Install
$ agentstack add skill-lhbsaa-embedded-dev-skill-embedded-gui-feedback ✓ scanned · ✓ verified, works with Claude Code, Cursor, and more.
Security review
✓ PassedNo issues found. Passed automated security review. · v0.1.0 How review works →
- ✓ Prompt-injection patterns
- ✓ Secret / credential exfiltration
- ✓ Dangerous shell & filesystem operations
- ✓ Untrusted network calls
- ✓ Known-malicious package signatures
What it can access
- ✓ Network access No
- ✓ Filesystem access No
- ✓ Shell / process execution No
- ✓ Environment & secrets No
- ✓ Dynamic code execution No
From automated source analysis of v0.1.0. “Used” means the capability is present in the source — more access means more to trust, not that it’s unsafe.
Verified badge
Passed review? Show it. Paste this badge into your README, it links to the public security report.
Reliability & compatibility
Declared compatibility
Compatibility is declared by the source manifest. End-to-end runtime verification is coming, see below.
We're building live execution health for every listing: tool-call success rate, median latency, uptime, and last-checked timestamps, measured, not self-reported. It isn't live yet, so we don't show numbers we can't stand behind.
How agent discovery & health will work →About
Embedded GUI Feedback
Overview
Visual verification for LCD/GUI projects. Human eye misses timing, alignment, and color issues. Camera capture + AI analysis catches them.
Core principle: Camera evidence, not human judgment.
Context: Run after embedded-verification passes for display projects.
When NOT to use: Projects without GUI/display components.
When to Use
- LCD driver projects
- Display configuration changes
- GUI layout updates
- Font/color modifications
- Any visual output project
Camera Setup
Requirements
- USB webcam (1080p recommended)
- Centered on LCD screen
- Uniform lighting (avoid glare)
- Distance: 15-30cm from screen
Windows Setup
# List cameras
python scripts/camera_capture.py --list
# Capture
python scripts/camera_capture.py --resolution 1920x1080 --session
Linux/macOS Setup
# List cameras
python scripts/camera_capture.py --list
# Capture
python scripts/camera_capture.py --resolution 1920x1080 --session
Process
1. Check Camera Available
Run: python scripts/camera_capture.py --list
If no cameras:
- Prompt user to connect camera
- Offer alternative: manual photo upload
2. Capture Display
Run: python scripts/camera_capture.py --session
Output: screenshots/capture_YYYYMMDD_HHMMSS.png
Session folder: Creates timestamped folder for multiple captures.
3. Image Analysis
Use image_read tool with analysis prompt:
Analyze LCD display for:
- Layout: Correct positioning?
- Font: Readable, correct size?
- Color: Expected colors displayed?
- Alignment: Elements aligned properly?
- Overlap: Any overlapping elements?
- Blank areas: Unexpected empty regions?
Compare to expected: [describe expected output]
4. Issue Detection
| Issue Type | Visual Indicator | Likely Cause | |------------|------------------|--------------| | Blank screen | No pixels | Init sequence wrong | | Partial display | Top/bottom missing | MADCTL value incorrect | | Color wrong | Wrong colors | Color format mismatch | | Offset display | Content shifted | ygap/xgap incorrect | | Mirror/flip | Content reversed | MADCTL rotation bits | | Flickering | Brightness varies | Refresh timing | | Lines missing | Horizontal gaps | DMA chunking issue |
5. Fix and Re-verify
If issues found:
1. Analyze cause from table
2. Apply fix
3. idf.py build flash monitor
4. Re-capture display
5. Re-analyze
6. Loop until approved
6. Save Evidence
Write: docs/embedded/screenshots/YYYY-MM-DD--analysis.md
Include:
- Before/after captures
- Issue descriptions
- Fixes applied
- Final status
Analysis Prompt Template
Use prompts/gui-feedback.md or inline:
Context: [Chip] + [Controller] + [Resolution]
Expected Display:
[Describe what should be shown]
Image: [path to capture]
Analyze for issues:
1. Blank screen → check init
2. Partial → check MADCTL
3. Wrong colors → check format
4. Offset → check gaps
5. Mirror → check rotation
6. Flickering → check timing
7. Gaps → check DMA
Provide:
- Issues found: [list]
- Likely cause: [analysis]
- Recommended fix: [action]
Comparison Workflow
For before/after analysis:
# Capture before
python scripts/camera_capture.py --session --count 1
# Apply fix
idf.py build flash monitor
# Capture after
python scripts/camera_capture.py --session --count 1
# Compare
python scripts/image_compare.py --before [before.png] --after [after.png]
Common Fixes
| Issue | Fix Location | Parameter | |-------|--------------|-----------| | Blank | Driver init | Reset sequence | | Partial | MADCTL | 0x00/0xC0/0x80 | | Offset | Driver config | ygap, xgap | | Mirror | MADCTL | Bit 5, 6, 7 | | Color | Color format | RGB565/RGB666 | | DMA overflow | Write function | Chunk size |
Red Flags - STOP
- "Looks fine to me" (no camera)
- Skipping camera capture
- No analysis before claiming "correct"
- Single capture (no comparison available)
- Truncated image analysis
ALL mean: STOP. Capture with camera, analyze properly.
Output Format
## GUI Feedback Report
### Capture
Camera: [status]
File: screenshots/[filename].png
Resolution: 1920x1080
### Analysis
Layout: [PASS/FAIL] - [details]
Font: [PASS/FAIL] - [details]
Color: [PASS/FAIL] - [details]
Alignment: [PASS/FAIL] - [details]
Overlap: [PASS/FAIL] - [details]
### Issues
[list or "None detected"]
### Fixes Applied
[list or "None needed"]
### Final Status
GUI: APPROVED / NEEDS FIX
Evidence: [capture path]
Transition
If GUI APPROVED:
GUI verification complete.
Project finished. Update AGENTS.md with findings.
Full workflow complete:
- brainstorming → driver-design → implementation → verification → gui-feedback
If GUI NEEDS FIX:
GUI issues detected. Apply fixes, re-verify, re-capture.
Do NOT claim completion until GUI approved.
Anti-Patterns
| Bad | Good | |-----|------| | "Display looks correct" | Camera capture + analysis | | Skip camera | Always capture for GUI projects | | Single glance | Multiple captures, comparison | | No before/after | Capture before fix, compare after | | Human judgment only | AI analysis + visual evidence |
Source & license
This open-source skill is cataloged on AgentStack and links to its original source — we do not rehost the code.
- Author: lhbsaa
- Source: lhbsaa/embedded-dev-skill
- License: MIT
Install and usage instructions live in the source repository linked above.
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Versions
- v0.1.0 Imported from the upstream source.