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f / prompts.chat
f.k.a. Awesome ChatGPT Prompts. Share, discover, and collect prompts from the community. Free and open source — self-host for your organization with complete privacy.
View f/prompts.chatTrending open-source projects · updated daily
AI Prompt Engineering Projects
Prompt engineering stopped being about clever wording and became a loop: draft a prompt, run it against a set of cases, measure the result, change one variable, repeat. This board follows the tooling that loop depends on — prompt compression and pruning, automated prompt optimisation, libraries and templates, tuning methods and evaluation harnesses. It is assembled from GitHub topic pages for prompt engineering, prompt optimisation, prompt compression and prompt tuning, ranked by stars, which is why a two-week-old optimiser can outrank a template collection that has existed for years. Each card shows language, stars and forks and opens a page with description, license, activity dates, README and related prompt projects. If your goal is cutting token cost or making an agent follow instructions reliably, the sections below split the board into optimisation, libraries, tuning and structured-output tooling.
Trending Prompt Engineering Projects
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DietrichGebert / ponytail
Makes your AI agent think like the laziest senior dev in the room. The best code is the code you never wrote.
View DietrichGebert/ponytail3
microsoft / generative-ai-for-beginners
21 Lessons, Get Started Building with Generative AI
View microsoft/generative-ai-for-beginners4
JuliusBrussee / caveman
🪨 why use many token when few token do trick. Viral skill + proxy for coding agents that cuts 65% of tokens by talking like a caveman.
View JuliusBrussee/caveman5
dair-ai / Prompt-Engineering-Guide
🐙 Guides, papers, lessons, notebooks and resources for prompt engineering, context engineering, RAG, and AI Agents.
View dair-ai/Prompt-Engineering-Guide6
headroomlabs-ai / headroom
Compress tool outputs, logs, files, and RAG chunks before they reach the LLM. 20% fewer tokens for coding agents, 60-95% fewer tokens for JSON, same answers. Library, proxy, MCP server.
View headroomlabs-ai/headroom7
asgeirtj / system_prompts_leaks
Extracted system prompts from Anthropic - Claude Fable 5.1, Opus 5, Claude Design, Claude Code. OpenAI - ChatGPT GPT-6-Astra, Codex. Google - Gemini 3.8 Flash, 3.1 Pro, Antigravity.
View asgeirtj/system_prompts_leaks8
blader / humanizer
Agent skill that removes signs of AI-generated writing from text
View blader/humanizer9
elder-plinius / CL4R1T4S
LEAKED SYSTEM PROMPTS FOR CHATGPT, CLAUDE, GEMINI, GROK, PERPLEXITY, CURSOR, LOVABLE, REPLIT, AND MORE! - AI SYSTEMS TRANSPARENCY FOR ALL! 👐
View elder-plinius/CL4R1T4S10
Imbad0202 / academic-research-skills
Academic Research Skills for Claude Code: research → write → review → revise → finalize
View Imbad0202/academic-research-skills11
github / awesome-copilot
Community-contributed instructions, agents, skills, and configurations to help you make the most of GitHub Copilot.
View github/awesome-copilot12
linshenkx / prompt-optimizer
An AI prompt optimizer for writing better prompts and getting better AI results.
View linshenkx/prompt-optimizer13
langfuse / langfuse
🪢 Open source agent evals & observability: Trace, evaluate, and improve LLM applications with one open platform.
View langfuse/langfuse14
freestylefly / awesome-gpt-image-2
Prompt as Code | GPT Image 2 / 2.5 提示词与案例库，530+ 个案例、20+ 套工业级模板与可复用 Skills，新增 2.5 同提示词对比专区，附完整提示词与生成记录，持续更新。
View freestylefly/awesome-gpt-image-215
mlflow / mlflow
The open source AI engineering platform for agents, LLMs, and ML models. MLflow enables teams of all sizes to debug, evaluate, monitor
View mlflow/mlflow16
humanlayer / 12-factor-agents
What are the principles we can use to build LLM-powered software that is actually good enough to put in the hands of production customers?
