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 vinsonconsulting/claude-skill-foundry --skill ratatuigit clone --depth 1 https://github.com/vinsonconsulting/claude-skill-foundryWrote 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/vinsonconsulting/claude-skill-foundry/ratatui)<a href="https://agentmods.dev/skills/vinsonconsulting/claude-skill-foundry/ratatui"><img src="https://agentmods.dev/badge/skills/vinsonconsulting/claude-skill-foundry/ratatui/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/vinsonconsulting/claude-skill-foundry/ratatui"><img src="https://agentmods.dev/badge/skills/vinsonconsulting/claude-skill-foundry/ratatui.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 | $0.00244 | $0.03939 |
| Opus 5 | $0.00122 | $0.01969 |
| Sonnet 5 | $0.00049 | $0.00788 |
| Haiku 4.5 | $0.00024 | $0.00394 |
Grade A, and why
ratatui 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 9d 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 — 323 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Ratatui
Write current, compiling Ratatui code (pinned to 0.30.x, Rust 2024) and refuse the
stale tui-rs patterns the model remembers from training. The body is the load-bearing
20%: one mental model and one verified example per concept. Everything enumerable —
the full widget catalog, every constraint, the streaming model, testing, migration —
lives in references/. Open the matching reference before writing nontrivial code in
that area.
Mental model
Ratatui is immediate mode: there are no retained widget objects. Every frame you
build the whole UI from your own application state and throw it away. A render loop
runs terminal.draw(|frame| …); inside, you slice the area into rectangles and draw
widgets into them. Ratatui keeps two Buffers and diffs them, writing only the
changed cells to the terminal — so redrawing the entire screen every frame is cheap and
correct. You own the loop: read an event, update state, draw, repeat.
Four nouns carry everything:
- Terminal — owns the backend (crossterm by default) and the double buffers; gives you a
Frame. - Frame — one frame's drawing surface;
frame.area()is the fullRect,frame.render_widget(w, rect)draws. - Buffer — the grid of styled cells widgets write into. Dimensions are
u16(max 65,535 per side). - Rect — an
x/y/width/heightregion inu16. Layout is just splitting oneRectinto moreRects.
Lifecycle: never hand-roll the terminal
Ratatui sets up raw mode, the alternate screen, and a panic hook for you. Do not call
enable_raw_mode, EnterAlternateScreen, or any manual teardown — if you do, a panic
or early return leaves the user's terminal wrecked.
fn main() -> color_eyre::Result<()> {
color_eyre::install()?; // BEFORE init(): ratatui's panic hook must be outermost,
let terminal = ratatui::init(); // so it restores the screen before color-eyre prints.
let result = App::default().run(terminal);
ratatui::restore(); // always runs; restore BEFORE surfacing the error
result
}
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.
- card-review.md 907 B
- card.authored.yaml 450 B
- card.json 4.9 KB
- evals/evals.json 4.0 KB
- evals/functional/graders.py 7.0 KB runs code
- evals/functional/run_grader.py 1.8 KB runs code
- evals/functional/tasks.json 3.7 KB
- evals/triggering.jsonl 3.3 KB
- README.md 5.1 KB
- references/agent-ui.md 5.8 KB
- references/ecosystem.md 3.5 KB
- references/layout.md 4.5 KB
- references/testing.md 3.0 KB
- references/text-and-unicode.md 3.3 KB
- references/versioning.md 3.8 KB
- references/widgets.md 6.3 KB
- scan.json 2.9 KB
- skill-card.md 5.7 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.
- 9d ago First seen · 323 lines · 244 tokens per session scan A 62c88a312984
ratatui is a skill published in the GitHub repository vinsonconsulting/claude-skill-foundry (1 stars, last pushed 1mo ago), licensed Apache-2.0. It adds 244 tokens to every session and 3,939 once invoked, about $0.0012 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
tauri-expert
Expert in Tauri framework, Rust backend, web frontend integration, and lightweight desktop applications. Use when the user mentions desktop, Rust, web, cross platform, or performance, or when the task involves Tauri Architecture, Tauri vs Electron, Core Components, or Security Features.
webassembly-expert
Create production-ready WebAssembly modules for web and server environments with optimal performance and seamless JavaScript integration. Use when the user mentions WebAssembly or Wasm, WASI, compiling Rust/C/C++ to the browser, Emscripten, wasmtime, or JavaScript-to-Wasm interop for performance-critical code.
dare-rust-leptos
Guia DARE para desenvolvimento Leptos (Rust + WASM) — decisão CSR vs Fullstack, idioms 0.7, antipatterns, tipos compartilhados server+WASM com cfgattr, workspace misto WASM+nativo, templates de tasks.
wasm-expert
WebAssembly expert for WASI, component model, Rust/C compilation, and browser integration.
rust-patterns
Rust: ownership, lifetimes, async (Tokio), Result/anyhow/thiserror, traits, unsafe. Triggers: Rust, borrow checker, lifetime, Tokio, cargo, trait, impl, Result, unsafe, clippy.
attributed-string
AttributedString patterns for rich text formatting, alignment, selection, and SwiftUI integration. Use when working with styled text, text editing, or AttributedString APIs.