axiom-ios-data▌
charleswiltgen/axiom · updated Apr 8, 2026
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You MUST use this skill for ANY data persistence, database, axiom-storage, CloudKit, or serialization work.
iOS Data & Persistence Router
You MUST use this skill for ANY data persistence, database, axiom-storage, CloudKit, or serialization work.
When to Use
Use this router when working with:
- Databases (SwiftData, Core Data, GRDB, SQLiteData)
- Schema migrations
- CloudKit sync
- File storage (iCloud Drive, local storage)
- Data serialization (Codable, JSON)
- Storage strategy decisions
- Keychain / secure credential storage
- Encryption, signing, key management (CryptoKit)
Routing Logic
SwiftData
Working with SwiftData → /skill axiom-swiftdata
Schema migration → /skill axiom-swiftdata-migration
Migration issues → /skill axiom-swiftdata-migration-diag
Migrating from Realm → /skill axiom-realm-migration-ref
SwiftData vs SQLiteData → /skill axiom-sqlitedata-migration
Other Databases
GRDB queries → /skill axiom-grdb
SQLiteData → /skill axiom-sqlitedata
Advanced SQLiteData → /skill axiom-sqlitedata-ref
Core Data patterns → /skill axiom-core-data
Core Data issues → /skill axiom-core-data-diag
Migrations
Database migration safety → /skill axiom-database-migration (critical - prevents data loss)
Serialization
Codable issues → /skill axiom-codable
Cloud Storage
Cloud sync patterns → /skill axiom-cloud-sync
CloudKit → /skill axiom-cloudkit-ref
iCloud Drive → /skill axiom-icloud-drive-ref
Cloud sync errors → /skill axiom-cloud-sync-diag
Keychain & Encryption
Keychain / secure credential storage → /skill axiom-keychain
Keychain errors → /skill axiom-keychain-diag
Keychain API reference → /skill axiom-keychain-ref
Encryption / signing / key management → /skill axiom-cryptokit
CryptoKit API reference → /skill axiom-cryptokit-ref
File Storage
Storage strategy → /skill axiom-storage
Storage issues → /skill axiom-storage-diag
Storage management → /skill axiom-storage-management-ref
File protection → /skill axiom-file-protection-ref
tvOS Storage
tvOS data persistence → /skill axiom-tvos (CRITICAL: no persistent local storage on tvOS)
tvOS + CloudKit → /skill axiom-sqlitedata (recommended: SyncEngine as persistent store)
Automated Scanning
Core Data audit → Launch core-data-auditor agent or /axiom:audit core-data (migration risks, thread-confinement, N+1 queries, production data loss)
Codable audit → Launch codable-auditor agent or /axiom:audit codable (try? swallowing errors, JSONSerialization, date handling)
iCloud audit → Launch icloud-auditor agent or /axiom:audit icloud (entitlement checks, file coordination, CloudKit anti-patterns)
Storage audit → Launch storage-auditor agent or /axiom:audit storage (wrong file locations, missing backup exclusions, data loss risks)
Decision Tree
- SwiftData? → swiftdata, swiftdata-migration
- Core Data? → core-data, core-data-diag
- GRDB? → grdb
- SQLiteData? → sqlitedata, sqlitedata-ref
- ANY schema migration? → database-migration (ALWAYS — prevents data loss)
- Realm migration? → realm-migration-ref
- SwiftData vs SQLiteData? → sqlitedata-migration
- Cloud sync architecture? → cloud-sync
- CloudKit? → cloudkit-ref
- iCloud Drive? → icloud-drive-ref
- Cloud sync errors? → cloud-sync-diag
- Codable/JSON serialization? → codable
- File storage strategy? → storage, storage-diag, storage-management-ref
- File protection? → file-protection-ref
- Keychain / storing tokens, passwords, secrets securely? → keychain, keychain-diag, keychain-ref
- SecItem errors (errSecDuplicateItem, errSecItemNotFound, errSecInteractionNotAllowed)? → keychain-diag
- Encryption, signing, Secure Enclave, CryptoKit? → cryptokit, cryptokit-ref
- Quantum-secure cryptography, HPKE, ML-KEM? → cryptokit
- Want Core Data safety scan? → core-data-auditor (Agent)
- Want Codable anti-pattern scan? → codable-auditor (Agent)
- Want iCloud sync audit? → icloud-auditor (Agent)
- Want storage location audit? → storage-auditor (Agent)
- tvOS data persistence? → axiom-tvos (CRITICAL: no persistent local storage) + axiom-sqlitedata (CloudKit SyncEngine)
Anti-Rationalization
| Thought | Reality |
|---|---|
| "Just adding a column, no migration needed" | Schema changes without migration crash users. database-migration prevents data loss. |
| "I'll handle the migration manually" | Manual migrations miss edge cases. database-migration covers rollback and testing. |
| "Simple query, I don't need the skill" | Query patterns prevent N+1 and thread-safety issues. The skill has copy-paste solutions. |
| "CloudKit sync is straightforward" | CloudKit has 15+ failure modes. cloud-sync-diag diagnoses them systematically. |
| "I know Codable well enough" | Codable has silent data loss traps (try? swallows errors). codable skill prevents production bugs. |
| "I'll use local storage on tvOS" | tvOS has NO persistent local storage. System deletes Caches at any time. axiom-tvos explains the iCloud-first pattern. |
| "UserDefaults is fine for this token" | UserDefaults is unencrypted, backed up to iCloud, and visible to MDM profiles. One audit catches it. keychain stores tokens securely. |
| "I'll encrypt it myself with CommonCrypto" | CryptoKit replaced CommonCrypto's buffer-management nightmares with one-line APIs. cryptokit prevents misuse. |
Critical Pattern: Migrations
ALWAYS invoke /skill axiom-database-migration when adding/modifying database columns.
