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    <title>prompt-engineering</title>
    <link rel="self" type="application/atom+xml" href="https://links.biapy.com/guest/tags/29/feed"/>
    <updated>2026-08-02T10:50:26+00:00</updated>
    <id>https://links.biapy.com/guest/tags/29/feed</id>
            <entry>
            <id>https://links.biapy.com/links/11243</id>
            <title type="text"><![CDATA[Repo Prompt]]></title>
            <link rel="alternate" href="https://repoprompt.com/" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/11243"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[Iterate on code with powerful AI.
Your AI Coding Swiss Army Knife.

Related contents:

- [Episode \#102: Try harder. Ultrathink! @ Changelog &amp;amp; Friends](https://changelog.com/friends/102).]]>
            </summary>
            <updated>2025-12-16T07:33:24+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/11120</id>
            <title type="text"><![CDATA[Dotprompt]]></title>
            <link rel="alternate" href="https://google.github.io/dotprompt/" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/11120"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[Executable GenAI Prompt Templates.

Dotprompt is an executable prompt template file format for Generative AI. It is designed to be agnostic to programming language and model provider to allow for maximum flexibility in usage. Dotprompt extends the popular Handlebars templating language with GenAI-specific features.

- [Dotprompt @ GitHub](https://github.com/google/dotprompt).
- [runprompt @ GitHub](https://github.com/chr15m/runprompt).]]>
            </summary>
            <updated>2025-11-28T12:45:11+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/10636</id>
            <title type="text"><![CDATA[Anthropic&amp;#039;s Prompt Engineering Interactive Tutorial]]></title>
            <link rel="alternate" href="https://github.com/anthropics/prompt-eng-interactive-tutorial" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/10636"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[This course is intended to provide you with a comprehensive step-by-step understanding of how to engineer optimal prompts within Claude.]]>
            </summary>
            <updated>2025-10-13T11:43:16+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/10602</id>
            <title type="text"><![CDATA[Fabric]]></title>
            <link rel="alternate" href="https://github.com/danielmiessler/fabric" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/10602"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[Fabric is an open-source framework for augmenting humans using AI. It provides a modular system for solving specific problems using a crowdsourced set of AI prompts that can be used anywhere.]]>
            </summary>
            <updated>2025-10-10T09:51:59+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/10551</id>
            <title type="text"><![CDATA[OpenAI Academy]]></title>
            <link rel="alternate" href="https://academy.openai.com/" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/10551"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[Unlock the opportunities of the AI era by equipping yourself with the knowledge and skills to harness artificial intelligence effectively.

- [Prompt Packs @ OpenAI Academy](https://academy.openai.com/public/tags/prompt-packs-6849a0f98c613939acef841c).

Related contents:

- [Des packs de prompts gratuits pour vos IA @ Korben :fr:](https://korben.info/openai-academy-prompt-packs-bibliotheque-gratuite.html).]]>
            </summary>
            <updated>2025-10-06T09:38:28+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/10288</id>
            <title type="text"><![CDATA[System Prompts Leaks]]></title>
            <link rel="alternate" href="https://github.com/asgeirtj/system_prompts_leaks" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/10288"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[Collection of extracted System Prompts from popular chatbots like ChatGPT, Claude &amp;amp; Gemini]]>
            </summary>
            <updated>2025-09-19T05:56:30+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/7</id>
            <title type="text"><![CDATA[AGENTS.md]]></title>
            <link rel="alternate" href="https://agents.md/" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/7"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[A simple, open format for guiding coding agents,
used by over 20k open-source projects.

Think of AGENTS.md as a README for agents: a dedicated, predictable place to provide the context and instructions to help AI coding agents work on your project.

- [AGENTS.md @ GitHub](https://github.com/openai/agents.md).

Related contents:

- [Improve your AI code output with AGENTS.md (+ my best tips) @ builder.io](https://www.builder.io/blog/agents-md).
- [\#118 - Les news sur le développement web et l&amp;#039;IA pour septembre 2025 RC1 @ Double Slash :fr:](https://double-slash.dev/podcasts/sept25-rc1/).
- [Optimizing repos for AI @ Tom Bedor&amp;#039;s Blog](https://tombedor.dev/optimizing-repos-for-ai/).
- [How to write a great agents.md: Lessons from over 2,500 repositories @ GitHub Blog](https://github.blog/ai-and-ml/github-copilot/how-to-write-a-great-agents-md-lessons-from-over-2500-repositories/).
- [Writing a good CLAUDE.md @ humanlayer](https://www.humanlayer.dev/blog/writing-a-good-claude-md).
- [Streamlining my user-level CLAUDE.md @ chris dzombak](https://www.dzombak.com/blog/2025/12/streamlining-my-user-level-claude-md/).
- [The Complete Guide to CLAUDE.md @ builder.io](https://www.builder.io/blog/claude-md-guide).
- [How to build self-improving coding agents - Part 1 @ Eric J Ma&amp;#039;s Website](https://ericmjl.github.io/blog/2026/1/17/how-to-build-self-improving-coding-agents-part-1/).
- [AGENTS.md outperforms skills in our agent evals @ Vercel](https://vercel.com/blog/agents-md-outperforms-skills-in-our-agent-evals).
- [Evaluating AGENTS.md: Are Repository-Level Context Files Helpful for Coding Agents? @ arXiv](https://arxiv.org/abs/2602.11988).
- [Knowledge Priming @ martinFowler.com](https://martinfowler.com/articles/reduce-friction-ai/knowledge-priming.html).
- [J&amp;#039;ai mis deux IA en code review l&amp;#039;une contre l&amp;#039;autre — voici ce que ça donne @ Maxence Maireaux :fr:](https://maxence.maireaux.fr/fr/blog/mon-workflow-ia-claude-code-codex/).
- [Filesystems are having a moment @ madalitso.me](https://madalitso.me/notes/why-everyone-is-talking-about-filesystems/).
- [Your Docs Directory Is Doomed @ Jim Yagmin&amp;#039;s Blog](https://yagmin.com/blog/your-docs-directory-is-doomed/).
- [Stop Wasting Hours Writing Unit Tests: Use GitHub Copilot to Explode Code Coverage Fast @ Build5Nines](https://build5nines.com/stop-wasting-hours-writing-unit-tests-use-github-copilot-to-explode-code-coverage-fast/).]]>
            </summary>
            <updated>2026-06-04T07:03:14+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/128</id>
            <title type="text"><![CDATA[POML (Prompt Orchestration Markup Language)]]></title>
            <link rel="alternate" href="https://microsoft.github.io/poml/latest/" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/128"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[POML (Prompt Orchestration Markup Language) is a novel markup language designed to bring structure, maintainability, and versatility to advanced prompt engineering for Large Language Models (LLMs). It addresses common challenges in prompt development, such as lack of structure, complex data integration, format sensitivity, and inadequate tooling. POML provides a systematic way to organize prompt components, integrate diverse data types seamlessly, and manage presentation variations, empowering developers to create more sophisticated and reliable LLM applications.

- [POML (Prompt Orchestration Markup Language) @ GitHub](https://github.com/microsoft/poml).]]>
            </summary>
            <updated>2025-10-16T09:05:41+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/307</id>
            <title type="text"><![CDATA[Agents.md]]></title>
            <link rel="alternate" href="https://agentsmd.net/" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/307"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[Agents.md Guide for OpenAI Codex

Learn how to use Agents.md files to enhance OpenAI Codex and other AI agents in navigating your codebases, running tests, and adhering to your project&amp;#039;s standard practices.

Related contents:

- [Docs for AI agents @ https://technicalwriting.dev](https://technicalwriting.dev/ai/agents/).]]>
            </summary>
            <updated>2025-12-31T14:22:35+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/388</id>
            <title type="text"><![CDATA[LangFast - Prompt Playground]]></title>
            <link rel="alternate" href="https://langfa.st/" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/388"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[A simple prompt playground to test and share your prompt templates.

A tool for testing, debugging, and refining AI prompts. Supports variables, templates to improve prompt quality and speed up development.]]>
            </summary>
            <updated>2026-01-20T15:32:24+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/510</id>
            <title type="text"><![CDATA[Anthropic Cookbook]]></title>
            <link rel="alternate" href="https://github.com/anthropics/anthropic-cookbook" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/510"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[A collection of notebooks/recipes showcasing some fun and effective ways of using Claude.

The Anthropic Cookbook provides code and guides designed to help developers build with Claude, offering copy-able code snippets that you can easily integrate into your own projects.