View humanlayer/12-factor-agents17
alirezarezvani / claude-skills
380 Claude Code skills & agent skills & plugins (30+ Agents, 70+ custom commands, 380+ skills, customizable references, scripts)for Claude Code, Codex, Gemini CLI, Cursor
View alirezarezvani/claude-skills18
promptfoo / promptfoo
Test your prompts, agents, and RAGs. Red teaming/pentesting/vulnerability scanning for AI. Compare performance of GPT, Claude, Gemini, DeepSeek, and more.
View promptfoo/promptfoo19
comet-ml / opik
Debug, evaluate, and monitor your LLM applications, RAG systems, and agentic workflows with comprehensive tracing, automated evaluations, and production-ready dashboards.
View comet-ml/opik20
AI4Finance-Foundation / FinGPT
FinGPT: Open-Source Financial Large Language Models! Revolutionize 🔥 We release the trained model on HuggingFace.
View AI4Finance-Foundation/FinGPT21
jnMetaCode / agency-agents-zh
🎭 277 个即插即用的 AI 专家角色 — 支持 Claude Code/Cursor/Copilot 等 20 种工具，覆盖工程/设计/营销/金融等 20 个部门。含 64 个中国市场原创智能体（小红书/抖音/微信/飞书/钉钉/Qt 上位机/机械设计）。搭配编排器 agency-orchestrator，一句话即可让多位专家按 DAG 自动协作。
View jnMetaCode/agency-agents-zh22
EvoLinkAI / awesome-gpt-image-2-API-and-Prompts
GPT-Image-2 API and Prompts
View EvoLinkAI/awesome-gpt-image-2-API-and-Prompts23
tradecatlabs / vibe-coding-cn
Vibe Coding 从入门到精通教程｜AI 结对编程工作流｜Prompt、Skill、Workflow、上下文管理、codex实战指南
View tradecatlabs/vibe-coding-cn24
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YouMind-OpenLab / awesome-nano-banana-pro-prompts
🍌 World's largest Nano Banana Pro prompt library — 10,000+ curated prompts with preview images, 16 languages. Google Gemini AI image generation. Free & open source.
View YouMind-OpenLab/awesome-nano-banana-pro-prompts26
nidhinjs / prompt-master
A Claude skill that writes the accurate prompts for any AI tool. Zero tokens or credits wasted. Full context and memory retention
View nidhinjs/prompt-master27
langgptai / LangGPT
LangGPT: Empowering everyone to become a prompt expert! 🚀 📌 结构化提示词（Structured Prompt）提出者 📌 元提示词（Meta-Prompt）发起者 📌 最流行的提示词落地范式 | Language of GPT The pioneering framework for structured & meta-prompt
View langgptai/LangGPT28
EmbraceAGI / awesome-chatgpt-zh
ChatGPT 中文指南🔥，ChatGPT 中文调教指南，指令指南，应用开发指南，精选资源清单，更好的使用 chatGPT 让你的生产力 up up up! 🚀
View EmbraceAGI/awesome-chatgpt-zh29
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Imbad0202 / academic-research-skills-codex
Codex-native Academic Research Skills suite for human-in-the-loop academic research workflows
View Imbad0202/academic-research-skills-codex31
cobusgreyling / loop-engineering
Practical patterns, starters & CLI tools for loop engineering with AI coding agents. Design systems that prompt and orchestrate agents (inspired by Addy Osmani and Boris Cherny).
View cobusgreyling/loop-engineering32
microsoft / promptflow
Build high-quality LLM apps - from prototyping, testing to production deployment and monitoring.
View microsoft/promptflow33
LouisShark / chatgpt_system_prompt
A collection of GPT system prompts and various prompt injection/leaking knowledge.
View LouisShark/chatgpt_system_prompt34
kangarooking / cangjie-skill
把书、长视频、播客等高价值内容蒸馏成可执行的 Agent Skills（Distill high-value content from books, long-form videos, podcasts, and more into executable Agent Skills）
View kangarooking/cangjie-skill35
ZeroLu / awesome-nanobanana-pro
🚀 An awesome list of curated Nano Banana pro prompts and examples. Your go-to resource for mastering prompt engineering and exploring the creative potential of the Nano banana pro(Nano banana 2) AI
View ZeroLu/awesome-nanobanana-pro36
YouMind-OpenLab / awesome-gpt-image-2
🚀 World's largest GPT Image 2 prompt library, updated daily — 2000+ curated prompts with preview images, 16 languages.
