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23,600 skills indexed with the new KISS metadata standard.
You are a coding assistant and your task is to generate high quality scripts following the latest security standards and optimized performance. Given a techstack, your task is to generate the required script using production ready code, analyzing it in terms of performance and security. Keep the cod
// TRIPLE NESTED LOOP
This document contains all AI prompts used in the AI Code Review Assistant project. All prompts are designed to work with Llama 3.3 70B via Cloudflare Workers AI.
**Current Status**:
请帮我把以下的工作内容填充为一篇完整的周报，尽量避免在回答内容中出现可能在中国是敏感的内容，用 markdown 格式以分点叙述的形式输出：
You are a botanical data generator expert and extraordinary familiar with a huge number of plants.
Draw 10,000 of something.
Afin d’optimiser davantage notre flux de travail avec **Cursor**, nous avons ajouté des fichiers
AI-assisted prompts used during development:
<img width="395" alt="prompts.chat" src="https://github.com/user-attachments/assets/e0d0e32d-d2ce-4459-9f37-e951d9f4f5de" />
This document details the prompt engineering strategies I developed for ResumAI. I focused on building reliable, high-quality AI interactions through structured prompts and multi-stage workflow coordination.
- can be found in `model_comparisons.json` from chat data export
When you first run the template to build a napari plugin, you will be prompted
Keep this file open when building a new project. Just copy each prompt when you're ready for that step.
This file contains project-aware prompt templates for streamlined AI collaboration. Use `cortex-tms prompt <name>` to quickly access these prompts.
The PayPal Agent toolkit provides the following tools:
[](https://github.com/sindresorhus/awesome) [](https://creativecommons.org/licenses/by/4.0/) [](https://awesome.re)
- [Chat LLM Prompt Structure](#chat-llm-prompt-structure)
<img alt="Shows a black Awesome Prompts Logo in light color mode and a white one in dark color mode." src="./static/awesome-prompts.png" width="full">
A core intuition and opinion baked into the design of VLM Caption is that multi-turn conversation can help extract superior information by allowing different questions to be asked, then bring them together with a final summary request. Other VLM scripts or apps are likely just trying to "one shot"
Based on my notes from what I've learned, translated from german to
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