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Sell a Prompt194 results for “chain_of_thought”
Multiple Use Auto Super Agents
The only prompt you will ever need
**SuperPrompt** by Quicksilver Create Anything You Can Imagine with This Structured
It automatically summons all necessary expert roles based on your desired output, then takes on those roles. It allows for an iterative process It allows for reference use in the process Make sure to change the {NAME} in the prompt to your own https://discord.com/channels/974519864045756446/1096142422725115995
Elastic Suite Attribute Set Extraction Prompt
LangChain Hub prompt: aamaro/elastic-suite-attribute-set-extraction-prompt
The Prompt Helping To Use OpenAI Tools Calling Abilities Together With Chain Of Thought. More Info: Https://github.com/dimitree54/yid Langchain Extensions
The prompt helping to use OpenAI tools calling abilities together with chain-of-thought. More info: https://github.com/dimitree54/yid_langchain_extensions
Better Chat
Want the perfect GPT? Here it is. @RealityMoez
Ultimate AI Prompting System
Unlock the power of AI with a multi-layered prompting strategy that crafts compelling, high-converting product descriptions. Using Tree of Thoughts, CoT, Oppositional Framing, Meta-Prompting, and RAG, this advanced method ensures depth, contrast, and precision—delivering persuasive, data-driven results that stand out....more
Payload Planner
LangChain Hub prompt: zulqarnain/payload_planner
NEW Now With Chain Of Thought! Evaluates And Scores Model Results Based On The Output They Generated For Their Given Input.
NEW - Now with chain of thought! Evaluates and scores Model results based on the output they generated for their given input.
Healthcare Ant
LangChain Hub prompt: kushthenoob/healthcare_ant
This Prompt Implements The Chain Of Thoughts
This prompt implements the chain of thoughts
An AI Driven Workflow To Collaborate With AI Assistants 'CoPilot' And 'Claude' For Knowledge Base Development, Transforming Unstructured User Inputs Into A Structured, JSON Formatted Knowledge Base.
An AI-driven workflow to collaborate with AI assistants 'CoPilot' and 'Claude' for knowledge base development, transforming unstructured user inputs into a structured, JSON-formatted knowledge base.
SUPERprompt - one to rule them all
One Prompt to rule them all. ChatGPT automatically takes on various expert roles at the same time, helps you build the perfect prompt, changes its strategy depending on your input and tries to find the best possible expert roles for your query. It reruns the initial prompt automatically throughout t
Prompt Otimizado Para Conversão De Bugs Em User Stories Com Alta Precisão, Utilizando Role Prompting, Few Shot E Chain Of Thought.
Prompt otimizado para conversão de bugs em User Stories com alta precisão, utilizando Role Prompting, Few-shot e Chain of Thought.
Swagger Buddy
LangChain Hub prompt: rdss/swagger--buddy
Generate Sql Query Prompt
LangChain Hub prompt: hj0302/generate_sql_query_prompt
Prompt Restaurado V20 Versão Final De Alta Precisão (Baseada Na V15)
Prompt Restaurado v20 - Versão Final de Alta Precisão (Baseada na v15)
Prompt Otimizado Para Converter Bugs Em User Stories Usando Role Prompting, Few Shot, Chain Of Thought, Rubric Based Prompting, Complexity Classification E Output Format
Prompt otimizado para converter bugs em User Stories usando Role Prompting, Few-Shot, Chain of Thought, Rubric-Based Prompting, Complexity Classification e Output Format
Prompt Otimizado Para Converter Relatos De Bugs Em User Stories Ágeis. Técnicas: Role Assignment, Few Shot Prompting, Explicit Output Format, Explicit Rules, Edge Case Handling, System/User Separation, Positive Framing, Chain Of Thought Via Scratchpad Implícito.
Prompt otimizado para converter relatos de bugs em User Stories ágeis. Técnicas: Role Assignment, Few-Shot Prompting, Explicit Output Format, Explicit Rules, Edge Case Handling, System/User Separation, Positive Framing, Chain-of-Thought via Scratchpad Implícito.
Prompt Otimizado Para Converter Relatos De Bug Em User Stories Ágeis (Como/Eu Quero/Para Que) Com Critérios De Aceitação Given When Then. Adapta O Nível De Detalhe À Complexidade Real Do Bug, Evita Alucinações E Segue Exatamente O Estilo Das References Do Dataset.
Prompt otimizado para converter relatos de bug em User Stories ágeis (Como/Eu quero/Para que) com Critérios de Aceitação Given-When-Then. Adapta o nível de detalhe à complexidade real do bug, evita alucinações e segue exatamente o estilo das references do dataset.
Two-Step Process for Creating and Refining Prompts for ChatGPT
This prompt guides the user in creating a new prompt for ChatGPT in two main steps. The first step involves formulating the prompt using the perfect prompt formula, which includes the context, specific information, intent/goal, and response format. The second step involves refining the prompt using eight strategies and techniques for optimizing ChatGPT performance in benchmarking assessments. The process is designed to be iterative and requires user input at each step. The final output is a refined prompt that is ready to be used with a GPT model.
Converte Relatos De Bugs Em User Stories Ágeis (Markdown + Critérios Gherkin), Com Critérios Convencionais Por Tipo De Bug E Profundidade Proporcional À Complexidade Do Relato. Técnicas Aplicadas: Few Shot Learning, Chain Of Thought, Role Prompting, Skeleton Of Thought
Converte relatos de bugs em User Stories ágeis (Markdown + critérios Gherkin), com critérios convencionais por tipo de bug e profundidade proporcional à complexidade do relato. Técnicas aplicadas: Few-shot Learning, Chain of Thought, Role Prompting, Skeleton of Thought
Prompt Otimizado Com Role Prompting, Chain Of Thought, Few Shot Learning E Skeleton Of Thought. Versão Final — Arquitetura De 3 Camadas: (1) Classificação Explícita Do Bug Antes De Escrever, (2) Skeleton Canônico Por Nível Ancorado Em Exemplos Verbatim Do Dataset, (3) Regras De Fidelidade Ao Relato. Elimina A Instabilidade Bimodal Das Iterações Anteriores Ao Substituir Routing Lógico Extenso Por Reconhecimento De Padrão Via Exemplos Completos Por Nível. Técnicas Aplicadas: Role Prompting, Few S
Prompt otimizado com Role Prompting, Chain of Thought, Few-shot Learning e Skeleton of Thought. Versão final — arquitetura de 3 camadas: (1) classificação explícita do bug antes de escrever, (2) skeleton canônico por nível ancorado em exemplos verbatim do dataset, (3) regras de fidelidade ao relato. Elimina a instabilidade bimodal das iterações anteriores ao substituir routing lógico extenso por reconhecimento de padrão via exemplos completos por nível. Técnicas aplicadas: Role Prompting, Few-shot Learning, Chain of Thought, Skeleton of Thought, Lexical Anchoring
Converte Relatos De Bugs Em User Stories Ageis Usando Few Shot, Chain Of Thought, Role Prompting E Rule Based Deduction. Preserva Dados Literais Do Bug E Deduz Boas Praticas Implicitas Por Categoria.
Converte relatos de bugs em User Stories ageis usando Few-shot, Chain of Thought, Role Prompting e Rule-based Deduction. Preserva dados literais do bug e deduz boas praticas implicitas por categoria.
Prompt Otimizado Para Converter Relatos De Bugs Em User Stories Claras, Completas E Prontas Para Desenvolvimento
Prompt otimizado para converter relatos de bugs em User Stories claras, completas e prontas para desenvolvimento