axiom-ios-vision▌
charleswiltgen/axiom · updated May 25, 2026
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You MUST use this skill for ANY computer vision work using the Vision framework.
iOS Computer Vision Router
You MUST use this skill for ANY computer vision work using the Vision framework.
When to Use
Use this router when:
- Analyzing images or video
- Detecting objects, faces, or people
- Tracking hand or body pose
- Segmenting people or subjects
- Lifting subjects from backgrounds
- Recognizing text in images (OCR)
- Detecting barcodes or QR codes
- Scanning documents
- Using VisionKit or DataScannerViewController
- Integrating with Visual Intelligence (iOS 26+ system camera feature)
Routing Logic
Vision Work
Implementation patterns → /skill axiom-vision
- Subject segmentation (VisionKit)
- Hand pose detection (21 landmarks)
- Body pose detection (2D/3D)
- Person segmentation
- Face detection
- Isolating objects while excluding hands
- Text recognition (VNRecognizeTextRequest)
- Barcode/QR detection (VNDetectBarcodesRequest)
- Document scanning (VNDocumentCameraViewController)
- Live scanning (DataScannerViewController)
- Structured document extraction (RecognizeDocumentsRequest, iOS 26+)
API reference → /skill axiom-vision-ref
- Complete Vision framework API
- VNDetectHumanHandPoseRequest
- VNDetectHumanBodyPoseRequest
- VNGenerateForegroundInstanceMaskRequest
- VNRecognizeTextRequest (fast/accurate modes)
- VNDetectBarcodesRequest (symbologies)
- DataScannerViewController delegates
- RecognizeDocumentsRequest (iOS 26+)
- Coordinate conversion patterns
Visual Intelligence integration → /skill axiom-vision-ref (see Visual Intelligence Integration section)
- Making app content discoverable to Visual Intelligence camera
IntentValueQueryandSemanticContentDescriptor- Deep linking from Visual Intelligence results
Diagnostics → /skill axiom-vision-diag
- Subject not detected
- Hand pose missing landmarks
- Low confidence observations
- Performance issues
- Coordinate conversion bugs
- Text not recognized or wrong characters
- Barcodes not detected
- DataScanner showing blank or no items
- Document edges not detected
Decision Tree
- Implementing (pose, segmentation, OCR, barcodes, documents, live scanning)? → vision
- Visual Intelligence system integration (camera feature, iOS 26+)? → vision-ref (Visual Intelligence section)
- Need API reference / code examples? → vision-ref
- Debugging issues (detection failures, confidence, coordinates)? → vision-diag
Anti-Rationalization
| Thought | Reality |
|---|---|
| "Vision framework is just a request/handler pattern" | Vision has coordinate conversion, confidence thresholds, and performance gotchas. vision covers them. |
| "I'll handle text recognition without the skill" | VNRecognizeTextRequest has fast/accurate modes and language-specific settings. vision has the patterns. |
| "Subject segmentation is straightforward" | Instance masks have HDR compositing and hand-exclusion patterns. vision covers complex scenarios. |
| "Visual Intelligence is just the camera API" | Visual Intelligence is a system-level feature requiring IntentValueQuery and SemanticContentDescriptor. vision-ref has the integration section. |
Critical Patterns
vision:
- Subject segmentation with VisionKit
- Hand pose detection (21 landmarks)
- Body pose detection (2D/3D, up to 4 people)
- Isolating objects while excluding hands
- CoreImage HDR compositing
- Text recognition (fast vs accurate modes)
- Barcode detection (symbology selection)
- Document scanning with perspective correction
- Live scanning with DataScannerViewController
- Structured document extraction (iOS 26+)
vision-diag:
- Subject detection failures
- Landmark tracking issues
- Performance optimization
- Observation confidence thresholds
- Text recognition failures (language, contrast)
- Barcode detection issues (symbology, distance)
- DataScanner troubleshooting
- Document edge detection problems
Example Invocations
User: "How do I detect hand pose in an image?"
→ Invoke: /skill axiom-vision
User: "Isolate a subject but exclude the user's hands"
→ Invoke: /skill axiom-vision
User: "How do I read text from an image?"
→ Invoke: /skill axiom-vision
User: "Scan QR codes with the camera"
→ Invoke: /skill axiom-vision
User: "How do I implement document scanning?"
→ Invoke: /skill axiom-vision
User: "Use DataScannerViewController for live text"
→ Invoke: /skill axiom-vision
User: "Subject detection isn't working"
→ Invoke: /skill axiom-vision-diag
User: "Text recognition returns wrong characters"
→ Invoke: /skill axiom-vision-diag
User: "Barcode not being detected"
→ Invoke: /skill axiom-vision-diag
User: "Show me VNDetectHumanBodyPoseRequest examples"
→ Invoke: /skill axiom-vision-ref
User: "What symbologies does VNDetectBarcodesRequest support?"
