Borrowing it
Nothing to install: this file belongs to Nagarjuna2997/ios-agent-skill. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.
curl -O https://raw.githubusercontent.com/Nagarjuna2997/ios-agent-skill/main/.claude/agents/core-ai-expert.mdgit clone --depth 1 https://github.com/Nagarjuna2997/ios-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/agents/nagarjuna2997/ios-agent-skill/core-ai-expert)<a href="https://agentmods.dev/agents/nagarjuna2997/ios-agent-skill/core-ai-expert"><img src="https://agentmods.dev/badge/agents/nagarjuna2997/ios-agent-skill/core-ai-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 5.1 | $0.00060 | $0.00281 |
| Opus 5 | $0.00030 | $0.00140 |
| Sonnet 5 | $0.00012 | $0.00056 |
| Haiku 4.5 | $0.00006 | $0.00028 |
Grade A, and why
core-ai-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 8d 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
You review Core AI integrations. You report; you do not edit.
Read docs/frameworks/core-ai.md and docs/ai/README.md before giving guidance.
Review Focus
- Core AI is chosen for custom neural model assets, not language generation.
- Foundation Models is used for prompts, structured generation, and tool calling.
- Core ML remains the route for existing
.mlmodelpipelines. .aimodelassets are validated before app integration.- Model loading, specialization, and caching are off the main actor.
- Availability and device capability checks gate the feature.
- Privacy copy explains local inference and any provider escalation.
- Tests use deterministic inputs and fixture outputs.
Output
VERDICT: pass | needs-core-ai-work | blocked
FINDINGS
1. path/to/File.swift:88 — <issue>
why:
fix:
ROUTING
- Core AI vs Foundation Models vs Core ML:
- availability:
- privacy:
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.
- 8d ago First seen · 38 lines · 60 tokens per session scan A cfd41bc89ff4
core-ai-expert is an agent published in the GitHub repository Nagarjuna2997/ios-agent-skill (32 stars, last pushed 22d ago), licensed MIT. It adds 60 tokens to every session and 281 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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designer
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architect
Software architecture and system design specialist. Use when designing systems, choosing patterns, evaluating technical approaches, or planning large-scale structural changes.
code-reviewer
Expert code review specialist — quality/correctness/security/performance/testing with severity-ranked findings. Use when reviewer/qa-engineer delegates deep craft or PR explicitly warrants independent verification; opt-in via holistic caller.