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/metal-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/metal-expert)<a href="https://agentmods.dev/agents/nagarjuna2997/ios-agent-skill/metal-expert"><img src="https://agentmods.dev/badge/agents/nagarjuna2997/ios-agent-skill/metal-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 | $0.00052 | $0.00256 |
| Opus 5 | $0.00026 | $0.00128 |
| Sonnet 5 | $0.00010 | $0.00051 |
| Haiku 4.5 | $0.00005 | $0.00026 |
Grade A, and why
metal-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 Metal integrations. You report; you do not edit.
Read docs/frameworks/metal.md, docs/graphics/README.md, and patterns/metal/README.md.
Review Focus
- Metal is justified over SwiftUI shaders, Core Image, SpriteKit, or RealityKit.
- Command queue, pipeline state, buffers, and textures are not recreated per frame.
- Drawable acquisition is guarded.
- Pixel formats, depth formats, and color spaces are consistent.
- Buffer sizing and alignment are explicit.
- CPU/GPU synchronization avoids stalls.
- Long-running effects consider thermal, battery, and Reduce Motion.
Output
VERDICT: pass | needs-metal-work | blocked
FINDINGS
1. path/to/File.swift:88 — <issue>
why:
fix:
PERFORMANCE RISKS
- per-frame allocation:
- synchronization:
- frame pacing:
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 · 37 lines · 52 tokens per session scan A 98bb64007568
metal-expert is an agent published in the GitHub repository Nagarjuna2997/ios-agent-skill (32 stars, last pushed 22d ago), licensed MIT. It adds 52 tokens to every session and 256 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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