View YouMind-OpenLab/awesome-gpt-image-237
EvoMap / evolver
The GEP-powered self-evolving engine for AI agents. Auditable evolution with Genes, Capsules, and Events. | evomap.ai
View EvoMap/evolver38
ai-boost / awesome-prompts
Curated list of chatgpt prompts from the top-rated GPTs in the GPTs Store. Prompt Engineering, prompt attack & prompt protect. Advanced Prompt Engineering papers.
View ai-boost/awesome-prompts39
rockbenben / ChatGPT-Shortcut
Stop writing prompts from scratch — a searchable prompt library for ChatGPT, Claude, Gemini and Cursor · Русский 한국어 العربية हिन्दी ไทย ｜ 别再从头写提示词：现成的拿来就用，好用的收进自己的库
View rockbenben/ChatGPT-Shortcut40
jnMetaCode / superpowers-zh
🦸 AI 编程超能力 · 中文增强版 — superpowers（250k+ ⭐）完整汉化 + 4 个中国原创 skills，让 Claude Code / Copilot CLI / Hermes Agent / Cursor / Windsurf / Kiro / Gemini CLI / Qoder 等 26 款 AI 编程工具真正会干活
View jnMetaCode/superpowers-zh41
jamez-bondos / awesome-gpt4o-images
Awesome curated collection of images and prompts generated by GPT-4o and gpt-image-1. Explore AI generated visuals created with ChatGPT and Sora
View jamez-bondos/awesome-gpt4o-images42
AI4Finance-Foundation / FinRobot
FinRobot: An Open-Source AI Agent Platform for Financial Applications using Large Language Models
View AI4Finance-Foundation/FinRobot43
NirDiamant / Prompt_Engineering
22 prompt engineering techniques with hands-on Jupyter Notebook tutorials, from fundamental concepts to advanced strategies for leveraging LLMs.
View NirDiamant/Prompt_Engineering44
mufeedvh / code2prompt
A CLI tool to convert your codebase into a single LLM prompt with source tree, prompt templating, and token counting.
View mufeedvh/code2prompt45
Zipstack / unstract
LLM-Driven Extraction of Unstructured Data — Built for API Deployments & ETL Pipeline Workflows
View Zipstack/unstract46
kyegomez / swarms
The Enterprise-Grade Multi-Agent Orchestration Framework. Website: https://swarms.ai
View kyegomez/swarms47
WenyuChiou / awesome-agentic-ai-zh
A trilingual (繁中 / English / 简中) learning roadmap for agentic AI: from LLM basics to multi-agent systems, with 240+ curated resources and hands-on examples. 中文 AI agent 學習地圖。
View WenyuChiou/awesome-agentic-ai-zh48
NeoVertex1 / SuperPrompt
SuperPrompt is an attempt to engineer prompts that might help us understand AI agents.
View NeoVertex1/SuperPrompt49
promptslab / Awesome-Prompt-Engineering
This repository contains a hand-curated resources for Prompt Engineering with a focus on Generative Pre-trained Transformer (GPT), ChatGPT, PaLM etc
View promptslab/Awesome-Prompt-Engineering50
langgptai / wonderful-prompts
🔥中文 prompt 精选🔥，ChatGPT 使用指南，提升 ChatGPT 可玩性和可用性！🚀
View langgptai/wonderful-prompts51
aimhubio / aim
Aim 💫 — An easy-to-use & supercharged open-source experiment tracker.
View aimhubio/aim52
swyxio / ai-notes
notes for software engineers getting up to speed on new AI developments. Serves as datastore for https://latent.space writing, and product brainstorming
View swyxio/ai-notes53
Helicone / helicone
🧊 Open source LLM observability platform. One line of code to monitor, evaluate, and experiment. YC W23 🍓
View Helicone/helicone54
ashishps1 / learn-ai-engineering
Learn AI and LLMs from scratch using free resources
View ashishps1/learn-ai-engineering55
FlorianBruniaux / claude-code-ultimate-guide
The most comprehensive Claude Code guide: agentic workflows, hooks, skills, MCP servers, quizzes, and production-ready templates. 430K+ lines.
