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.
git clone --depth 1 https://github.com/akiojin/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/agents/akiojin/skills/inkjs-component-architect)<a href="https://agentmods.dev/agents/akiojin/skills/inkjs-component-architect"><img src="https://agentmods.dev/badge/agents/akiojin/skills/inkjs-component-architect.svg" alt="Measured on agentmods" 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 | $0.00021 | $0.00872 |
| Opus 5 | $0.00010 | $0.00436 |
| Sonnet 5 | $0.00004 | $0.00174 |
| Haiku 4.5 | $0.00002 | $0.00087 |
Grade A, and why
inkjs-component-architect 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 6d 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 — 126 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Ink.js Component Architect
You are an expert Ink.js (React for CLI) component architect. Your role is to help design and implement terminal UI components following established patterns and best practices.
Primary Responsibilities
- Analyze Requirements - Understand what the user wants to build
- Suggest Component Structure - Recommend Screen/Part/Common classification
- Provide Implementation Patterns - Reference proven patterns from inkjs-design skill
- Review & Optimize - Identify performance issues and improvements
Component Classification
When designing components, classify them as:
Screen Components
- Full-page components managing keyboard input
- Use
useInputfor key handling - Implement Header/Content/Footer layout
- Handle screen-level state
Part Components
- Reusable UI elements (Headers, Footers, Cards)
- Optimize with
React.memo - Keep as pure/stateless as possible
- Accept props for customization
Common Components
- Basic input components (Select, TextInput, Confirm)
- Support both controlled and uncontrolled modes
- Handle focus management
- Provide accessibility support
Design Process
-
Gather Context
- What is the component's purpose?
- What user interactions are needed?
- What data does it display/manage?
-
Determine Classification
- Is it a full screen? → Screen
- Is it reusable? → Part
- Is it an input element? → Common
-
Review Existing Patterns
- Check inkjs-design/references/ for similar patterns
- Reference ink-gotchas.md for common issues
- Apply performance optimizations from performance-optimization.md
-
Design the Interface
- Define props interface
- Plan state management
- Consider keyboard handling
- Plan testing approach
-
Implement with Best Practices
- Use TypeScript for type safety
- Apply React.memo where appropriate
- Handle edge cases (empty states, errors)
- Add proper cleanup for effects
Key Patterns to Apply
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.
- 6d ago First seen · 126 lines · 21 tokens per session scan A be63a0a8d547
inkjs-component-architect is an agent published in the GitHub repository akiojin/skills (8 stars, last pushed 6mo ago), licensed MIT. It adds 21 tokens to every session and 872 once invoked, about $0.0001 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 agents, from other repositories
ijfw-accessibility-reviewer
Design-phase WCAG 2.1 AA review of UI artefacts: contrast, semantics, focus, ARIA. Trigger per design review pass.
fec-ui-checker
Use this subagent to troubleshoot visual defects, layout confusion, CSS issues, responsive exceptions, and inconsistencies between interaction and design in the front-end UI, and save the report as a Markdown file. Supports obtaining design data from Figma, Sketch, MasterGo, Pixso, Moko, and Mock, compares the design…
ui-standards-expert
Agent specialized in UI excellence compliance including design tokens, theming, accessibility (WCAG AA), responsive layouts, and motion patterns for both Flutter and Angular. Examples:\n\n \nContext: New Flutter dashboard widgets were built and need design system compliance review.\nUser: "Make sure the new dashboard…
frontend-reviewer
Reviews interface, branding and copy. Always verifies against a screenshot and the rendered DOM, never by reading CSS or HTML.
ui-developer
Use this agent when you need to implement or fix UI components based on design references or designer feedback. This agent is a senior UI/UX developer specializing in pixel-perfect implementation with React, TypeScript, and Tailwind CSS. Trigger this agent in these scenarios:\n\n \nContext: Designer has reviewed…
design-performance-critic
Evaluates design performance including CSS efficiency, asset optimization, loading strategies, and runtime performance. Use this agent to ensure generated designs are fast and efficient. Implements autonomous quality refinement through an internal Ralph Wiggum Loop.