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Top AI Repos tracks AI repositories on GitHub and answers two different questions about each one: is it moving right now, and would you bet a product on it.
Top AI Repos tracks AI repositories on GitHub and answers two different questions about each one: is it moving right now, and would you bet a product on it.
🧠 Curated collection of system prompts for top AI tools. Perfect for AI agent builders and prompt engineers. Incuding: ChatGPT, Claude, Perplexity, Manus, Claude-Code, Loveable, v0, Grok, same new, windsurf, notion, and MetaAI.
| Date | Stars |
|---|---|
| 2026-07-31 | 6113 |
| 2026-08-02 | 6113 |
| 2026-08-05 | 6128 |
| 2026-08-06 | 6128 |
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# Crafting Effective Prompts for Agentic AI Systems: Patterns and Practices
## Table of Contents
* [Introduction: The Blueprint of Agentic AI](#introduction-the-blueprint-of-agentic-ai)
* [The Foundation: Core Principles of Agentic Prompts](#the-foundation-core-principles-of-agentic-prompts)
* [1. Clear Role Definition and Scope](#1-clear-role-definition-and-scope)
* [2. Structured Instructions and Organization](#2-structured-instructions-and-organization)
* [3. Explicit Tool Integration and Usage Guidelines](#3-explicit-tool-integration-and-usage-guidelines)
* [4. Step-by-Step Reasoning and Planning](#4-step-by-step-reasoning-and-planning)
* [5. Environment and Context Awareness](#5-environment-and-context-awareness)
* [6. Domain-Specific Expertise and Constraints](#6-domain-specific-expertise-and-constraints)
* [7. Safety, Alignment, and Refusal Protocols](#7-safety-alignment-and-refusal-protocols)
* [8. Consistent Tone and Interaction Style](#8-consistent-tone-and-interaction-style)
* [Case Studies: Analyzing Real-World Prompts](#case-studies-analyzing-real-world-prompts)
* [Vercel v0: UI Generation & Component Tooling](#vercel-v0-ui-generation--component-tooling)
* [same.new: Agentic Pair Programming & Strict Tooling](#samenew-agentic-pair-programming--strict-tooling)
* [Manus: General Purpose Agent & Explicit Loop](#manus-general-purpose-agent--explicit-loop)
* [OpenAI ChatGPT (GPT-4.5/4o): Integrated Tools & Policies](#openai-chatgpt-gpt-454o-integrated-tools--policies)
* [Notes on Other Systems (Cline, Bolt, Augment, Claude Code, Clawdbot)](#notes-on-other-systems-cline-bolt-augment-claude-code-clawdbot)
* [Synthesizing Best Practices: Key Takeaways for Builders](#synthesizing-best-practices-key-takeaways-for-builders)
* [Unique Conventions & Architectural Differences](#unique-conventions--architectural-differences)
* [Conclusion: Building the Agentic Future](#conclusion-building-the-agentic-future)
* [Visual AI Agent: Harpagan](https://harpagan.com)
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## Introduction: The Blueprint of Agentic AI
The rise of agentic Artificial Intelligence (AI) systems marks a significant shift from purely conversational models to AI that can actively perform tasks, interact with tools, and pursue complex goals autonomously. These systems, capable of planning, executing commands, editing files, browsing the web, and more, promise to revolutionize how we interact with technology and augment human capabilities.
At the heart of every effective agentic AI lies its **system prompt**. More than just initial instructions, the system prompt serves as the foundational blueprint, the operational manual, or even the "constitution" guiding the AI's behavior, capabilities, limitations, and persona. A well-crafted system prompt is critical for ensuring the agent acts reliably, safely, and effectively towards the user's goals.
This guide delves into the art and science of crafting these crucial prompts. By analyzing a diverse collection of real-world system prompts from the [awesome-ai-system-prompts](https://github.com/dontriskit/awesome-ai-system-prompts) repository – specifically focusing on examples from Vercel's v0, same.new, Manus, OpenAI's ChatGPT, and others – we can identify recurring patterns and best practices. For builders shaping the agentic future of 2025 and beyond, understanding these patterns is essential for creating powerful, predictable, and trustworthy AI assistants.
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## The Foundation: Core Principles of Agentic Prompts
Across different agentic systems, several core principles consistently emerge in successful system prompts. These form the foundation upon which complex agent behavior is built.
### 1. Clear Role Definition and Scope
**Why it matters:** Explicitly defining the AI's identity, core function, and operational domain anchors its behavior, sets user expectations, and helps prevent scope creep or nonsensical respExcerpt of 36,245 characters
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Andrea Pinto · @nottelabs
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Would you bet a product on this? Bounded 0–100 and slow moving.
matched fp:99b8a46a783799c5, desc:ai agent