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 agentmods add skills/geoffjay/claude-plugins/gpui-patternsnpx skills add geoffjay/claude-plugins --skill gpui-patternsgit clone --depth 1 https://github.com/geoffjay/claude-pluginsWhat 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 | $0.00043 | $0.02972 |
| Opus 5 | $0.00022 | $0.01486 |
| Sonnet 5 | $0.00009 | $0.00594 |
| Haiku 4.5 | $0.00004 | $0.00297 |
Grade A, and why
gpui-patterns 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 2d 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 — 604 lines — stays where its author put it; the contents beside it link to each section on GitHub.
GPUI Patterns
Metadata
This skill provides comprehensive guidance on common GPUI patterns and best practices for building maintainable, performant applications.
Instructions
Component Composition Patterns
Basic Component Structure
use gpui::*;
// View component with state
struct MyView {
state: Model<MyState>,
_subscription: Subscription,
}
impl MyView {
fn new(state: Model<MyState>, cx: &mut ViewContext<Self>) -> Self {
let _subscription = cx.observe(&state, |_, _, cx| cx.notify());
Self { state, _subscription }
}
}
impl Render for MyView {
fn render(&mut self, cx: &mut ViewContext<Self>) -> impl IntoElement {
let state = self.state.read(cx);
div()
.flex()
.flex_col()
.child(format!("Value: {}", state.value))
}
}
Container/Presenter Pattern
Container (manages state and logic):
struct Container {
model: Model<AppState>,
_subscription: Subscription,
}
impl Container {
fn new(model: Model<AppState>, cx: &mut ViewContext<Self>) -> Self {
let _subscription = cx.observe(&model, |_, _, cx| cx.notify());
Self { model, _subscription }
}
}
impl Render for Container {
fn render(&mut self, cx: &mut ViewContext<Self>) -> impl IntoElement {
let state = self.model.read(cx);
// Pass data to presenter
Presenter::new(state.data.clone())
}
}
Presenter (pure rendering):
struct Presenter {
data: String,
}
impl Presenter {
fn new(data: String) -> Self {
Self { data }
}
}
impl Render for Presenter {
fn render(&mut self, cx: &mut ViewContext<Self>) -> impl IntoElement {
div().child(self.data.as_str())
}
}
Compound Components
// Parent component with shared context
pub struct Tabs {
items: Vec<TabItem>,
active_index: usize,
}
pub struct TabItem {
label: String,
content: Box<dyn Fn() -> AnyElement>,
}
impl Tabs {
pub fn new() -> Self {
Self {
items: Vec::new(),
active_index: 0,
}
}
pub fn add_tab(
mut self,
label: impl Into<String>,
content: impl Fn() -> AnyElement + 'static,
) -> Self {
self.items.push(TabItem {
label: label.into(),
content: Box::new(content),
});
self
}
fn set_active(&mut self, index: usize, cx: &mut ViewContext<Self>) {
self.active_index = index;
cx.notify();
}
}
impl Render for Tabs {
fn render(&mut self, cx: &mut ViewContext<Self>) -> impl IntoElement {
div()
.flex()
.flex_col()
.child(
// Tab headers
div()
.flex()
.children(
self.items.iter().enumerate().map(|(i, item)| {
tab_header(&item.label, i == self.active_index, || {
self.set_active(i, cx)
})
})
)
)
.child(
// Active tab content
(self.items[self.active_index].content)()
)
}
}
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.
- 2d ago First seen · 604 lines · 43 tokens per session scan A 597dcfc627d1
gpui-patterns is a skill published in the GitHub repository geoffjay/claude-plugins (8 stars, last pushed 10mo ago), licensed MIT. It adds 43 tokens to every session and 2,972 once invoked, about $0.0002 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.
Other skills, from other repositories
systematic-debugging
Use when encountering any bug, test failure, or unexpected behavior, before proposing fixes.
brainstorming
You MUST use this before any creative work - creating features, building components, adding functionality, or modifying behavior. Explores user intent, requirements and design before implementation.
auto-perf-optimize
Run agent-driven VS Code performance or memory investigations. Use when asked to launch Code OSS, automate a VS Code scenario, run the Chat memory smoke runner, capture renderer heap snapshots, take workflow screenshots, compare run summaries, or drive a repeatable scenario before heap-snapshot analysis.
chat-perf
Run chat perf benchmarks and memory leak checks against the local dev build or any published VS Code version. Use when investigating chat rendering regressions, validating perf-sensitive changes to chat UI, or checking for memory leaks in the chat response pipeline.
chat-pet-sprite-creation
Use when creating or changing VS Code chat pet sprite art, sprite sheets, state animations, eye treatments, Stable/Insiders variants, or pet transitions under src/vs/workbench/contrib/chat/browser/widget/media/chatPet.
cpu-profile-analysis
Analyze V8/Chrome CPU profiles (.cpuprofile) and DevTools trace files (Trace-.json). Use when: profiling performance, investigating slow functions, comparing code paths, finding bottlenecks, analyzing timeToRequest, understanding call trees from sampling profiler data, analyzing layout/paint/rendering, investigating…