Capture Context. Analyze Flow. Query the Hive Mind.
"Software collaboration is broken. We interrupt engineers like routers. DevScope captures the context so you don't have to."
- Bus Factor: When a developer leaves, history leaves with them. Commits show what changed, never how we got there.
- Interruption Tax: Getting context means DM pings (“Hey, how does the Auth API work?”). Every sync interruption kills flow.
- Humans as Routers: Engineers burn cycles ferrying tribal knowledge instead of building.
DevScope solves this by creating an Organization-Wide Hive Mind. It runs silently on local machines, captures "Deep Work" context using Multimodal AI (Vision + LLM), and syncs it to a central JSON-based RAG system—allowing teams to query history without breaking flow.
graph TD
subgraph "Local Client (System)"
A[Screen Telemetry] -->|Capture| B(Dual Context Engine)
B -->|Frame + Metadata| C{Privacy Firewall}
C -- Allowed --> D[Gemini 2.0 Vision]
C -- Blocked --> X((Drop))
D -->|Structured Log| E[Local Ring Buffer]
end
subgraph "Knowledge Layer"
E -->|Sync| F[(MongoDB Atlas)]
F -->|Indexing| G[Searchable Hive Mind]
end
subgraph "Interaction"
H[Teammate] -->|Query| I[Oracle Interface]
I -->|Retrieve| F
F -->|Context| I
end
- Panoramic + Resized Input:
msscaptures the stitched virtual desktop, then downsamples to 1080p via Pillow so Gemini never chokes on 4K dual-monitor payloads. - Foveal Focus Telemetry: AppKit/Quartz provides the active app and frontmost window title, giving Gemini an authoritative “what the engineer is actually touching” signal.
- Smart Extractor Prompting: A senior-auditor style system prompt instructs Gemini to trust the active focus, describe the exact action/target (“Editing the JSON schema”), and ignore background noise (Spotify, Discord).
- Ring Buffer & Auto-Cleanup: Each session’s deque stores ~30 minutes of entries; when it overflows we evict the oldest record and delete its PNG, guaranteeing bounded disk usage.
- Timed/On-Demand Runs: Daemon wakes every 30 minutes to sweep each session’s
temp_diskfolder. - Gemini 1.5 Pro Standup: Large-context prompt converts the entire visual reel into a markdown Daily Standup Report (features, bugs, research, context score).
- Hive Mind Storage: Summaries land in the Atlas
session_summariescollection withuser_id,project_name, and timestamp, creating a searchable history.
- Deep Work Filter: Metadata is uploaded only if the frame is aligned with the stated goal. Social media, banking, or idle states never leave the laptop.
- Flexible Schema: Each document stores timestamp, project, technical context, and alignment score—perfect for Visual RAG without schema migrations.
- Org-Level Tagging: Every record automatically carries the NYU team org tag plus
user_idandproject_name, so queries can scope to a squad or span the entire company.
| Capability | Engineering Logic |
|---|---|
| Dual-Context Capture | Uses mss for panoramic capture + Quartz to identify active window focus. This prevents background noise from confusing the AI. |
| Privacy Firewall | A local classifier runs before upload. If is_deep_work == False or app in blacklist, the frame is dropped instantly. Zero PII leaves the device. |
| Visual RAG | Instead of just text embeddings, we store the semantic description of the screen state. Querying "Show me the UI glitch" actually finds the visual context. |
| Mission Control | A PyQt dashboard for multi-session management, live activity buffer, and status logs. Features collapsible cards and real-time buffer updates. |
- macOS Sequoia/Sonoma with Screen Recording permission
- Python 3.10+
GEMINI_API_KEY(Gemini 2.0 Flash)
# 1. Clone & Env
git clone git@github.com:NamanVashishta/DevScope.git
cd DevScope
python3 -m venv venv && source venv/bin/activate
# 2. Install
pip install -r requirements.txt
# 3. Configure
export GEMINI_API_KEY="AIza..."
# 4. Run
python3 src/main.pyWant to test the Hive Mind without waiting 30 days?
# Generate ~840 activity entries and summaries for 7 team members
python3 scripts/ghost_team.py --entries-per-user 120 --days 30A PyQt dashboard for multi-session management.
- Live Activity Buffer: Watch the AI analyze your screen in real-time.
- Debounced Updates: Zero-flicker UI updates even with high-frequency capture.
Productivity analytics dashboard.
- Deep Work Metrics: Visualizes your "Flow State" vs "Fragmentation".
- App Usage: Breakdowns of VS Code vs Slack vs Chrome.
Query-specific project or org-wide scope.
- Smart Formatting: Gemini returns answers with icons (📋 Summary,
⚠️ Risks). - Project Discovery: Automatically combines local projects with those found in the MongoDB Graph.
"Is this spyware?" No. We built a Privacy Firewall that runs locally before any data leaves your machine.
- Local Privacy Classifier:
DEVSCOPE_PRIVACY_APPS(e.g., 1Password, Banking) triggers a hardware-level capture halt. - Deep Work Gate: The Vision AI labels every frame. If
is_deep_work == False(e.g., Reddit, YouTube), the frame is scrubbed locally. - No Screenshots in Cloud: Only structured JSON metadata touches the database. Raw images are deleted from the local ring buffer every 30 mins.
- Maker-First: We verify Context before we verify Upload.
| Question | Response |
|---|---|
| Why MongoDB Atlas? | Engineering context is messy. Mongo’s flexible document model ingests multimodal metadata (error codes, app names) without painful schema migrations. |
| How is this collaborative? | DevScope enables “Async Omniscience.” Teammates unblock each other by querying the Hive Mind instead of DM’ing for status updates. |
| What about privacy apps? | Configure DEVSCOPE_PRIVACY_APPS="Safari,Notes,1Password" etc. Blocklisted apps short-circuit capture before frames ever reach disk. |
- Windows/Linux Support: Porting
AppKitlogic toWin32APIandX11. - IDE Plugin: Bringing the Oracle directly into VS Code.
- Self-Hosted Mode: Allow teams to bring their own S3/Mongo for total data sovereignty.
DevScope is released under the MIT License.
Naman Vashishta | 2026