feat: add comprehensive documentation for AI Workspace, including architecture, memory model, profiles, services, and security guidelines

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2026-05-21 09:32:09 -06:00
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# Security And Privacy
AI Workspace is designed for local-first, auditable context management. Treat it as a companion workspace that may contain sensitive project metadata and communication evidence.
## Rules
- Do not commit secrets, tokens, cookies, API keys, headers, or session IDs.
- Keep connector credentials in ignored `.env` files.
- Keep raw evidence outside canonical project memory until curated.
- Keep MCP read-only unless a write tool has explicit safety rules.
- Treat generated indexes as local artifacts because they may contain snippets from project notes.
- Prefer local services for corporate or confidential projects.
## Ignored Local State
Examples of local-only data:
```text
.aiw/runtime/
.aiw/indexes/
ai/inbox/mattermost-mirror/
scripts/*/.env
```
## Cloud Memory Systems
Tools such as mem9 or managed vector stores can be useful, but they introduce a data boundary.
Before enabling them for a project, decide:
- what data may be stored;
- whether cloud storage is allowed;
- whether self-hosting is required;
- who can inspect/delete memories;
- what happens when cloud memory conflicts with Markdown.
Default recommendation:
```text
Use cloud memory only for non-sensitive preferences unless a project policy approves broader use.
```
## MCP Safety
MCP clients may let models invoke tools automatically. For that reason, workspace MCP tools should stay read-only by default and return bounded, source-attributed context.
If future MCP write tools are added, require:
- explicit user intent;
- narrow target paths;
- clear diffs or summaries;
- no secret exposure;
- easy audit through git.
## Sharing The Repo
Before sharing or open-sourcing a reusable version:
1. Remove or isolate project-specific profile data.
2. Confirm ignored inbox/runtime files are not tracked.
3. Replace real profile examples with sanitized examples.
4. Keep reusable architecture docs in `docs/` and `core/`.
5. Keep confidential project knowledge in private profile/workspace data.