native

Guidance for creating PyWry widgets in a native desktop window rather than a browser page, notebook, or embedded frame. The window uses a WebView while retaining operating-system features such as its title bar, file dialogs, notifications, and clipboard access.

In plain words
What is it for?
Use it to build standalone desktop interfaces with PyWry, including windows that need direct access to operating-system features.
Why use it?
It clarifies the runtime environment and prevents browser-specific or notebook-specific assumptions when building the interface.

Skill for Claude CodeCodex

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.

agentmods
npx agentmods add skills/deeleeramone/pywry/native
Any agent
npx skills add deeleeramone/PyWry --skill native
Clone the repo
git clone --depth 1 https://github.com/deeleeramone/PyWry

Made for: Claude Code, Codex.

Per session 0 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 1,549 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. Scan, not verified.
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 $0.00000 $0.01549
Opus 5 $0.00000 $0.00775
Sonnet 5 $0.00000 $0.00310
Haiku 4.5 $0.00000 $0.00155

Measured 2d ago against content hash 0590a051b405, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade A, and why

native 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.

pywry/pywry/mcp/skills/native/SKILL.md · 214 lines

How it starts

The opening of the file, as written. The whole thing — 214 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Native Window Mode

CRITICAL: This is a native desktop application using PyWry/WRY (Rust WebView). This is NOT a browser. This is NOT Jupyter. This is NOT an iframe.

What Native Mode IS

You're creating widgets for a native desktop window powered by:

  • PyWry (Python bindings)
  • WRY (Rust WebView library)
  • Tauri ecosystem (system-level access)

The widget runs in a standalone system window with:

  • Native title bar, minimize, maximize, close buttons
  • Direct OS integration (file dialogs, notifications, clipboard)
  • No browser chrome, no URL bar, no tabs
  • Full screen real estate for your content

What Native Mode is NOT

NOT a web browser - No DevTools (unless explicitly enabled), no extensions, no URL bar ❌ NOT Jupyter - No cell output area, no kernel, no notebook context ❌ NOT an iframe - No parent page, no sandboxing, no cross-origin restrictions

Architecture

┌───────────────────────────────────────────────────────────┐
│                      Native Window                        │
│  ┌─────────────────────────────────────────────────────┐  │
│  │               Title Bar (OS-native)                 │  │
│  ├─────────────────────────────────────────────────────┤  │
│  │                                                     │  │
│  │                 WebView (WRY/Tauri)                 │  │
│  │                                                     │  │
│  │    ┌─────────────────────────────────────────┐      │  │
│  │    │          Your Widget Content            │      │  │
│  │    │      (HTML/CSS/JS via PyWry API)        │      │  │
│  │    └─────────────────────────────────────────┘      │  │
│  │                                                     │  │
│  └─────────────────────────────────────────────────────┘  │
└───────────────────────────────────────────────────────────┘
              ↕ Python ↔ Rust ↔ OS integration

Key Capabilities

Window Control

  • Resize, minimize, maximize, close via native controls
  • Set window title dynamically
  • Window always stays on top (optional)
  • Multiple windows possible

Read the full file on GitHub · 214 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. 2d ago First seen · 214 lines · 0 tokens per session scan A 0590a051b405

Subscribe to this mod's changes

native is a skill published in the GitHub repository deeleeramone/PyWry (93 stars, last pushed 8d ago), licensed Apache-2.0. It costs nothing until one of its globs matches a file; then it loads 1,549 tokens. 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.

Related

Other skills, from other repositories

dashboard-design

Use this skill first when the user wants to design or plan a dashboard, especially Vizro dashboards. Enforces a 3-step workflow (requirements, layout, visualization) before implementation. Activate when the user asks to create, design, or plan a dashboard. For implementation, use the dashboard-build skill after…

mckinsey/vizro · 71 tokens

industry-chain

产业链下钻与不可替代性判定方法:以龙头为"需求入口"沿供应链逐层下钻(整机 / 龙头 → 部件 → 核心器件 → 材料 → 衬底与设备),用物理 / 材料约束(扩产周期、良率、认证周期、有无替代)当筛子找供给刚性的卡口;给每个标的贴不可替代性标签(techmoat / capacitymoat / both / 待补)并列证据;含"卡口越硬越贵"与预期差四问的校准。当任务涉及产业链位置、上下游、护城河、不可替代性、供给瓶颈、竞争格局时加载;单纯取数、估值计算、财报拆分等不涉及产业链结构的任务不要加载。只产出框架与证据表,不给投资动作建议。.

simonlin1212/Vibe-Research · 212 tokens

selecting-vizro-charts

Use this skill when choosing chart types, applying Plotly Express conventions, configuring colors, building KPI cards, or adding tables (AG Grid) to Vizro dashboards. Activate when the user asks which chart fits their data, needs custom chart functions, wants to set colors or palettes, is creating KPI metric cards, or…

mckinsey/vizro · 78 tokens

verify-changes

Verify a code change in this repo before committing or opening a PR. Use after editing collector (backend), web (frontend), shared package, or the Go agent — picks the minimal sufficient check set per touched area.

foru17/neko-master · 47 tokens

openai-docs

Use when the user asks how to build with OpenAI products or APIs and needs up-to-date official documentation with citations (for example: Codex, Responses API, Chat Completions, Apps SDK, Agents SDK, Realtime, model capabilities or limits); prioritize OpenAI docs MCP tools and restrict any fallback browsing to…

Soju06/codex-lb · 74 tokens

catalyst-risk

催化剂与风险的反证式写法:每个强结论必须先找反证;催化剂按"兑现型 / 预期型 / 周期型"分类并要求可验证的数据时点;风险按技术路线断层、客户集中、产能过剩与价格战、周期顶、预期透支(假便宜 PEG)、一致预期下修、治理与流动性、数据源冲突分类;裁决点的标准写法(什么数据出来会改变判断 + 下一个公开数据时点);知识档案旧结论的反证处理。当任务涉及风险、反证、催化剂、裁决点、预期兑现、什么会推翻结论时加载;单纯取数、估值计算、财报拆分等不需要反证框架的任务不要加载。只产出框架、概率与裁决点,不给投资动作建议。.

simonlin1212/Vibe-Research · 206 tokens