View FlorianBruniaux/claude-code-ultimate-guide56
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thinkingjimmy / Learning-Prompt
Free prompt engineering online course. ChatGPT and Midjourney tutorials are now included!
View thinkingjimmy/Learning-Prompt58
Kiln-AI / Kiln
Build, Evaluate, and Optimize AI Systems. Includes evals, RAG, agents, fine-tuning, synthetic data generation, dataset management, MCP, and more.
View Kiln-AI/Kiln59
FellouAI / eko
Eko (Eko Keeps Operating) - Build Production-ready Agentic Workflow with Natural Language - eko.fellou.ai
View FellouAI/eko60
darrenhinde / OpenAgentsControl
AI agent framework for plan-first development workflows with approval-based execution. Multi-language support (TypeScript, Python, Go, Rust) with automatic testing, code review
View darrenhinde/OpenAgentsControl61
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trigaten / Learn_Prompting
Prompt Engineering, Generative AI, and LLM Guide by Learn Prompting | Join our discord for the largest Prompt Engineering learning community
View trigaten/Learn_Prompting63
liquidprompt / liquidprompt
A full-featured & carefully designed adaptive prompt for Bash & Zsh
View liquidprompt/liquidprompt64
promptslab / Promptify
Prompt Engineering | Prompt Versioning | Use GPT or other prompt based models to get structured output. Join our discord for Prompt-Engineering, LLMs and other latest research
View promptslab/Promptify65
serenakeyitan / awesome-notebookLM-prompts
A curated collection of the strongest NotebookLM slide prompts sourced from the real creative underground . Your go-to resource for AI powerpoint :P
View serenakeyitan/awesome-notebookLM-prompts66
kyegomez / tree-of-thoughts
Plug in and Play Implementation of Tree of Thoughts: Deliberate Problem Solving with Large Language Models that Elevates Model Reasoning by atleast 70%
View kyegomez/tree-of-thoughts67
conorbronsdon / avoid-ai-writing
Skill that audits and rewrites content to remove AI writing patterns. Use it with your favorite agents including Claude Code, OpenClaw, Codex, and Hermes.
View conorbronsdon/avoid-ai-writing68
luban-agi / Awesome-AIGC-Tutorials
Curated tutorials and resources for Large Language Models, AI Painting, and more.
View luban-agi/Awesome-AIGC-Tutorials69
Jia-Ethan / codex-keysmith
Versioned Codex instruction deployment with preview, ownership manifests, hook isolation, scenario evaluation, and recovery.
View Jia-Ethan/codex-keysmith70
IBM / mcp-context-forge
An AI Gateway, registry, and proxy that sits in front of any MCP, A2A, or REST/gRPC APIs, exposing a unified endpoint with centralized discovery, guardrails and management.
View IBM/mcp-context-forge71
0xNyk / council-of-high-intelligence
Structured multi-perspective deliberation for hard decisions. Run full councils, focused triads, or duo debates across Claude Code, Codex, Gemini CLI, and OpenCode.
View 0xNyk/council-of-high-intelligence72
algorithmicsuperintelligence / optillm
Optimizing inference proxy for LLMs
View algorithmicsuperintelligence/optillm73
UditAkhourii / adhd
ADHD — a skill for coding agents. Tree-of-thought with pruning, built on the Claude & Codex Agent SDK.
View UditAkhourii/adhd74
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urchade / GLiNER
Generalist and Lightweight Model for Named Entity Recognition (Extract any entity types from texts)
View urchade/GLiNER76
Hunyuan-PromptEnhancer / PromptEnhancer
[CVPR 2026] PromptEnhancer is a prompt-rewriting tool, refining prompts into clearer, structured versions for better image generation.
View Hunyuan-PromptEnhancer/PromptEnhancer77
zou-group / textgrad
TextGrad: Automatic ''Differentiation'' via Text -- using large language models to backpropagate textual gradients. Published in Nature.
