-model workflows. It provides a system for managing specialized agent roles, reusable skills, and structured planning to execute complex software development tasks across different AI-powered code editors. The project distinguishes itself as a Model Context Protocol manager, providing a configuration layer to integrate external servers and audit tool execution. It further implements an agentic security sandbox that restricts sensitive file access and scans for secret leakage to secure a