Community Prompt Rating And Feedback

via “community voting and quality signaling system”

Curated collection of 150+ ChatGPT prompt templates.

Unique: Stores individual vote records per user-prompt pair rather than just aggregating counts, enabling personalized 'liked' collections, vote reversal, and detailed analytics on voting patterns. Integrates vote counts into search ranking and discovery feeds, making community quality signals visible throughout the platform.

vs others: More transparent and community-driven than algorithmic ranking because users can see vote counts and understand why a prompt is recommended, while still enabling algorithmic trending based on vote velocity for discovering emerging high-quality prompts.

via “asset rating and feedback system”

Discover and download a variety of assets including prompts, skills, and connectors from the Spark marketplace. Access detailed documentation, ratings, and raw content to quickly integrate pre-built components into your projects. Filter by domain and popularity to find the most relevant solutions fo

Unique: Integrates user feedback directly into the asset discovery process, which is often absent in other marketplaces that do not prioritize community input.

vs others: More transparent and community-oriented than traditional repositories that lack user interaction features.

via “user feedback and community engagement system”

🚀💪Maximize your efficiency and productivity. The ultimate hub to manage, customize, and share prompts. (English/中文/Español/العربية). 让生产力加倍的 AI 快捷指令。更高效地管理提示词，在分享社区中发现适用于不同场景的灵感。

Unique: Integrates feedback and comments directly into the Docusaurus site through React components, enabling community discussion without requiring a separate forum or comment platform. Likely leverages GitHub Issues as the backend, maintaining consistency with the GitHub-first architecture.

vs others: More integrated than external comment systems like Disqus because feedback flows directly into the development workflow via GitHub Issues, reducing context switching for maintainers.

via “community-contributed-prompt-aggregation”

Curated list of chatgpt prompts from the top-rated GPTs in the GPTs Store. Prompt Engineering, prompt attack & prompt protect. Advanced Prompt Engineering papers.

Unique: Implements a GitHub-based collaborative model where community prompts are version-controlled, attributed to contributors, and discoverable alongside official GPT Store prompts, treating prompt engineering as a collaborative software development practice rather than a static knowledge base.

vs others: Enables community iteration and attribution in ways that centralized prompt marketplaces (PromptBase, OpenAI's own prompt sharing) do not, by leveraging git history and pull request workflows for transparency and collaborative improvement.

via “rating system for problems”

Search solved.ac problems by difficulty, tags, and keywords to find the right challenges. Check user ratings, tiers, and solved counts to track progress. Convert natural language into precise filters for faster discovery.

Unique: Utilizes a community-driven approach to problem ratings, enhancing the quality of challenges available to users.

vs others: More reliable than single-user ratings as it aggregates multiple perspectives for a balanced view.

via “community voting and reputation system with leaderboards”

A collection of prompt examples to be used with the ChatGPT model.

via “prompt-usage-analytics-and-insights”

Discover, create and share powerful prompts

via “community-driven prompt feedback”

Guide and resources for prompt engineering.

Unique: The guide's focus on community-driven feedback sets it apart from other resources that do not facilitate user interaction or collaboration.

vs others: More interactive and community-focused than traditional prompt engineering resources that lack engagement features.

via “community-prompt-contribution”

A collection of free prompts for Stable Diffusion.

Unique: Implements a crowdsourced prompt library model where the community directly expands the collection, rather than relying on a centralized team or algorithmic generation. This creates a network effect where more users contribute, making the library more valuable.

vs others: More scalable and diverse than curated-only libraries, but requires moderation overhead and may suffer from quality variance compared to professionally-curated prompt collections

via “prompt categorization and tagging”

Search prompts for models like Stable Diffusion, ChatGPT, Midjourney, etc.

Unique: The user-driven tagging system encourages community involvement, creating a dynamic and evolving prompt library that adapts to user needs.

vs others: More collaborative than static prompt libraries, fostering a community-driven approach to prompt discovery.

via “prompt quality scoring and diagnostic feedback”

Tool for prompt engineering.

via “community-driven prompt feedback system”

Search prompts from top prompt engineers. Sell your own prompts.

Unique: Incorporates a structured feedback mechanism that directly influences prompt visibility and sales, unlike many static platforms without user interaction.

vs others: More interactive and responsive to user needs compared to traditional prompt repositories that lack real-time feedback.

via “character-rating-and-community-feedback”

Character.AI lets you create characters and chat to them.

via “prompt curation and community sharing”

Search 10M+ of prompts, and generate AI art via Stable Diffusion, DALL·E 2.

via “prompt-and-bot-sharing-and-discovery”

Search for prompts and bots, then use them with your favorite AI. All in one place.

via “prompt evaluation feedback”

A free, open source course on communicating with artificial intelligence.

Unique: Incorporates a heuristic scoring system for prompt evaluation, providing structured feedback that is often lacking in other educational resources.

vs others: Offers a more systematic approach to prompt feedback compared to generic peer reviews or unstructured feedback.

via “community-prompt-rating-and-feedback”

via “prompt-quality-rating-and-feedback”

Unique: Implements a community rating system to surface high-quality prompts and filter low-performing templates. Likely uses simple star ratings and text reviews rather than structured quality metrics or A/B testing data.

vs others: Provides social proof for prompt selection, but lacks the rigor of A/B testing or systematic quality evaluation used by specialized prompt optimization platforms

via “prompt-rating-and-feedback”

via “community-driven prompt quality validation”

Unique: Combines visual preview outputs with community ratings to create a transparent quality signal, whereas most prompt repositories rely on keyword search or creator reputation alone without showing actual generated results

vs others: More transparent than closed prompt libraries (OpenAI's official prompts), but less rigorous than expert-curated collections because validation relies on community feedback rather than technical review