liquid-glass-auditor

liquid-glass-auditor is an agent for Claude Code from CharlesWiltgen/Axiom. It costs 34 tokens per session (6,873 once invoked), scanned A, original, MIT.

A code-review agent for SwiftUI apps, focused on Liquid Glass, Apple’s newer translucent interface style in iOS 26 and later. It scans the codebase for places where this style could be added or improved.

In plain words
What is it for?
Use it to review SwiftUI views, toolbars, blur-effect migrations, tinting, and compatibility checks before adopting Liquid Glass.
Why use it?
It shows where Liquid Glass is missing, incorrectly configured, or likely to look visually muddled, including on older iOS versions.

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, 6 hooks shipped together

Good fit Use it to review SwiftUI views, toolbars, blur-effect migrations, tinting, and compatibility checks before adopting Liquid Glass.

Compare 6 agents from other repositories ↓
Install with agentmods
npx agentmods add agents/charleswiltgen/axiom/liquid-glass-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 · 1,235 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, 6 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 liquid-glass-auditor

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

Your own site · 80×15
<a href="https://agentmods.dev/agents/charleswiltgen/axiom/liquid-glass-auditor"><img src="https://agentmods.dev/badge/agents/charleswiltgen/axiom/liquid-glass-auditor.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 34 Only the description is in the session, so the agent can decide to use it. The body loads when it is invoked.
When invoked 6,873 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 $0.00034 $0.06873
Opus 5.5 $0.00014 $0.02749
Sonnet 5.5 $0.00007 $0.01375
Haiku 4.5 $0.00003 $0.00687

Measured 26d ago against content hash fb2517fdd0b7, method: parsed. Prices are Anthropic first-party input rates as of 2026-10-07, from the pricing page.

Security

Grade A, and why

liquid-glass-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 26d 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/liquid-glass-auditor.md · 371 lines

How it starts

The opening of the file, as written. The whole thing — 371 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Liquid Glass Auditor Agent

You are an expert at identifying Liquid Glass adoption opportunities AND adoption gaps — both surfaces where the iOS 26+ visual treatment isn't yet applied AND adoption-completeness issues like unstyled pre-26 fallbacks, wrong variant for content type (Regular vs Clear), nested glass causing visual muddiness, positionally placed primary actions, and an app-wide UIDesignRequiresCompatibility opt-out.

Note on Audit Framing

Unlike safety-oriented auditors, this agent surfaces adoption opportunities, not bugs. A codebase with no Liquid Glass adoption is not broken — it's pre-adoption. The Health Score reflects adoption progress (NOT ADOPTED → PARTIAL → ADOPTED), and "issues" are framed as opportunities with priority by impact, not danger.

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 Visual Treatment Architecture

Step 1: Identify Deployment Target and Availability Discipline

Establish the actual project, target, configuration and SDK before making deployment-specific recommendations. Discover both project.pbxproj and JSON5 project.xcproj at any depth, excluding dependency/cache directories. Read project/target settings and included xcconfig files, including conditional keys and array values. Label structural values "declared; effective value unverified"; a first match is not an evaluated target. For effective values, the owning workflow can obtain a matching authorized Xcode settings capture using axiom-build (skills/build-performance.md), "Project selection and effective settings". Do not launch Xcode under file-read-only scope. Apply target/phase file membership and synchronized-folder exception sets before assigning a source finding to a target; otherwise report it as a codebase match with target ownership unverified.

Read the full file on GitHub · 371 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. 26d ago Changed · +2 lines fb2517fdd0b7
  2. 1mo ago Changed · +8 lines · -129 tokens per session eda0425ab3b2
  3. 1mo ago Changed · +26 lines 8af1b64fd7aa
  4. 2mo ago First seen · 335 lines · 163 tokens per session scan A 021cc09a18ad

Subscribe to this mod's changes

liquid-glass-auditor is an agent published in the GitHub repository CharlesWiltgen/Axiom (1,235 stars, last pushed today), licensed MIT. It adds 34 tokens to every session and 6,873 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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