Fetches axiom-vision-diag from charleswiltgen/axiom and configures it for Cursor.
3
Select Cursor when prompted
The CLI shows a list of agents. Use arrow keys and space to select Cursor:
◆ Which agents do you want to install to?
│
│ ── Universal (.agents/skills) ────────────────
│ · Cline · Codex · Goose · Windsurf
│ ●Cursor(selected)
│ · Cursor · Aider · Continue
4
Verify installation
Confirm successful installation by checking the skill directory location:
.cursor/skills/axiom-vision-diag
Restart Cursor to activate axiom-vision-diag. Access via /axiom-vision-diag in your agent's command palette.
⚠
Security Notice
We perform automated surface-level scans (Gen AI Scanner, Socket, Snyk) during installation. These checks detect common vulnerabilities but do not guarantee complete security. Always review skill source code and verify the publisher's reputation before production use.
Skills execute code in your environment. Always review source, verify the publisher, and test in isolation before production.
Many landmarks < 0.3 → Poor lighting, occlusion, or edge of frame
Step 3: Verify Threading
print("🧵 Thread: \(Thread.current)")ifThread.isMainThread {print("❌ Running on MAIN THREAD - will block UI!")}else{print("✅ Running on background thread")}
Expected output:
✅ Background thread → Correct
❌ Main thread → Move to DispatchQueue.global()
Decision Tree
Vision not working as expected?
│
├─ No results returned?
│ ├─ Check Step 1 output
│ │ ├─ "Request failed" → See Pattern 1a (API availability)
│ │ ├─ "No results" → See Pattern 1b (nothing detected)
│ │ └─ Results but count = 0 → See Pattern 1c (edge of frame)
│
├─ Landmarks have nil/low confidence?
│ ├─ Hand pose → See Pattern 2 (hand detection issues)
│ ├─ Body pose → See Pattern 3 (body detection issues)
│ └─ Face detection → See Pattern 4 (face detection issues)
│
├─ UI freezing/slow?
│ ├─ Check Step 3 (threading)
│ │ ├─ Main thread → See Pattern 5a (move to background)
│ │ └─ Background thread → See Pattern 5b (performance tuning)
│
├─ Overlays in wrong position?
│ └─ See Pattern 6 (coordinate conversion)
│
├─ Person segmentation missing people?
│ └─ See Pattern 7 (crowded scenes)
│
├─ VisionKit not working?
│ └─ See Pattern 8 (VisionKit specific)
│
├─ Text recognition issues?
│ ├─ No text detected → See Pattern 9a (image quality)
│ ├─ Wrong characters → See Pattern 9b (language/correction)
│ └─ Too slow → See Pattern 9c (recognition level)
│
├─ Barcode detection issues?
│ ├─ Barcode not detected → See Pattern 10a (symbology/size)
│ └─ Wrong payload → See Pattern 10b (barcode quality)
│
├─ DataScannerViewController issues?
│ ├─ Blank screen → See Pattern 11a (availability check)
│ └─ Items not detected → See Pattern 11b (data types)
│
└─ Document scanning issues?
├─ Edges not detected → See Pattern 12a (contrast/shape)
└─ Perspective wrong → See Pattern 12b (corner points)
"VNGenerateForegroundInstanceMaskRequest is only available on iOS 17.0 or newer"
"VNDetectHumanBodyPose3DRequest is only available on iOS 17.0 or newer"
Root cause: Using iOS 17+ APIs on older deployment target
Prevention: Check API availability in axiom-vision-ref before implementing
Time to fix: 10 min
Pattern 1b: No Results (Nothing Detected)
Symptom: request.results == nil or results.isEmpty
Diagnostic:
// 1. Save debug image to PhotosUIImageWriteToSavedPhotosAlbum(debugImage,nil,nil,nil)// 2. Inspect visually// - Is subject too small? (< 10% of image)// - Is subject blurry?// - Poor contrast with background?
Common causes:
Subject too small (resize or crop closer)
Subject too blurry (increase lighting, stabilize camera)
Low contrast (subject same color as background)
Fix:
// Crop image to focus on region of interestlet croppedImage =cropImage(sourceImage, to: regionOfInterest)let handler =VNImageRequestHandler(cgImage: croppedImage)
Time to fix: 30 min
Pattern 1c: Edge of Frame Issues
Symptom: Subject detected intermittently as object moves across frame
Root cause: Partial occlusion when subject touches image edges
Diagnostic:
// Check if subject is near edgesiflet observation = results.first as?VNInstanceMaskObservation{let mask =try observation.createScaledMask(for: observation.allInstances, croppedToInstancesContent:true)let bounds =calculateMaskBounds(mask)if bounds.minX <0.1|| bounds.maxX >0.9|| bounds.minY <0.1|| bounds.maxY >0.9{print("⚠️ Subject too close to edge")}}
Fix:
// Add padding to capture arealet paddedRect
✓
Make data-driven prioritization decisions faster
Stakeholder Communication
Draft PRDs, status updates, and stakeholder presentations
›Access to product documentation and roadmap tools (Jira, Notion, etc.)
›Understanding of product management frameworks (RICE, Jobs-to-be-Done, etc.)
›Stakeholder contact information and communication channels
Time Estimate
30-60 minutes to see productivity improvements
Steps
1Install product management skill
2Start with user story generation for known feature
3Progress to competitive analysis: research 2-3 competitors
4Use for roadmap prioritization: apply RICE/ICE scoring
5Draft stakeholder communications and refine based on feedback
6Build template library for recurring PM tasks
7Share effective prompts with product team
Common Pitfalls
⚠Not validating competitive research—verify facts before sharing
⚠Accepting user stories without involving engineering team
⚠Over-relying on frameworks without qualitative judgment
⚠Not customizing outputs to company culture and communication style
⚠Skipping stakeholder validation of generated requirements
Best Practices
✓ Do
+Validate research and competitive analysis with real data
+Collaborate with engineering when generating technical requirements
+Customize frameworks and templates to your company context
+Use skill for first drafts, refine with stakeholder input
+Document successful prompt patterns for PM tasks
+Combine AI efficiency with human judgment and intuition
✗ Don't
−Don't publish competitive analysis without fact-checking
−Don't finalize user stories without engineering review
−Don't make prioritization decisions solely on AI scoring
−Don't skip customer validation of generated requirements
−Don't ignore company-specific context and culture
💡 Pro Tips
★Provide context: company goals, constraints, customer feedback
★Ask for alternatives: 'Show 3 ways to prioritize this roadmap'
★Request stakeholder-specific formatting: 'Executive summary vs. engineering spec'
★Use skill for 70% generation + 30% customization to company needs
When to Use This
✓ Use when
Use for user story writing, competitive research, roadmap prioritization, stakeholder communication, and PRD drafting. Best for reducing repetitive documentation and research work.
✗ Avoid when
Avoid for strategic product vision (requires deep customer empathy), pricing decisions (needs market and financial expertise), or when face-to-face customer discovery is more valuable than speed.
Learning Path
1Basic: user stories, feature specs, status updates