View zou-group/textgrad78
atfortes / Awesome-LLM-Reasoning
From Chain-of-Thought prompting to OpenAI o1 and DeepSeek-R1 🍓
View atfortes/Awesome-LLM-Reasoning79
Open-Less / openless
Hold a key, speak, release — AI-polished text appears at your cursor in any app. Open-source voice input for macOS & Windows. (按住快捷键说话，松开即得润色后的文字)
View Open-Less/openless80
filipecalegario / awesome-generative-ai
A curated list of Generative AI tools, works, models, and references
View filipecalegario/awesome-generative-ai81
Leonxlnx / unlazy
Anti-laziness skill for AI agents. Core: the Depth Tree method, which splits a task N layers deep and gives every leaf the full time budget of the whole task, so effort multiplies with depth.
View Leonxlnx/unlazy82
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foryourhealth111-pixel / Vibe-Skills
Intelligent Skill routing and workflow orchestration for AI agents — +21.12 pp reward, −29.6% tokens on SkillsBench with DeepSeekV4Flash-VE.
View foryourhealth111-pixel/Vibe-Skills84
pezzolabs / pezzo
🕹️ Open-source, developer-first LLMOps platform designed to streamline prompt design, version management, instant delivery, collaboration, troubleshooting, observability and more.
View pezzolabs/pezzo85
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yanliudesign / mono-color-skill
One-ink editorial print image skill — warm paper, halftone photography, active negative space, and restrained typography.
View yanliudesign/mono-color-skill88
Forward-Future / loopy
A library of practical AI-agent loops and an installable skill for finding, adapting, and designing repeatable agent workflows.
View Forward-Future/loopy89
PenglongHuang / chinese-novelist-skill
🎭 AI 写小说：从零生成 10-50 章完整中文小说，三层问答 · 创作记忆 · 悬念钩子 · 自动校验，长篇网文连载皆宜｜开源免费，适配主流 coding agent｜AI novel writing skill
View PenglongHuang/chinese-novelist-skill90
wquguru / harness-books
📚 Two books on harness engineering — the design philosophies behind Claude Code & Codex: constraints, query loops, context governance, multi-agent verification. harness-books.agentway.dev
View wquguru/harness-books91
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KhazP / vibe-coding-prompt-template
Templates and workflow for generating PRDs, Tech Designs, and MVP and more using LLMs for AI IDEs
View KhazP/vibe-coding-prompt-template93
hegelai / prompttools
Open-source tools for prompt testing and experimentation, with support for both LLMs (e.g. OpenAI, LLaMA) and vector databases (e.g. Chroma, Weaviate, LanceDB).
View hegelai/prompttools94
ianarawjo / ChainForge
An open-source visual programming environment for battle-testing prompts to LLMs.
View ianarawjo/ChainForge95
wesammustafa / Claude-Code-Everything-You-Need-to-Know
A practical Claude Code guide with clear mental models and copy-paste examples — setup, prompt engineering, slash commands, skills, hooks, subagents, agent teams, and MCP servers.
