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 vosslab/vosslab-skills --skill glass-expertgit clone --depth 1 https://github.com/vosslab/vosslab-skillsWrote 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/vosslab/vosslab-skills/glass-expert)<a href="https://agentmods.dev/skills/vosslab/vosslab-skills/glass-expert"><img src="https://agentmods.dev/badge/skills/vosslab/vosslab-skills/glass-expert/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/vosslab/vosslab-skills/glass-expert"><img src="https://agentmods.dev/badge/skills/vosslab/vosslab-skills/glass-expert.svg" alt="Reviewed on agentmods" width="80" 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 | $0.00059 | $0.01282 |
| Opus 5 | $0.00030 | $0.00641 |
| Sonnet 5 | $0.00012 | $0.00256 |
| Haiku 4.5 | $0.00006 | $0.00128 |
Grade A, and why
glass-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 10d 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 — 100 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Liquid Glass Expert
Overview
Use this skill to get Liquid Glass demonstrably correct in SwiftUI apps on macOS 26+ (and iOS 26). Glass is a backdrop-sampling material: it blurs, refracts, and tints whatever renders behind it, adapts its own opacity to the backdrop, and guarantees no minimum text contrast. Most failures are silent -- the code compiles and a capture looks plausible while the effect is absent or illegible. This skill turns "add glass" into layered implementation plus visual evidence: a correct sampling path, colors that stay legible, and captures that prove the effect is live.
SwiftUI is the implementation layer; treat AppKit as a legacy escape hatch reached only when SwiftUI cannot yet express the behavior.
When to use
- Implement custom glass (
.glassEffect,GlassEffectContainer, morphing). - Debug glass that renders flat, gray, invisible, or unexpectedly opaque.
- Prove with captures that glass is live before accepting work as done.
- Decide which surfaces should be glass and which stay stable content.
- Guarantee text contrast over glass across arbitrary backdrops.
- Review or harden an existing app's glass adoption.
When not to use
- Web glassmorphism (CSS
backdrop-filter); this skill is SwiftUI-specific. - App-icon glass (Icon Composer layered icons); a different pipeline.
- General SwiftUI layout or state questions with no glass involvement.
Workflow
- Frame the project shape. When invoked on a target app, decide greenfield
versus improve-existing and follow the matching workflow in
references/project_workflow.md. Skip this step for a one-off question with no target repo. - Classify the task (placement, implementation, verification, debugging, or
contrast) using
references/task_selection.md. - For an observed problem ("glass looks flat", "text unreadable"), start at
the symptom router
references/topic_index.md. - Open the one matching reference from the routing table below.
- Implement with the seed views in
assets/(seereferences/component_seeds.md) when the surface carries text or needs accessibility fallbacks. - Prove the result with the evidence protocol in
references/testing_and_oracles.md, using the capture and comparison tools inscripts/. Ship only on visual evidence, never on compiling code.
What ships with it
18 files 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.
- agents/openai.yaml 302 B
- assets/GlassEvidenceView.swift 1.4 KB
- assets/GlassSurface.swift 1.7 KB
- references/api_quick_reference.md 3.6 KB
- references/capture_paths.md 2.1 KB
- references/color_and_contrast.md 2.8 KB
- references/component_seeds.md 2.0 KB
- references/design_placement.md 3.0 KB
- references/layers_and_sampling.md 2.2 KB
- references/project_workflow.md 3.2 KB
- references/skill_maintenance.md 4.4 KB
- references/task_selection.md 2.7 KB
- references/testing_and_oracles.md 3.4 KB
- references/toolbar_best_practices.md 3.5 KB
- references/topic_index.md 3.6 KB
- scripts/capture_glass_evidence.sh 1.3 KB runs code
- scripts/compare_captures.py 3.9 KB runs code
- scripts/list_window_ids.swift 1.3 KB
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.
- 10d ago First seen · 100 lines · 59 tokens per session scan A af335f562ef1
glass-expert is a skill published in the GitHub repository vosslab/vosslab-skills (2 stars, last pushed 14d ago), licensed MIT. It adds 59 tokens to every session and 1,282 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 2026-08-31.
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