Related contents:

- [Anthropic Cookbook - Claude devient encore plus accessible aux devs @ Korben :fr:](https://korben.info/anthropic-cookbook-claude-accessible-developpeurs.html).]]>
            </summary>
            <updated>2025-08-28T17:22:56+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/790</id>
            <title type="text"><![CDATA[CoRT (Chain of Recursive Thoughts) 🧠🔄]]></title>
            <link rel="alternate" href="https://github.com/PhialsBasement/Chain-of-Recursive-Thoughts" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/790"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[I made my AI think harder by making it argue with itself repeatedly. It works stupidly well. 

CoRT makes AI models recursively think about their responses, generate alternatives, and pick the best one. It&amp;#039;s like giving the AI the ability to doubt itself and try again... and again... and again.]]>
            </summary>
            <updated>2025-08-28T18:10:22+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/908</id>
            <title type="text"><![CDATA[Awesome GPT-4o Images ✨]]></title>
            <link rel="alternate" href="https://github.com/jamez-bondos/awesome-gpt4o-images" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/908"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[Awesome curated collection of GPT-4o images &amp;amp; prompts. Explore diverse AI-generated art styles (Ghibli, 3D, etc.) from OpenAI&amp;#039;s latest model.]]>
            </summary>
            <updated>2025-08-28T18:30:32+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/954</id>
            <title type="text"><![CDATA[awesome-ai-system-prompts]]></title>
            <link rel="alternate" href="https://github.com/dontriskit/awesome-ai-system-prompts" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/954"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[Crafting Effective Prompts for Agentic AI Systems: Patterns and Practices.

 🧠 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.]]>
            </summary>
            <updated>2025-08-28T18:36:38+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/1729</id>
            <title type="text"><![CDATA[Langfuse]]></title>
            <link rel="alternate" href="https://langfuse.com/" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/1729"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[Open Source LLM Engineering Platform.
Traces, evals, prompt management and metrics to debug and improve your LLM application.

🪢 Open source LLM engineering platform: LLM Observability, metrics, evals, prompt management, playground, datasets. Integrates with LlamaIndex, Langchain, OpenAI SDK, LiteLLM, and more. 🍊YC W23 

- [Langfuse @ GitHub](https://github.com/langfuse/langfuse).

Related contents:

- [Self-hosting Langfuse with Kubernetes @ Xebia](https://xebia.com/blog/setting-up-local-langfuse-server/).]]>
            </summary>
            <updated>2025-08-28T20:43:58+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/1730</id>
            <title type="text"><![CDATA[Agenta]]></title>
            <link rel="alternate" href="https://agenta.ai/" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/1730"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[Prompt Engineering, Evaluation, and Observability for LLM apps.

Your End-to-End Collaborative Open Source End-to-End LLM Engineering Platform.
Agenta provides integrated tools for prompt engineering, versioning, evaluation, and observability—all in one place.

The open-source LLMOps platform: prompt playground, prompt management, LLM evaluation, and LLM Observability all in one place. 

- [Agenta @ GitHub](https://github.com/agenta-ai/agenta).]]>
            </summary>
            <updated>2025-08-28T20:44:44+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/1732</id>
            <title type="text"><![CDATA[PromptPal]]></title>
            <link rel="alternate" href="https://promptpal.github.io/" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/1732"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[A Prompt Manager that focuses on On-Premise and developer experience.

- [PromptPal @ GitHub](https://github.com/PromptPal/PromptPal).]]>
            </summary>
            <updated>2025-08-28T20:44:45+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/2034</id>
            <title type="text"><![CDATA[code2prompt]]></title>
            <link rel="alternate" href="https://github.com/mufeedvh/code2prompt" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/2034"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[A CLI tool to convert your codebase into a single LLM prompt with source tree, prompt templating, and token counting.]]>
            </summary>
            <updated>2025-08-28T21:36:17+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/2594</id>
            <title type="text"><![CDATA[Promptim]]></title>
            <link rel="alternate" href="https://github.com/hinthornw/promptimizer" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/2594"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[Prompt optimization scratch.
Promptim is an experimental prompt optimization library to help you systematically improve your AI systems.

Promptim automates the process of improving prompts on specific tasks. You provide initial prompt, a dataset, and custom evaluators (and optional human feedback), and promptim runs an optimization loop to produce a refined prompt that aims to outperform the original.

