axiom-app-intents-ref▌
charleswiltgen/axiom · updated Apr 8, 2026
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Comprehensive guide to App Intents framework for exposing app functionality to Siri, Apple Intelligence, Shortcuts, Spotlight, and other system experiences. Replaces older SiriKit custom intents with modern Swift-first API.
App Intents Integration
Overview
Comprehensive guide to App Intents framework for exposing app functionality to Siri, Apple Intelligence, Shortcuts, Spotlight, and other system experiences. Replaces older SiriKit custom intents with modern Swift-first API.
Core principle App Intents make your app's actions discoverable across Apple's ecosystem. Well-designed intents feel natural in Siri conversations, Shortcuts automation, and Spotlight search.
When to Use This Skill
- Exposing app functionality to Siri and Apple Intelligence
- Making app actions available in Shortcuts app
- Enabling Spotlight search for app content
- Integrating with Focus filters, widgets, Live Activities
- Adding Action button support (Apple Watch Ultra)
- Debugging intent resolution or parameter validation failures
- Testing intents with Shortcuts app
- Implementing entity queries for app content
Related Skills
- app-shortcuts-ref — App Shortcuts for instant Siri/Spotlight availability without user setup
- core-spotlight-ref — Core Spotlight and NSUserActivity integration for content indexing
- app-discoverability — Strategic guide for making apps surface system-wide across all APIs
System Experiences Supported
App Intents integrate with:
- Siri — Voice commands and Apple Intelligence
- Shortcuts — Automation workflows
- App Shortcuts — Pre-configured actions available instantly (see app-shortcuts-ref)
- Spotlight — Search discovery
- Focus Filters — Contextual filtering
- Action Button — Quick actions (Apple Watch Ultra)
- Control Center — Custom controls
- WidgetKit — Interactive widgets
- Live Activities — Dynamic Island updates
- Visual Intelligence — Image-based interactions
Visual Intelligence Integration
IntentValueQuery
Allow users to circle objects in the Visual Intelligence camera and see matching results from your app:
@UnionValue
enum VisualSearchResult {
case landmark(LandmarkEntity)
case collection(CollectionEntity)
}
struct LandmarkIntentValueQuery: IntentValueQuery {
func values(for input: SemanticContentDescriptor) async throws -> [VisualSearchResult] {
// Match visual input to app entities
}
}
// Each entity type needs an OpenIntent
struct OpenLandmarkIntent: OpenIntent { /* ... */ }
struct OpenCollectionIntent: OpenIntent { /* ... */ }
Onscreen Entities
Associate app entities with visible content so users can ask Siri or ChatGPT about what's on screen:
struct LandmarkDetailView: View {
let landmark: LandmarkEntity
var body: some View {
Group { /* View content */ }
.userActivity("com.landmarks.ViewingLandmark") { activity in
activity.title = "Viewing \(landmark.name)"
activity.appEntityIdentifier = EntityIdentifier(for: landmark)
}
}
}
Core Concepts
The Three Building Blocks
1. AppIntent — Executable actions with parameters
struct OrderSoupIntent: AppIntent {
static var title: LocalizedStringResource = "Order Soup"
static var description: IntentDescription = "Orders soup from the restaurant"
@Parameter(title: "Soup")
var soup: SoupEntity
@Parameter(title: "Quantity")
var quantity: Int?
func perform() async throws -> some IntentResult {
guard let quantity = quantity, quantity < 10 else {
throw $quantity.needsValue("Please specify how many soups")
}
try await OrderService.shared.order(soup: soup, quantity: quantity)
return .result()
}
}
2. AppEntity — Objects users interact with
struct SoupEntity: AppEntity {
var id: String
var name: String
var price: Decimal
static var typeDisplayRepresentation: TypeDisplayRepresentation = "Soup"
var displayRepresentation: DisplayRepresentation {
DisplayRepresentation(title: "\(name)", subtitle: "$\(price)")
}
static var defaultQuery = SoupQuery()
}
3. AppEnum — Enumeration types for parameters
enum SoupSize: String, AppEnum {
case small
case medium
case large
static var typeDisplayRepresentation: TypeDisplayRepresentation = "Size"
static var caseDisplayRepresentations: [SoupSize: DisplayRepresentation] = [
.small: "Small (8 oz)",
.medium: "Medium (12 oz)",
.large: "Large (16 oz)"
]
}
AppIntent: Defining Actions
Essential Properties
struct SendMessageIntent: AppIntent {
// REQUIRED: Short verb-noun phrase
static var title: LocalizedStringResource = "Send Message"
// REQUIRED: Purpose explanation
static var description: IntentDescription = "Sends a message to a contact"
// OPTIONAL: Discovery in Shortcuts/Spotlight
static var isDiscoverable: Bool = true
// OPTIONAL: Launch app when run
static var openAppWhenRun: Bool = false
// OPTIONAL: Authentication requirement
static var authenticationPolicy: IntentAuthenticationPolicy = .requiresAuthentication
}
Parameter Declaration
struct BookAppointmentIntent: AppIntent {
// Required parameter (non-optional)
@Parameter(title: "Service")
var service: ServiceEntity
// Optional parameter
@Parameter(title: "Preferred Date")
var preferredDate: Date?
// Parameter with requestValueDialog for disambiguation
@Parameter(title: "Location",
requestValueDialog: "Which location would you like to visit?")
var location: LocationEntity
// Parameter with default value
@Parameter(title: "Duration")
var duration: Int = 60
}
Parameter Summary (Siri Phrasing)
How to use axiom-app-intents-ref 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-app-intents-ref
Execute installation command
Execute the skills CLI command in your project's root directory to begin installation:
The skills CLI fetches axiom-app-intents-ref 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-app-intents-ref. Access the skill through slash commands (e.g., /axiom-app-intents-ref) 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.
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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
4.4★★★★★51 reviews- ★★★★★Hiroshi Harris· Dec 28, 2024
axiom-app-intents-ref is among the better-maintained entries we tried; worth keeping pinned for repeat workflows.
- ★★★★★Layla Menon· Dec 16, 2024
axiom-app-intents-ref has been reliable in day-to-day use. Documentation quality is above average for community skills.
- ★★★★★Ira Nasser· Dec 16, 2024
Solid pick for teams standardizing on skills: axiom-app-intents-ref is focused, and the summary matches what you get after install.
- ★★★★★Layla Okafor· Nov 19, 2024
Solid pick for teams standardizing on skills: axiom-app-intents-ref is focused, and the summary matches what you get after install.
- ★★★★★Yusuf Johnson· Nov 7, 2024
Keeps context tight: axiom-app-intents-ref is the kind of skill you can hand to a new teammate without a long onboarding doc.
- ★★★★★Ira Park· Nov 7, 2024
axiom-app-intents-ref is among the better-maintained entries we tried; worth keeping pinned for repeat workflows.
- ★★★★★Layla Mensah· Oct 26, 2024
axiom-app-intents-ref is among the better-maintained entries we tried; worth keeping pinned for repeat workflows.
- ★★★★★Isabella Li· Oct 26, 2024
Keeps context tight: axiom-app-intents-ref is the kind of skill you can hand to a new teammate without a long onboarding doc.
- ★★★★★Sakura Smith· Oct 10, 2024
axiom-app-intents-ref has been reliable in day-to-day use. Documentation quality is above average for community skills.
- ★★★★★Rahul Santra· Sep 25, 2024
I recommend axiom-app-intents-ref for anyone iterating fast on agent tooling; clear intent and a small, reviewable surface area.
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