518b8eca85
md-first memory extraction framework for AI agents. Markdown is the single source of truth; SQLite holds state and LanceDB provides the rebuildable vector + BM25 + scalar index. The codebase follows a single-direction DDD layering (entrypoints -> service -> memory -> infra, with component / core / config cross-cutting) enforced by import-linter. Engineering surface: - Coding conventions in .claude/rules/ (path-scoped) and workflows in .claude/skills/ (/commit, /new-branch, /pr). - GitHub Actions CI runs make lint + test + integration; pre-commit mirrors the gates locally (ruff, hygiene hooks, gitlint commit-msg). - Commit messages follow Conventional Commits, enforced by gitlint. - make lint also enforces datetime two-zone discipline and OpenAPI drift.
38 lines
1.1 KiB
YAML
38 lines
1.1 KiB
YAML
name: Use-case proposal
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description: Propose an app, demo, or integration for use-cases/
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title: "[Use Case]: "
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labels: ["use case"]
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body:
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- type: textarea
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id: summary
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attributes:
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label: Summary
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description: What does the use case demonstrate?
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validations:
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required: true
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- type: textarea
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id: memory
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attributes:
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label: Memory behavior
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description: What should the agent remember, retrieve, or evolve over time?
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validations:
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required: true
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- type: textarea
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id: stack
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attributes:
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label: Stack and dependencies
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description: List frameworks, services, models, or external APIs.
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- type: textarea
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id: run
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attributes:
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label: Run path
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description: How should a new developer run or inspect it?
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- type: checkboxes
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id: checklist
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attributes:
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label: Contribution checklist
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options:
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- label: I can include a README with setup instructions.
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- label: I can avoid committing secrets, generated output, dependency folders, and image files.
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- label: I can include `.env.example` if configuration is needed.
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