Related contents:

- [Promptim: an experimental library for prompt optimization @ LangChain](https://blog.langchain.dev/promptim/).
- [Promptimizer - Optimisez vos prompts IA automatiquement @ Korben :fr:](https://korben.info/promptimizer-optimisation-automatique-prompts-ia.html).]]>
            </summary>
            <updated>2025-08-28T23:09:09+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/2887</id>
            <title type="text"><![CDATA[LLM Prompt Tuning Playbook]]></title>
            <link rel="alternate" href="https://github.com/varungodbole/prompt-tuning-playbook" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/2887"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[A playbook for effectively prompting post-trained LLMs.

This document is for anyone who would like to get better at prompting post-trained LLMs. We assume that readers have had some basic interactions with some sort of LLM (e.g. Gemini), but we do not assume a rigorous technical understanding.]]>
            </summary>
            <updated>2025-08-28T23:57:37+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/3455</id>
            <title type="text"><![CDATA[Priompt]]></title>
            <link rel="alternate" href="https://github.com/anysphere/priompt" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/3455"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[Prompt design using JSX.

Priompt (priority + prompt) is a JSX-based prompting library. It uses priorities to decide what to include in the context window.

Priompt is an attempt at a prompt design library, inspired by web design libraries like React.

- [Prompt Design @ Cursor](https://www.cursor.com/blog/prompt-design).]]>
            </summary>
            <updated>2025-08-29T01:33:05+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/3462</id>
            <title type="text"><![CDATA[Prompt Engineering Guide]]></title>
            <link rel="alternate" href="https://www.promptingguide.ai/" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/3462"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[🐙 Guides, papers, lecture, notebooks and resources for prompt engineering.

Prompt engineering is a relatively new discipline for developing and optimizing prompts to efficiently use language models (LMs) for a wide variety of applications and research topics. Prompt engineering skills help to better understand the capabilities and limitations of large language models (LLMs).

- [Prompt Engineering Guide @ GitHub](https://github.com/dair-ai/Prompt-Engineering-Guide).
- [AI tools for software engineers, but without the hype – with Simon Willison (co-creator of Django) @ The Pragmatic Engineer](https://newsletter.pragmaticengineer.com/p/ai-tools-for-software-engineers-simon-willison).]]>
            </summary>
            <updated>2025-08-29T01:33:10+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/3467</id>
            <title type="text"><![CDATA[BAML]]></title>
            <link rel="alternate" href="https://docs.boundaryml.com/" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/3467"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[BAML is an expressive language for structured text generation.
BAML is a domain-specific language to write and test LLM functions.

In BAML, prompts are treated like functions. An LLM function is a prompt template with some defined input variables, and a specific output type like a class, enum, union, optional string, etc.

With BAML you can write and test a complex LLM function in 1/10 of the time it takes to setup a python LLM testing environment.

- [BAML @ GitHub](https://github.com/boundaryml/baml).]]>
            </summary>
            <updated>2025-08-29T01:34:06+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/4922</id>
            <title type="text"><![CDATA[FlowGPT]]></title>
            <link rel="alternate" href="https://flowgpt.com/" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/4922"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[Best ChatGPT Prompts &amp;amp; AI Prompts Community]]>
            </summary>
            <updated>2025-08-29T05:37:09+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/4992</id>
            <title type="text"><![CDATA[promptmap]]></title>
            <link rel="alternate" href="https://github.com/utkusen/promptmap" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/4992"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[automatically tests prompt injection attacks on ChatGPT instances.

Prompt injection is a type of security vulnerability that can be exploited to control the behavior of a ChatGPT instance. By injecting malicious prompts into the system, an attacker can force the ChatGPT instance to do unintended actions.]]>
            </summary>
            <updated>2025-08-29T05:49:15+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/5085</id>
            <title type="text"><![CDATA[Learn Prompting]]></title>
            <link rel="alternate" href="https://learnprompting.org/" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/5085"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[Your Guide to Communicating with Artificial Intelligence.

Learn how to use ChatGPT and other AI tools to accomplish your goals using our free and open source curriculum, designed for all skill levels!

[Learn Prompting @ GitHub](https://github.com/trigaten/Learn_Prompting).]]>
            </summary>
            <updated>2025-08-29T06:04:24+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/6542</id>
            <title type="text"><![CDATA[PromptHero]]></title>
            <link rel="alternate" href="https://prompthero.com/?ref=CtrlAltCC" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/6542"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[Search prompts for Stable Diffusion, DALL-E &amp;amp; Midjourney.
Search millions of art images by AI models like DALL-E, Stable Diffusion, Midjourney...]]>
            </summary>
            <updated>2025-08-29T10:07:33+00:00</updated>
        </entry>
    </feed>