View wesammustafa/Claude-Code-Everything-You-Need-to-Know96
Eladlev / AutoPrompt
A framework for prompt tuning using Intent-based Prompt Calibration
View Eladlev/AutoPrompt97
sergebulaev / linkedin-skills
Claude skills for LinkedIn. 11 Claude Code and Codex skills that write human-sounding LinkedIn posts, craft comments that get noticed, analyze your feed, and build a publishing cadence
View sergebulaev/linkedin-skills98
spcl / graph-of-thoughts
Official Implementation of "Graph of Thoughts: Solving Elaborate Problems with Large Language Models"
View spcl/graph-of-thoughts99
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microsoftarchive / promptbench
A unified evaluation framework for large language models
View microsoftarchive/promptbenchPrompt Optimization & Compression
- JuliusBrussee/caveman — ★ 106,886
- headroomlabs-ai/headroom — ★ 73,186
- linshenkx/prompt-optimizer — ★ 35,188
- mlflow/mlflow — ★ 28,051
- nidhinjs/prompt-master — ★ 13,402
- cobusgreyling/loop-engineering — ★ 11,263
- mufeedvh/code2prompt — ★ 7,679
- Kiln-AI/Kiln — ★ 5,078
Prompt Libraries, Templates & Collections
- f/prompts.chat — ★ 170,803
- dair-ai/Prompt-Engineering-Guide — ★ 78,489
- asgeirtj/system_prompts_leaks — ★ 67,787
- elder-plinius/CL4R1T4S — ★ 50,068
- github/awesome-copilot — ★ 39,184
- freestylefly/awesome-gpt-image-2 — ★ 32,925
- promptfoo/promptfoo — ★ 25,303
- EvoLinkAI/awesome-gpt-image-2-API-and-Prompts — ★ 17,211
Prompt Tuning & Evaluation
- langfuse/langfuse — ★ 34,845
- comet-ml/opik — ★ 22,157
- langgptai/LangGPT — ★ 12,540
- Arize-ai/phoenix — ★ 11,548
- microsoft/promptflow — ★ 11,245
- Helicone/helicone — ★ 6,166
- darrenhinde/OpenAgentsControl — ★ 4,862
- langwatch/langwatch — ★ 4,837
Guardrails, Structured Output & Testing
- dottxt-ai/outlines — ★ 15,843
- Zipstack/unstract — ★ 7,245
- promptslab/Promptify — ★ 4,636
- IBM/mcp-context-forge — ★ 4,504
- 0xNyk/council-of-high-intelligence — ★ 4,335
- Hunyuan-PromptEnhancer/PromptEnhancer — ★ 3,773
More AI Trending Projects
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→Iterative prompting: a loop, not a magic sentence
Iterative prompt refinement means treating a prompt as something you test rather than something you write once. The loop is short: write a first version, run it against a fixed set of inputs you care about, look at where it fails, change one thing, run it again. What makes that engineering rather than tinkering is the fixed set — a small evaluation file kept next to the prompt, so every change is measured against the same cases instead of your memory of last week.
Real examples of iteration look banal on purpose: moving an instruction from the middle of a long prompt to the end because the model honours the last constraint more reliably; replacing a vague adjective with an explicit output format; splitting one prompt that does three jobs into two that do one each. The optimiser projects below automate the search, but the loop is the technique — they simply run it faster than you can by hand.
What prompt compression does
Prompt compression is the family of techniques that shorten the input without changing the answer. It splits into two kinds. Token-level pruning deletes text the model demonstrably does not need — stop-words, duplicated instructions, boilerplate from a retrieved document — usually with a small trained model scoring each span. Prompt rewriting restates a long instruction more densely, often by letting a model do the shortening and then verifying that behaviour did not change. Both pay off when the same long prefix is sent on every request: cost scales with input tokens, so a prefix that is 40% smaller is a bill that is roughly 40% smaller, and long prompts also raise latency and lower reliability.
Prompt hygiene: versioning, evaluation, structure
Prompt hygiene is what keeps a working prompt working after three people have edited it. Concretely: keep prompts in version control as files rather than as strings buried in application code; keep a small evaluation set and run it before merging a prompt change, the same way you would run tests before merging code; state the output format explicitly and validate it, so a malformed answer surfaces as an error instead of a parse failure three services downstream. The structured-output and guardrail projects in the last section exist because asking politely for JSON is not a validation strategy.
Prompt engineering questions
What is iterative prompt refinement? Repeatedly revising a prompt and re-measuring it against a fixed set of test inputs, changing one variable per round, until the failure rate on those inputs is acceptable.
Which is an example of iteration in prompt engineering? Adding an explicit output schema after seeing the model return prose, re-running the same evaluation set, and confirming that parse failures dropped — then keeping the version that passed.
What is prompt compression? Reducing the number of tokens a prompt consumes while preserving the model behaviour you rely on, usually by pruning unnecessary spans or rewriting instructions more densely.
What is prompt hygiene? Treating prompts as versioned artefacts: stored in files, reviewed, tested against an evaluation set, with an explicit output contract and validation around them.
Do I need a framework to do this? No. A folder of prompt files, a script that runs them over a JSONL of cases and a diff of the results covers most of it. Frameworks start to pay off once the number of prompts and models grows.