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SQLite Metadata Proposal

This repository hosts a living proposal for building a cloud-agnostic metadata platform on top of SQLite. The goal is to capture design decisions, research notes, and implementation plans in a highly collaborative format that works for both humans and automation agents.

Quick Links

Getting Started

git clone https://github.com/ganesh47/sqlite-metadata-proposal.git
cd sqlite-metadata-proposal
gh repo sync
  1. Review open issues and the project board to understand current priorities.
  2. Open or select an issue (Planning / Research template) and self-assign.
  3. Create a feature branch (git switch -c docs/section-update-<issue#>).
  4. Make changes, update the proposal or notes, and open a pull request using the template.
  5. Ensure CI checks (markdown lint, link check) pass before requesting review.

Automation

  • markdown-lint: Runs on PRs and pushes touching .md to enforce style consistency.
  • link-check: Runs on PRs and a weekly schedule to keep references fresh.
  • auto-assign: Runs on PRs and issues to auto-assign work to @ganesh47.
  • spec-task-sync: Runs weekly (and via manual trigger) to mirror specs/tasks.json entries into GitHub issues with correct labels/assignees.

The project board uses the Stage single-select field with steps Backlog → Selected → In Progress → Review → Done.

Collaboration Rules

  • Branch per task; keep history tidy with squash merges.
  • Reference issues in commits/PRs (Closes #<id>).
  • Capture context in docs/notes/YYYY-MM-DD.md for research spikes.
  • Use labels + milestones to track progress toward proposal maturity.

Roadmap Milestones

  1. M1 – Foundations: Complete scaffolding, workflows, and baseline proposal structure.
  2. M2 – Architecture Draft: Produce the first end-to-end design narrative.
  3. M3 – Implementation Plan: Translate the proposal into actionable project work.

Support

Open a discussion if you have questions or suggestions: Discussions will be enabled soon to support broader async collaboration.

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Proposal for a cloud-agnostic metadata system built on SQLite

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