dot-ai-request-dot-ai-feature

Request Feature in dot-ai Project

Write a feature request to a file in the target dot-ai project's tmp directory. The user will review and approve the write operation.

Projects

Project	Directory	Description
dot-ai	../dot-ai	Main MCP server (API endpoints, tools, handlers)
dot-ai-ui	../dot-ai-ui	Web UI for visualizations and dashboard
dot-ai-controller	../dot-ai-controller	Kubernetes controller
dot-ai-stack	../dot-ai-stack	Stack deployment configs
dot-ai-website	../dot-ai-website	Documentation website

Important: Do NOT use this skill to request features in the project you're currently working in. Just implement them directly.

Process

1. Determine the target project from the user's request
2. Determine the current project name from the directory name: basename $(git rev-parse --show-toplevel)
3. Delete any existing feature-request.md in the target project's tmp directory (so the diff only shows new content)
4. Write the feature request to: ../[target-project]/tmp/feature-request.md
5. Tell the user to open the target project and run /process-feature-request

File Format

Write the feature request file with this content (replace [CURRENT_PROJECT] with the actual project name from step 2):

# Feature Request from [CURRENT_PROJECT]

**Requesting project directory:** ../[CURRENT_PROJECT]

## What We Need

[DESCRIPTION OF WHAT WE NEED AND WHY]

## Our Suggestion

(You decide the best approach)

- [Suggested approach or implementation idea]

## Context

[What this unblocks in our project]

## Notes

You're the expert on this codebase. Feel free to implement this differently if there's a better approach, or push back if this doesn't make sense.

## Response Instructions

After implementing this feature, write a response file to help the requesting project integrate:

1. Write to: `../[CURRENT_PROJECT]/tmp/feature-response.md`
2. Include: what was implemented, how to use it (API signatures, endpoints, types), and any usage examples

Guidelines

1. Describe what you need and why, not how to implement it
2. Suggestions are just suggestions - the receiving agent decides the approach
3. The receiving agent is the authority on their codebase
4. Keep the request focused on the problem, not the solution
5. The user will review the write operation before it's accepted