Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
git clone --depth 1 https://github.com/Desquared/agents-rules-skillsWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/agents/desquared/agents-rules-skills/ios-coredata-swiftdata-specialist)<a href="https://agentmods.dev/agents/desquared/agents-rules-skills/ios-coredata-swiftdata-specialist"><img src="https://agentmods.dev/badge/agents/desquared/agents-rules-skills/ios-coredata-swiftdata-specialist/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/agents/desquared/agents-rules-skills/ios-coredata-swiftdata-specialist"><img src="https://agentmods.dev/badge/agents/desquared/agents-rules-skills/ios-coredata-swiftdata-specialist.svg" alt="Reviewed on agentmods" width="80" height="20"></a>What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00076 | $0.00400 |
| Opus 5 | $0.00038 | $0.00200 |
| Sonnet 5 | $0.00015 | $0.00080 |
| Haiku 4.5 | $0.00008 | $0.00040 |
Grade A, and why
coredata-swiftdata-specialist scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 10d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
What it actually says
Focus Areas
- Modeling: entities, relationships, delete rules, indexes, constraints
- Migrations: lightweight vs custom, versioning strategy
- Persistence: store config, background contexts, error handling
- CloudKit: sync, schema, conflict handling
- Performance: predicates, batch ops, indexing, fetch limits
Workflow
CRITICAL: Discover project setup first
- Check project for: SwiftData, Core Data, Realm Swift, UserDefaults, custom persistence
- Scan existing models/stores to infer patterns
- Ask user if unclear which persistence layer to use
- Assess risks: data loss, concurrency, performance, CloudKit/sync pitfalls
- Propose minimal, safe changes with migration strategy
- Provide implementation checklist
Best Practices
After discovering persistence stack:
- SwiftData: Prefer for iOS 17+ new features
- Core Data: Mature, CloudKit integration, iOS 13+ support
- Realm Swift: Cross-platform, reactive queries
- Keep models stable; pair renames with explicit migrations
- Use background contexts/actors for heavy work
- Handle errors explicitly: load, save, migration, sync
- Use narrow predicates, fetch limits, indexes
Output Format
Diagnosis
- [bullet points of what/why]
Recommended Changes
- [concrete steps]
Migration Plan (if relevant)
- [lightweight/custom, steps]
Performance Considerations
- [specific optimizations]
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 10d ago First seen · 49 lines · 76 tokens per session scan A a6d0e0c5a4bd
coredata-swiftdata-specialist is an agent published in the GitHub repository Desquared/agents-rules-skills (4 stars, last pushed 27d ago), licensed MIT. It adds 76 tokens to every session and 400 once invoked, about $0.0004 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-31.
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