Ideas for Future Workflow Automation
June 8, 2026 · View on GitHub
Proposed Features
1. Auto-Open Browser on Startup
Current: User must manually navigate to http://localhost:3160/search after starting the engine.
Proposed: Automatically open browser and load search page when server starts.
// In engine/src/index.ts or startup script
server.listen(PORT, async () => {
console.log(`Server running on port ${PORT}`);
// Auto-open browser (macOS/Linux)
if (process.platform !== 'win32') {
const { exec } = require('child_process');
exec(`open http://localhost:${PORT}/search`);
} else {
// Windows
const { spawn } = require('child_process');
spawn('start', ['http://localhost:3160/search'], { detached: true });
}
});
Considerations:
- User may not want browser to auto-start (privacy, distraction)
- Should be configurable via
user_settings.json - Respect user preference for manual launch
2. VS Code Integration / Auto-Detect Workspace
Current: User must manually add project path in the GUI.
Proposed: Detect active VS Code workspace and auto-add to watch list.
// On engine startup, check if launched from VS Code
const { env } = process;
if (env.VSCODE_CWD && env.VSCODE_PID) {
// Add env.VSCODE_CWD to watched paths automatically
}
Alternative: VS Code extension that:
- Watches for Anchor Engine running on localhost:3160
- Automatically adds current workspace folder to watch list
- Shows engine status in Status Bar
- Provides "Start Watchdog" command
3. Incremental Index Correction
Current: Database rebuilds from scratch on startup (ephemeral design).
Proposed: Track file changes incrementally and update index as you code.
flowchart LR
A[File Write] --> B[Watchdog Detect Change]
B --> C[Extract Atoms]
C --> D[Update Molecules]
D --> E[Incremental Search Update]
E --> F[Serve Queries]
Benefits:
- No rebuild needed when editing a single file
- Instant search updates as you type
- Lower resource usage during development sessions
Challenges:
- Maintaining consistency with atomic transactions
- Handling deleted files and content removals
- Managing provenance chain updates
4. Project-Specific Context Awareness
Current: All data goes into a single database.
Proposed: Automatically detect multiple projects in workspace and create separate contexts.
// Example structure:
~/.anchor/notebook/
├── project-a/ # Files from .qwenpaw/workspaces/P1/coding_projects/myapp
├── project-b/ # Files from .qwenpaw/workspaces/P2/coding_projects/api-server
└── shared/ # Shared context (if any)
user_settings.json:
{
"paths": {
"notebook": "~/.anchor/notebook",
"contexts": {
"project-a": "~/coding_projects/myapp",
"project-b": "~/coding_projects/api-server"
}
}
}
UI Implications:
- Add "Switch Context" dropdown in search UI
- Different color coding for different projects
- Ability to run watchdog per-context
5. Incremental Corpus Backup
Current: Full corpus backup exports all molecules as YAML (takes time, requires I/O).
Proposed: Delta backups that only export changed records since last backup.
{
"incremental_backup": {
"last_full_backup": "2026-06-07T10:00:00Z",
"changes_since": {
"added": ["atom_abc123", "molecule_def456"],
"modified": ["atom_ghi789"],
"deleted": []
},
"checksums": { ... }
}
}
Restore Process:
- Full backup provides base snapshot
- Incremental backups apply deltas in order
- Much faster than full export for frequent backups
6. Live Preview Pane
Current: Search results require clicking to view full context.
Proposed: Side panel showing expanded molecule/atom content as you search.
block-beta
column1: Search Results List
column2: Context Expansion Area
block:Result[Result Item]
direction LR
title["Record Title"]
preview["Content Preview..."]
expand[Expand ↗]
end
Result --> expand --> context[Full Atom Content]
Implementation:
- Add "Expand" button to search results
- Show full atom/molecule text in right panel
- Support nested expansion (show related atoms)
7. Smart Tag Suggestions
Current: Tags must be manually assigned during ingestion.
Proposed: Auto-suggest tags based on content analysis.
// Example logic:
const analyzeTags = async (content: string) => {
const techStack = ['typescript', 'nodejs', 'react', 'docker'];
const keywords = techStack.filter(t =>
content.toLowerCase().includes(t)
);
return [...new Set(keywords)]; // Deduplicate
};
Benefits:
- Better searchability without manual effort
- Consistent tagging across corpus
- Can be overridden by user if needed
Priority Order
- Incremental Index Correction — highest impact for developer experience
- VS Code Integration — removes friction from setup
- Auto-Open Browser — convenience feature (low effort, high value)
- Project Context Awareness — enables multi-project workflows
- Live Preview Pane — improves search UX
- Incremental Backups — complements full backup system
Implementation Notes
Data Migration Path
When implementing incremental features:
- Keep existing ephemeral database design
- Add
last_updated_atcolumn to atoms/molecules tables - Track change timestamps for delta detection
Performance Considerations
- Incremental updates should be <100ms per file
- Avoid blocking UI during ingestion
- Use background workers for heavy operations
Testing Strategy
- Create "live-fire" test suite that:
- Writes test files
- Verifies immediate search availability
- Checks provenance chain integrity