proompts

A curated set of prompts in YAML for AI-assisted product development, regulatory workflows, and general operations. Prompts are organized by topic: ranging from code reviews to market research. You can mix and match them in your own agentic workflows!

🗺️ Directory Map

Path	Description	Key Contents
prompts/	The Core Library. YAML-based prompts organized by domain.	business/, clinical/, technical/
workflows/	Chained Sequences. Multi-step prompt chains for complex tasks.	technical/software_engineering/paw_workflow.workflow.yaml
tools/	The Engine Room. Utilities for maintenance and development.	scripts/ (Python), prompt_tools/ (Meta-prompts)
scripts/	Shell Wrappers. Convenience scripts for common tasks.	validate_prompts.sh
docs/	Knowledge Base. Guides, usage instructions, and generated docs.	USAGE.md, BEST_PRACTICES.md

System Architecture

graph TD
    %% Define Nodes
    A[Developers / Contributors] -->|Commit Changes| B(GitHub Repository)

    subgraph "Core Data"
        C1["prompts/<br>(.prompt.yaml)"]
        C2["workflows/<br>(.workflow.yaml)"]
        C1 -.->|Chained by| C2
    end
    B -->|Contains| C1
    B -->|Contains| C2

    subgraph "The Engine Room (scripts/)"
        D1(validate_prompts.sh)
    end

    %% Flow of Validation
    C1 -->|Validated by| D1
    C2 -->|Validated by| D1

    subgraph "Output Artifacts"
        E1["docs/<br>(Markdown site)"]
    end

    D1 -->|Builds| E1

    classDef default fill:#f9f9f9,stroke:#333,stroke-width:1px;
    classDef highlight fill:#e1f5fe,stroke:#01579b,stroke-width:2px;
    class C1,C2 highlight;

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Integrations

• Model Context Protocol (MCP) – Learn how to expose the local prompt library as tools for Claude Desktop and other MCP-compatible AI agents.

Docs

• 🚀 Quickstart: 5-Minute Onboarding – Start here! Learn how to run your first simulation.
• Full Table of Contents – Browse all prompts by category
• Usage Guide – Learn how to use and integrate prompts
• Developer Scripts – Tools for validating and maintaining the repo
• IDE JSON Schemas – Configure your IDE for prompt and workflow validation

Setup

To run validation scripts and tools locally, you need Python 3 and the required dependencies.

1. Create a virtual environment (optional but recommended):

   python3 -m venv venv
   source venv/bin/activate

2. Install dependencies:

   pip install -r requirements.txt

3. Run the validation script to verify everything is set up correctly:

   ./scripts/validate_prompts.sh

Prompt Schema

Prompts are stored as .prompt.yaml or .prompt.yml files. Each prompt file contains two sections:

• Runtime information – ordered messages with role/content pairs that form the actual prompt. Use {{variable}} placeholders for user-provided values.
• Development information – optional metadata that describes the prompt and how to test it.

Top-level fields available in a prompt file include:

• name – short human-readable title
• description – concise summary of what the prompt does
• model – model identifier
• modelParameters – optional model parameters such as temperature
• messages – list of system and user messages
• testData – example inputs with their expected outputs
• evaluators – rules for verifying model responses

See docs/template_prompt.prompt.md for a filled-out Markdown example, and docs/schemas/prompt.schema.json for the strict JSON schema definitions.

Prompt Workflows

In addition to individual prompts, this repository supports Prompt Workflows, which chain multiple prompts together to perform complex, multi-step tasks. Workflows are defined in .workflow.yaml files and call prompts located in dedicated workflow subfolders (e.g., prompts/clinical/protocol/protocol_workflow/). included runner script.

To learn more, see the Prompt Workflows Documentation.

Validation

To run all validation checks (YAML linting, schema validation, documentation index verification) locally, use the provided script:

./scripts/validate_prompts.sh

This script runs the following checks:

• cleanup_mac_files: Removes macOS metadata files (._*) to ensure a clean state.
• check_prompts: Verifies file naming conventions and directory structure.
• validate_prompt_schema: Ensures prompts follow the required schema (e.g., messages, testData).
• check_broken_links: Scans for broken internal links in documentation.
• yamllint: Lints YAML files for formatting.

It is recommended to run this script before committing changes.

Contributing

See CONTRIBUTING.md for detailed instructions on how to contribute.

1. Create prompts as .prompt.yaml or .prompt.md files that follow docs/schemas/prompt.schema.json and place them in the appropriate folder.
2. Review the Best Practices Guide for detailed guidance on creating high-quality prompts.
3. Ensure your prompt includes:
   • Meaningful testData with realistic examples (at least 1-2 test cases)
   • evaluators to validate output quality
   • Clear instructions and expected output format
4. Before committing, run validation:

   ./scripts/validate_prompts.sh

5. If you create a new directory, an overview.md will be generated automatically by the workflow.

The same validation runs in CI, but running checks locally helps catch issues early.

License

This project is licensed under the Proompts Personal Use License. Individuals may freely use, modify, and distribute the prompts for personal, non-commercial purposes. Commercial entities must obtain written permission from Frederick de Ruiter before using the material.