core-data-auditor

core-data-auditor is an agent for Claude Code from CharlesWiltgen/Axiom. It costs 28 tokens per session (3,260 once invoked), scanned A, original, MIT.

A Core Data code reviewer for Apple's framework for storing application data in structured local databases.

In plain words
What is it for?
It is for inspecting the Core Data stack and related Swift and data-model files for five listed safety and performance problems.
Why use it?
It helps uncover migration problems, incorrect thread use, repeated database queries, data-loss risks, and slow data access before they affect users.

Agent for Claude Code

Written for Claude Code: background in frontmatter. Also seen: model in frontmatter; mentions .claude-plugin.

Part of the axiom plugin — 27 skills, 17 commands, 42 agents, 5 hooks shipped together

Good fit It is for inspecting the Core Data stack and related Swift and data-model files for five listed safety and performance problems.

Compare 6 agents from other repositories ↓
Install with agentmods
npx agentmods add agents/charleswiltgen/axiom/core-data-auditor
About the project

Axiom is a toolkit of instructions, agents, commands, and development tools that give coding assistants specialized guidance for Apple operating-system development. It covers Swift, SwiftUI, interface design, data, concurrency, performance, networking, accessibility, logging, crash analysis, simulator testing, and profiling for iOS, iPadOS, watchOS, and tvOS. The catalogue contains 42 agents, 16 commands, and one plugin from this toolkit.

CharlesWiltgen/Axiom · 1,223 stars · on GitHub · charleswiltgen.github.io

Install

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.

Clone the repo
git clone --depth 1 https://github.com/CharlesWiltgen/Axiom

Made for: Claude Code.

Or install axiom, the plugin that ships this one along with the rest of its 27 skills, 17 commands, 42 agents, 5 hooks.

Wrote 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.

agentmods badge for core-data-auditor

README.md
[![agentmods](https://agentmods.dev/badge/agents/charleswiltgen/axiom/core-data-auditor/github.svg)](https://agentmods.dev/agents/charleswiltgen/axiom/core-data-auditor)
Your own site
<a href="https://agentmods.dev/agents/charleswiltgen/axiom/core-data-auditor"><img src="https://agentmods.dev/badge/agents/charleswiltgen/axiom/core-data-auditor/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.

agentmods 80×15 button for core-data-auditor

Your own site · 80×15
<a href="https://agentmods.dev/agents/charleswiltgen/axiom/core-data-auditor"><img src="https://agentmods.dev/badge/agents/charleswiltgen/axiom/core-data-auditor.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 28 Only the description is in the session, so the agent can decide to use it. The body loads when it is invoked.
When invoked 3,260 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe.
Origin original No closer match found in the catalogue.
Token cost

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.

ModelPer sessionOnce invoked
Fable 5.1 $0.00028 $0.03260
Opus 5.5 $0.00011 $0.01304
Sonnet 5.5 $0.00006 $0.00652
Haiku 4.5 $0.00003 $0.00326

Measured 1mo ago against content hash 7f38246405a3, method: parsed. Prices are Anthropic first-party input rates as of 2026-10-07, from the pricing page.

Security

Grade A, and why

core-data-auditor 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 1mo 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.

.claude-plugin/plugins/axiom/agents/core-data-auditor.md · 298 lines

How it starts

The opening of the file, as written. The whole thing — 298 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Core Data Auditor Agent

You are an expert at detecting Core Data safety violations — both known anti-patterns AND missing/incomplete patterns that cause production crashes, permanent data loss, and performance degradation.

Tool Use Is Mandatory

Run every Glob, Grep, and Read this prompt lists. Do not reason from training data instead of scanning.

  • Run each Grep pattern as written; do not collapse them into one mega-regex.
  • Run the Read verifications each section calls for.
  • "Build a mental model" / "map the architecture" means with tool output in hand, not from memory.

Files to Exclude

Skip: *Tests.swift, *Previews.swift, */Pods/*, */Carthage/*, */.build/*, */DerivedData/*, */scratch/*, */docs/*, */.claude/*, */.claude-plugin/*

Phase 1: Map Core Data Architecture

Step 1: Identify Core Data Stack

Glob: **/*.swift, **/*.xcdatamodeld (excluding test/vendor paths)
Grep for:
  - `NSPersistentContainer` — Modern stack (iOS 10+)
  - `NSPersistentCloudKitContainer` — CloudKit-synced stack
  - `NSPersistentStoreCoordinator` — Legacy stack setup
  - `NSManagedObjectModel` — Model loading
  - `NSPersistentStoreDescription` — Store configuration

Step 2: Identify Context Usage Patterns

Grep for:
  - `viewContext` — Main thread context
  - `newBackgroundContext` — Background context creation
  - `perform {`, `performAndWait` — Safe context access
  - `NSManagedObjectContext(concurrencyType:` — Direct context creation
  - `.automaticallyMergesChangesFromParent` — Cross-context merge
  - `.mergePolicy` — Conflict resolution

Step 3: Map Persistence Patterns

Read 2-3 key persistence files (stack setup, a data manager, a model class) to understand:

  • How many contexts exist and what roles they play
  • Whether background work uses background contexts or misuses viewContext
  • What the migration strategy is (automatic, custom, none)
  • How entities relate to each other (complexity of object graph)

Output

Write a brief Core Data Architecture Map (5-10 lines) summarizing:

  • Stack type (modern container vs legacy coordinator, CloudKit vs local)
  • Context strategy (single viewContext, viewContext + background, per-operation)
  • Migration configuration (automatic lightweight, custom mapping, unconfigured)
  • Entity/relationship complexity

Read the full file on GitHub · 298 lines

Changes

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.

  1. 1mo ago Changed 7f38246405a3
  2. 1mo ago Changed · +8 lines · -233 tokens per session 90d7ebc9e6ea
  3. 1mo ago First seen · 290 lines · 261 tokens per session scan A 1f70c3f6a451

Subscribe to this mod's changes

core-data-auditor is an agent published in the GitHub repository CharlesWiltgen/Axiom (1,223 stars, last pushed today), licensed MIT. It adds 28 tokens to every session and 3,260 once invoked, about $0.0001 per session on Opus 5.5. 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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