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nidhinjs avatar

nidhinjs/prompt-master

0
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9,731 stars·1,152 forks·MIT·256 views

Prompt Master

Prompt Master is an AI skill that automates prompt engineering by detecting the target AI system and applying the correct prompt architecture automatically. It generates optimized prompts for over 30 different AI tools, adapting format and syntax to each target system without requiring manual conversion.

The system distinguishes itself through several integrated capabilities. It extracts missing dimensions of intent from vague requests by asking up to three targeted clarifying questions before generating a final prompt. A memory block of prior decisions and constraints is prepended to maintain consistency across conversation sessions, preventing the AI from contradicting earlier work. Additionally, it analyzes prompts against 35 common wasteful patterns and rewrites them for improved clarity and efficiency.

The project covers the full workflow of prompt engineering automation, including cross-tool syntax adaptation, intent clarification, context retention for conversational consistency, and prompt debugging through pattern analysis. It functions as both a prompt optimization tool and a cross-platform prompt generator, adapting prompts written for one AI system into the format required by a different target tool.

Features

  • Automated Prompt Engineering - Automates prompt engineering by detecting the target AI system and applying the correct prompt architecture.
  • Session Context Blocks - Prepends a memory block of prior decisions and constraints to prevent contradictions across sessions.
  • Cross-Platform Generators - Generates optimized prompts for over 30 AI tools by adapting format and syntax automatically.
  • Automatic Prompt Engineering - An AI skill that writes optimized prompts for any tool by detecting the target system automatically.
  • Session Memory Blocks - Prepends a memory block of prior decisions and constraints to maintain consistency across sessions.
  • Session Context Retention - Maintains a memory block of prior decisions and constraints to prevent contradictions across sessions.
  • Intent Extraction Systems - Asks targeted clarifying questions to fill missing dimensions of intent before generating prompts.
  • Prompt-to-Tool Adapters - Adapts prompts written for one AI system into the format and syntax required by a different target tool.
  • Cross-Tool Prompt Strategies - Converts prompts written for one AI system into the format and syntax required by a different target tool.
  • Prompt Debugging Utilities - Analyzes existing prompts to identify wasteful patterns and rewrites them for clarity and efficiency.
  • Cross-Tool Syntax Adapters - Automatically translates prompt syntax and format between over 30 different AI tools.
  • Prompt Optimization Tools - Analyzes prompts for 35 common token-wasting patterns and rewrites them for clarity and efficiency.
  • Cross-Platform Generators - Generates optimized prompts for over 30 AI tools by detecting the target system automatically.
  • Prompt Optimizers - Analyzes prompts, identifies 35 common wasteful patterns, and rewrites them for clarity and efficiency.
  • AI System Detectors - Automatically detects the target AI system and applies the correct prompt architecture.
  • Session Context Blocks - Prepends a memory block of prior decisions and constraints so the AI does not contradict earlier work.
  • Token Waste Detectors - Analyzes prompts against 35 common token-wasting patterns and rewrites them for efficiency.
  • Intent Clarification - Asks up to three targeted clarifying questions to fill missing dimensions of intent before generating prompts.

Star history

Star history chart for nidhinjs/prompt-masterStar history chart for nidhinjs/prompt-master

How this analysis was created: This summary and feature list are AI-generated from collected project material and can contain mistakes. Stars, license and language are imported from GitHub. Inclusion does not mean that we have tested or audited this project. Check the source documentation for any feature you depend on. Learn more on our About page.

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Frequently asked questions

What does nidhinjs/prompt-master do?

Prompt Master is an AI skill that automates prompt engineering by detecting the target AI system and applying the correct prompt architecture automatically. It generates optimized prompts for over 30 different AI tools, adapting format and syntax to each target system without requiring manual conversion.

What are the main features of nidhinjs/prompt-master?

The main features of nidhinjs/prompt-master are: Automated Prompt Engineering, Session Context Blocks, Cross-Platform Generators, Automatic Prompt Engineering, Session Memory Blocks, Session Context Retention, Intent Extraction Systems, Prompt-to-Tool Adapters.

Which projects share features with nidhinjs/prompt-master?

Projects with overlapping indexed features include: keirp/automatic_prompt_engineer — Automatic Prompt Engineer is a framework designed to automate the generation, refinement, and performance measurement… microsoft/typechat — TypeChat is a schema enforcement library and framework for building natural language interfaces. It ensures that… microsoft/lmops — LMOps is a research-driven operations framework for optimizing the deployment, fine-tuning, and performance of large… prompt-engineering/click-prompt — Click-prompt is a centralized management platform designed for engineering, organizing, and executing generative… mshumer/gpt-prompt-engineer — This project is an automated prompt engineering and optimization tool designed to iteratively create, test, and refine… stanfordnlp/dspy — DSPy is a declarative programming framework designed for building complex language model applications. It treats model…

Projects sharing features with Prompt Master

These projects share indexed features with Prompt Master. Shared tags can include platform or build tooling; verify the primary use case before treating a result as a replacement.
  • keirp/automatic_prompt_engineerkeirp avatar

    keirp/automatic_prompt_engineer

    1,360View on GitHub↗

    Automatic Prompt Engineer is a framework designed to automate the generation, refinement, and performance measurement of language model instructions. It functions as a systematic tool for optimizing prompt phrasing by iteratively testing candidate instructions against specific input and output datasets to maximize task accuracy. The system distinguishes itself through an evaluation-driven approach that uses automated feedback loops to score prompt variations. By employing template-based input structuring, it ensures consistent testing environments where candidate instructions are measured aga

    Python
    View on GitHub↗1,360
  • microsoft/typechatmicrosoft avatar

    microsoft/TypeChat

    8,666View on GitHub↗

    TypeChat is a schema enforcement library and framework for building natural language interfaces. It ensures that responses from large language models strictly adhere to predefined TypeScript type definitions, translating unstructured human language into predictable, structured data. The project functions as both a prompt generator and an output validator. It automatically creates model instructions by extracting requirements from type schemas to replace manual prompt engineering and verifies that model outputs match the required format. The system handles structured output generation and res

    TypeScript
    View on GitHub↗8,666
  • microsoft/lmopsmicrosoft avatar

    microsoft/LMOps

    4,418View on GitHub↗

    LMOps is a research-driven operations framework for optimizing the deployment, fine-tuning, and performance of large language models. It provides a specialized toolkit for foundation model adaptation, inference acceleration, prompt optimization, and context orchestration. The framework distinguishes itself through an inference accelerator that reduces token generation latency by verifying and copying overlapping text spans from reference documents. It also features a prompt engineering optimizer that employs reinforcement learning, beam search, and non-natural language markers to automaticall

    Python
    View on GitHub↗4,418
  • prompt-engineering/click-promptprompt-engineering avatar

    prompt-engineering/click-prompt

    2,389View on GitHub↗

    Click-prompt is a centralized management platform designed for engineering, organizing, and executing generative artificial intelligence prompts. It provides a dedicated workspace for users to construct, refine, and optimize prompt structures, ensuring that interactions with various artificial intelligence models remain consistent and structured. The platform distinguishes itself through a collaborative library that enables users to publish and share prompt collections, facilitating knowledge exchange within a community. It features an interactive builder that maps specific user requirements

    TypeScriptchatgptgithub-copilotprompt-engineering
    View on GitHub↗2,389
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