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.
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 skills add CharlesWiltgen/Axiom --skill axiom-audit-liquid-glassgit clone --depth 1 https://github.com/CharlesWiltgen/AxiomWrote 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/charleswiltgen/axiom/axiom-audit-liquid-glass)<a href="https://agentmods.dev/skills/charleswiltgen/axiom/axiom-audit-liquid-glass"><img src="https://agentmods.dev/badge/skills/charleswiltgen/axiom/axiom-audit-liquid-glass/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.
<a href="https://agentmods.dev/skills/charleswiltgen/axiom/axiom-audit-liquid-glass"><img src="https://agentmods.dev/badge/skills/charleswiltgen/axiom/axiom-audit-liquid-glass.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector warn
SkillSpector: 1 finding, up to medium
These are SkillSpector’s own severities. On a checked sample its high-severity flags on skills were ~96% false positives — a documented command, a public API, a “never do X” rule — so we show them as a caution to read, not a verdict. Why →
- medium Rogue Agent · line 31 Skill establishes unauthorized persistence across sessions via cron jobs, startup scripts, or state files. Session persistence allows an attacker to maintain access beyond the current interaction.Fix: Remove any persistence mechanisms (cron jobs, startup scripts, state files). Skills should not maintain state across sessions without explicit user consent.
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 | $0.00032 | $0.06836 |
| Opus 5.5 | $0.00013 | $0.02734 |
| Sonnet 5.5 | $0.00006 | $0.01367 |
| Haiku 4.5 | $0.00003 | $0.00684 |
Grade A, and why
axiom-audit-liquid-glass 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 23d 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.
How it starts
The opening of the file, as written. The whole thing — 361 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.
What ships with it
1 file 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.
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.
- 23d ago Changed · +2 lines 174cf32ea457
- 1mo ago Changed · +20 lines 7eb1a83588bc
- 1mo ago Changed · +26 lines fbc124737126
- 1mo ago First seen · 313 lines · 32 tokens per session scan A af92421e3866
axiom-audit-liquid-glass is a skill published in the GitHub repository CharlesWiltgen/Axiom (1,231 stars, last pushed yesterday), licensed MIT. It adds 32 tokens to every session and 6,836 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 2026-09-06.
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