→ Invoke: /skill axiom-vision-ref
User: "RecognizeDocumentsRequest API reference"
→ Invoke: /skill axiom-vision-ref
User: "How do I make my app work with Visual Intelligence?"
→ Invoke: /skill axiom-vision-ref
User: "How do users discover my app content through the camera?"
→ Invoke: /skill axiom-vision-ref
How to use axiom-ios-vision on Cursor
AI-first code editor with Composer
Prerequisites
Before installing skills in Cursor, ensure your development environment meets these requirements:
- ›Cursor installed and configured on your development machine
- ›Node.js version 16.0+ with npm package manager (verify with
node --version) - ›Active project directory or workspace where you want to add axiom-ios-vision
Execute installation command
Execute the skills CLI command in your project's root directory to begin installation:
The skills CLI fetches axiom-ios-vision from GitHub repository charleswiltgen/axiom and configures it for Cursor.
Select Cursor when prompted
The CLI will show a list of available agents. Use arrow keys to navigate and space to select Cursor:
Verify installation
Confirm successful installation by checking the skill directory location:
Reload or restart Cursor to activate axiom-ios-vision. Access the skill through slash commands (e.g., /axiom-ios-vision) or your agent's skill management interface.
Security & Verification 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 development environment. Always verify the publisher's identity, review recent commits, and test in isolated environments before production deployment.
List & Monetize Your Skill
Submit your Claude Code skill and start earning
Use Cases▌
User Story & Requirements Generation
Create detailed user stories, acceptance criteria, and feature specs
Example
Generate user stories for 'password reset feature' with acceptance criteria, edge cases, and test scenarios
Reduce spec writing time by 50%, ensure comprehensive coverage
Competitive Analysis
Research competitors, compare features, identify gaps
Example
Analyze 5 competitor products, create feature comparison matrix, suggest differentiation opportunities
Complete competitive research in 2 hours instead of 2 days
Roadmap Prioritization
Evaluate features using frameworks (RICE, ICE, Kano) and create prioritized backlogs
Example
Score 20 feature ideas using RICE framework, generate prioritized roadmap with rationale
Make data-driven prioritization decisions faster
Stakeholder Communication
Draft PRDs, status updates, and stakeholder presentations
Example
Create executive summary of Q3 roadmap, monthly progress report, feature launch announcement
Save 3-5 hours/week on communication overhead
Implementation Guide▌
Prerequisites
- ›Claude Desktop or compatible AI client
- ›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
Installation Steps
- 1.Install product management skill
- 2.Start with user story generation for known feature
- 3.Progress to competitive analysis: research 2-3 competitors
- 4.Use for roadmap prioritization: apply RICE/ICE scoring
- 5.Draft stakeholder communications and refine based on feedback
- 6.Build template library for recurring PM tasks
- 7.Share 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
- 2Intermediate: competitive analysis, prioritization frameworks, PRDs
- 3Advanced: product strategy, go-to-market planning, OKR setting
- 4Expert: product vision, market positioning, business model innovation
Discussion
Product Hunt–style comments (not star reviews)- No comments yet — start the thread.
Ratings
4.6★★★★★61 reviews- ★★★★★Kofi Rahman· Dec 24, 2024
axiom-ios-vision reduced setup friction for our internal harness; good balance of opinion and flexibility.
- ★★★★★Kofi Farah· Dec 8, 2024
Useful defaults in axiom-ios-vision — fewer surprises than typical one-off scripts, and it plays nicely with `npx skills` flows.
- ★★★★★Mei Rao· Dec 4, 2024
Keeps context tight: axiom-ios-vision is the kind of skill you can hand to a new teammate without a long onboarding doc.
- ★★★★★Kaira Flores· Dec 4, 2024
axiom-ios-vision is among the better-maintained entries we tried; worth keeping pinned for repeat workflows.
- ★★★★★Kofi Flores· Nov 27, 2024
I recommend axiom-ios-vision for anyone iterating fast on agent tooling; clear intent and a small, reviewable surface area.
- ★★★★★Kofi Abbas· Nov 23, 2024
axiom-ios-vision is among the better-maintained entries we tried; worth keeping pinned for repeat workflows.
- ★★★★★Kaira Lopez· Nov 23, 2024
Keeps context tight: axiom-ios-vision is the kind of skill you can hand to a new teammate without a long onboarding doc.
- ★★★★★Diya Jackson· Nov 19, 2024
We added axiom-ios-vision from the explainx registry; install was straightforward and the SKILL.md answered most questions upfront.
- ★★★★★Evelyn Taylor· Nov 15, 2024
Solid pick for teams standardizing on skills: axiom-ios-vision is focused, and the summary matches what you get after install.
- ★★★★★Diya Thomas· Nov 15, 2024
axiom-ios-vision has been reliable in day-to-day use. Documentation quality is above average for community skills.
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