This prevents:
- "FOREIGN KEY constraint failed" errors
- "no such column" crashes
- Data loss from unsafe migrations
Example Invocations
User: "I need to add a column to my SwiftData model"
→ Invoke: /skill axiom-database-migration (critical - prevents data loss)
User: "How do I query SwiftData with complex filters?"
→ Invoke: /skill axiom-swiftdata
User: "CloudKit sync isn't working"
→ Invoke: /skill axiom-cloud-sync-diag
User: "Should I use SwiftData or SQLiteData?"
→ Invoke: /skill axiom-sqlitedata-migration
User: "Check my Core Data code for safety issues"
→ Invoke: core-data-auditor agent
User: "Scan for Codable anti-patterns before release"
→ Invoke: codable-auditor agent
User: "Audit my iCloud sync implementation"
→ Invoke: icloud-auditor agent
User: "Check if my files are stored in the right locations"
→ Invoke: storage-auditor agent
User: "How do I persist data on tvOS?"
→ Invoke: /skill axiom-tvos + /skill axiom-sqlitedata
User: "My tvOS app loses data between launches"
→ Invoke: /skill axiom-tvos
User: "How do I store an auth token securely?"
→ Invoke: /skill axiom-keychain
User: "errSecDuplicateItem but I checked and the item doesn't exist"
→ Invoke: /skill axiom-keychain-diag
User: "How do I encrypt data with AES in Swift?"
→ Invoke: /skill axiom-cryptokit
User: "I need to sign data with the Secure Enclave"
→ Invoke: /skill axiom-cryptokit
User: "What's ML-KEM and should I use it?"
→ Invoke: /skill axiom-cryptokit
How to use axiom-ios-data 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-data
Execute installation command
Execute the skills CLI command in your project's root directory to begin installation:
The skills CLI fetches axiom-ios-data 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-data. Access the skill through slash commands (e.g., /axiom-ios-data) 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
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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
4.8★★★★★51 reviews- ★★★★★Chaitanya Patil· Dec 28, 2024
Keeps context tight: axiom-ios-data is the kind of skill you can hand to a new teammate without a long onboarding doc.
- ★★★★★Yusuf Ghosh· Dec 20, 2024
axiom-ios-data is among the better-maintained entries we tried; worth keeping pinned for repeat workflows.
- ★★★★★Kofi Tandon· Dec 16, 2024
axiom-ios-data fits our agent workflows well — practical, well scoped, and easy to wire into existing repos.
- ★★★★★Meera Abbas· Dec 16, 2024
axiom-ios-data has been reliable in day-to-day use. Documentation quality is above average for community skills.
- ★★★★★Pratham Ware· Dec 8, 2024
axiom-ios-data fits our agent workflows well — practical, well scoped, and easy to wire into existing repos.
- ★★★★★Aditi Johnson· Dec 8, 2024
Keeps context tight: axiom-ios-data is the kind of skill you can hand to a new teammate without a long onboarding doc.
- ★★★★★Benjamin Rao· Nov 27, 2024
axiom-ios-data has been reliable in day-to-day use. Documentation quality is above average for community skills.
- ★★★★★Piyush G· Nov 19, 2024
axiom-ios-data has been reliable in day-to-day use. Documentation quality is above average for community skills.
- ★★★★★Aarav Shah· Nov 11, 2024
Solid pick for teams standardizing on skills: axiom-ios-data is focused, and the summary matches what you get after install.
- ★★★★★Yuki Diallo· Nov 7, 2024
Keeps context tight: axiom-ios-data is the kind of skill you can hand to a new teammate without a long onboarding doc.
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