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.
npx agentmods add skills/avdlee/core-data-agent-skill/core-data-expertnpx skills add AvdLee/Core-Data-Agent-Skill --skill core-data-expertgit clone --depth 1 https://github.com/AvdLee/Core-Data-Agent-SkillWrote 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/skills/avdlee/core-data-agent-skill/core-data-expert)<a href="https://agentmods.dev/skills/avdlee/core-data-agent-skill/core-data-expert"><img src="https://agentmods.dev/badge/skills/avdlee/core-data-agent-skill/core-data-expert.svg" alt="Measured on agentmods" 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 | $0.00058 | $0.01082 |
| Opus 5 | $0.00029 | $0.00541 |
| Sonnet 5 | $0.00012 | $0.00216 |
| Haiku 4.5 | $0.00006 | $0.00108 |
Grade A, and why
core-data-expert 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 4d 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.
Copies of this mod
1 near-identical copy found in the catalogue:
- core-data-expert — 94% identical, 4 lines differ
How it starts
The opening of the file, as written. The whole thing — 83 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Core Data Expert
Fast, production-oriented guidance for building correct, performant Core Data stacks and fixing common crashes.
Agent behavior contract (follow these rules)
- Determine OS/deployment target when advice depends on availability (iOS 14+/17+ features, etc.).
- Identify the context type before proposing fixes: view context (UI) vs background context (heavy work).
- Recommend
NSManagedObjectIDfor cross-context/cross-task communication; never passNSManagedObjectinstances across contexts. - Prefer lightweight migration when possible; use staged migration (iOS 17+) for complex changes.
- When recommending batch operations, verify persistent history tracking is enabled (often required for UI updates).
- For CloudKit integration, remind developers that Production schema is immutable.
- Reference WWDC/external resources sparingly; prefer this skill’s
references/.
First 60 seconds (triage template)
- Clarify the goal: setup, bugfix, migration, performance, CloudKit?
- Collect minimal facts:
- platform + deployment target
- store type (SQLite / in-memory) and whether CloudKit is enabled
- context involved (view vs background) and whether Swift Concurrency is in use
- exact error message + stack trace/logs
- Branch immediately:
- threading/crash → focus on context confinement +
NSManagedObjectIDhandoff - migration error → identify model versions + migration strategy
- batch ops not updating UI → persistent history tracking + merge pipeline
- threading/crash → focus on context confinement +
Routing map (pick the right reference fast)
- Stack setup / merge policies / contexts →
references/stack-setup.md - Saving patterns →
references/saving.md - Fetch requests / list updates / aggregates →
references/fetch-requests.md - Traditional threading (perform/performAndWait, object IDs) →
references/threading.md - Swift Concurrency (async/await, actors, Sendable, DAOs) →
references/concurrency.md - Batch insert/delete/update →
references/batch-operations.md - Persistent history tracking + “batch ops not updating UI” →
references/persistent-history.md - Model configuration (constraints, validation, derived/composite, transformables) →
references/model-configuration.md - Schema migration (lightweight/staged/deferred) →
references/migration.md - CloudKit integration & debugging →
references/cloudkit-integration.md - Performance profiling & memory →
references/performance.md - Testing patterns →
references/testing.md - Terminology →
references/glossary.md
What ships with it
15 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
- references/_index.md 4.0 KB
- references/batch-operations.md 14 KB
- references/cloudkit-integration.md 6.2 KB
- references/concurrency.md 13 KB
- references/fetch-requests.md 17 KB
- references/glossary.md 5.6 KB
- references/migration.md 11 KB
- references/model-configuration.md 14 KB
- references/performance.md 6.2 KB
- references/persistent-history.md 17 KB
- references/project-audit.md 2.1 KB
- references/saving.md 14 KB
- references/stack-setup.md 17 KB
- references/testing.md 7.8 KB
- references/threading.md 14 KB
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.
- 4d ago First seen · 83 lines · 58 tokens per session scan A 74cac8c2a868
core-data-expert is a skill published in the GitHub repository AvdLee/Core-Data-Agent-Skill (303 stars, last pushed 28d ago), licensed MIT. It adds 58 tokens to every session and 1,082 once invoked, about $0.0003 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 2026-08-30.
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