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Introduce PromptyDumpty #107
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Pull request overview
This PR introduces PromptyDumpty package manager support for HVE Core, enabling users to install chatmodes, prompts, instructions, and scripts via a simple command-line tool rather than manually cloning the repository. The implementation adds a comprehensive package manifest that catalogs all 61 artifacts across 8 functional categories, and updates the README with installation instructions highlighting this as the recommended approach.
Key Changes:
- Added
dumpty.package.yamlmanifest defining package metadata and all HVE Core artifacts - Updated README.md to feature PromptyDumpty installation as Option 1 (recommended)
- Organized artifacts into 8 categories enabling selective installation by workflow type
Reviewed changes
Copilot reviewed 2 out of 2 changed files in this pull request and generated 3 comments.
| File | Description |
|---|---|
| dumpty.package.yaml | New package manifest cataloging 14 chatmodes, 10 prompts, 17 instructions, and 20 script files with metadata, file paths, and category assignments |
| README.md | Added PromptyDumpty installation instructions as recommended Option 1, with pip install command and documentation link |
| - name: copilot-instructions | ||
| description: Comprehensive coding guidelines and instructions for hve-core | ||
| file: .github/copilot-instructions.md | ||
| installed_path: copilot-instructions.md |
Copilot
AI
Nov 28, 2025
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The copilot-instructions entry is missing the categories field, which all other instructions have. Since this is a comprehensive root-level instruction file that should apply to all development contexts, consider adding categories: [development] or document in the manifest comments why this instruction is category-free.
| installed_path: copilot-instructions.md | |
| installed_path: copilot-instructions.md | |
| categories: [development] |
| #### Option 2: Install via PromptyDumpty | ||
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| ```bash | ||
| pip install prompty-dumpty |
Copilot
AI
Nov 28, 2025
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The PromptyDumpty documentation URL https://dumpty.dev should be verified. If this URL doesn't exist or is a placeholder, consider linking to the actual PromptyDumpty documentation (e.g., GitHub repository or PyPI page).
| #### Option 1: Clone Repository | ||
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| To use HVE Core's GitHub Copilot customizations in your project, clone this repository as a sibling to your project and configure a multi-root workspace. See the [Getting Started Guide](docs/getting-started.md) for step-by-step instructions. | ||
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| #### Option 2: Install via PromptyDumpty | ||
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Copilot
AI
Nov 28, 2025
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[nitpick] Consider adding a brief note about where PromptyDumpty installs the artifacts (e.g., .github/chatmodes/hve-core/, .github/prompts/hve-core/, etc.) and whether any workspace configuration is needed after installation, to help users understand the difference between Option 1 and Option 2.
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The tool itself looks interesting. My question is "how do we want/expect hve-core to be installed by users?". The current guidance (and, I assume, testing) assumes that hve-core is cloned beside the project you're working on. That has some benefits:
However, the current guidance also has downsides:
The PromptyDumpty approach is different. Instead of using Personally, I like the PromptyDumpty approach. It's much clearer that these hve-core files become the users's files, and there there is no expectation that these files will be updated with back-compat in mind. Project-specific changes to these files can be committed along with the project. However, I worry that having 2 very different approaches confuses the user. Which do they pick, and why? My suggestion is that hve-core has one "opinionated" view of how it is used, and how it is installed, and that it should avoid having multiple options. If PromptyDumpty is that approach then great. If you want to have two approaches then both need to be tested, and both need to be explained in a way that helps users know which to choose and why. [BTW, I have no skin in this game at all. I just want to make sure that hve-core doesn't scare first-time users off by presenting a matrix of options and approaches, or give itself problems in terms of testing/supporting/documenting the differences in those approaches] |
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Thanks for having a look Martin.
This is the idea. You can customize the prompts to work within your environment. Dumpty allows you to update the prompts from source again but these updates will get captured as changes in your own git repo.
Yes the assets are considered yours once they get pulled down. It actually uses git under the hood but that is opaque. Once the assets are copied over, the link is severed. Those assets become the repos files from that point onwards. Dumpty lockfile just tracks all of it to make future removal or updates easier.
100% |
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@dasiths can you file an issue where we can talk through this proposal (rather than in the context of the PR)? |
Description
This PR introduces PromptyDumpty package support for HVE Core, making it easy to install chatmodes, prompts, instructions, and scripts into any project using a simple package manager.
Key Changes:
dumpty.package.yamlmanifest file defining all HVE Core artifactschatmodesandinstructionsartifact typesInstallation:
Users can now selectively install components by category (ado, git, development, documentation, testing, security, linting, data-science) or install everything at once.
Related Issue(s)
Type of Change
Select all that apply:
Code & Documentation:
Infrastructure & Configuration:
AI Artifacts:
prompt-builderchatmode and addressed all feedback.github/instructions/*.instructions.md).github/prompts/*.prompt.md).github/chatmodes/*.chatmode.md)Other:
Testing
Validation:
dumpty validate-manifest dumpty.package.yamlchatmodesandinstructionstypesExpected Installation Structure:
Package Categories:
ado- Azure DevOps workflows (5 agents, 4 prompts, 5 instructions)git- Git workflows (2 agents, 6 prompts, 2 instructions)development- Development tools (8 agents, 2 prompts, 9 instructions, 2 scripts)documentation- Documentation generators (3 agents, 1 instruction)testing- Testing tools (1 agent, 1 instruction)security- Security validation (1 agent, 3 scripts)linting- Code quality tools (13 script files)data-science- Data science workflows (3 agents)Checklist
Required Checks
AI Artifact Contributions
prompt-builderchatmode to review contributionprompt-builderreviewRequired Automated Checks
The following validation commands must pass before merging:
npm run lint:mdnpm run spell-checknpm run lint:frontmatternpm run lint:md-linksnpm run lint:psSecurity Considerations
Additional Notes
Benefits of PromptyDumpty Integration:
Future Enhancements:
v1.0.0)