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/matthewye/opencode-toolbox/design-an-interfacenpx skills add MatthewYe/opencode-toolbox --skill design-an-interfacegit clone --depth 1 https://github.com/MatthewYe/opencode-toolboxWhat 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 | $0.00711 |
| Opus 5 | $0.00022 | $0.00356 |
| Sonnet 5 | $0.00009 | $0.00142 |
| Haiku 4.5 | $0.00004 | $0.00071 |
Grade A, and why
design-an-interface 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.
This is a copy
95% identical to api-shape-explorer — 2 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.
How it starts
The opening of the file, as written. The whole thing — 95 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Design an Interface
Based on "Design It Twice" from "A Philosophy of Software Design": your first idea is unlikely to be the best. Generate multiple radically different designs, then compare.
Workflow
1. Gather Requirements
Before designing, understand:
- What problem does this module solve?
- Who are the callers? (other modules, external users, tests)
- What are the key operations?
- Any constraints? (performance, compatibility, existing patterns)
- What should be hidden inside vs exposed?
Ask: "What does this module need to do? Who will use it?"
2. Generate Designs (Parallel Sub-Agents)
Spawn 3+ sub-agents simultaneously using Task tool. Each must produce a radically different approach.
Prompt template for each sub-agent:
Design an interface for: [module description]
Requirements: [gathered requirements]
Constraints for this design: [assign a different constraint to each agent]
- Agent 1: "Minimize method count - aim for 1-3 methods max"
- Agent 2: "Maximize flexibility - support many use cases"
- Agent 3: "Optimize for the most common case"
- Agent 4: "Take inspiration from [specific paradigm/library]"
Output format:
1. Interface signature (types/methods)
2. Usage example (how caller uses it)
3. What this design hides internally
4. Trade-offs of this approach
3. Present Designs
Show each design with:
- Interface signature - types, methods, params
- Usage examples - how callers actually use it in practice
- What it hides - complexity kept internal
Present designs sequentially so user can absorb each approach before comparison.
4. Compare Designs
After showing all designs, compare them on:
- Interface simplicity: fewer methods, simpler params
- General-purpose vs specialized: flexibility vs focus
- Implementation efficiency: does shape allow efficient internals?
- Depth: small interface hiding significant complexity (good) vs large interface with thin implementation (bad)
- Ease of correct use vs ease of misuse
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 · 95 lines · 43 tokens per session scan A a2596e9fa2d5
design-an-interface is a skill published in the GitHub repository MatthewYe/opencode-toolbox (5 stars, last pushed 2mo ago), licensed MIT. It adds 43 tokens to every session and 711 once invoked, about $0.0002 per session on Opus 5. A static security scan graded it A with 0 findings. It is 95% identical to api-shape-explorer, differing in 2 lines, and is treated as a copy.
Other skills, from other repositories
design-guide
Paperclip UI design system guide for building consistent, reusable frontend components. Use when creating new UI components, modifying existing ones, adding pages or features to the frontend, styling UI elements, or when you need to understand the design language and conventions. Covers: component creation, design…
gstack-openclaw-office-hours
Use when asked to brainstorm, evaluate whether an idea is worth building, run office hours, or think through a new product idea or design direction before any code is written.
accessibility
Consolidated accessibility skill entrypoint for WCAG 2.2, ARIA Authoring Practices, cognitive accessibility, Section 508, EN 301 549, design intent verification, and the Accessibility Planner workflow.
deck-course-module
暖纸背景 + Playfair, 左侧学习目标常驻, 含 MCQ 自测页.
desktop-principles
Desktop-specific UX principles - hover states, pointer precision, keyboard shortcuts, multi-window, focus management. Covers macOS, Windows, Linux, web desktop.
ios-hig-design
Design native iOS interfaces following Apple Human Interface Guidelines. Use when the user mentions "iPhone app", "iPad layout", "SwiftUI", "UIKit", "Dynamic Island", "safe areas", "HIG compliance", "SF Symbols", "haptic feedback", "iOS accessibility", "make my app feel native", or "follow Apple design guidelines".…