Ensure accessibility in UI components including semantic HTML, ARIA attributes, keyboard navigation, and WCAG 2.2 AA compliance.
日本語の概要は準備中です。原文の説明を表示しています。
Rules for integrating Tauri's native APIs in the frontend application.
インストールする前に、エージェントに与えられる指示の中身を確認できます。
tauri-specta to generate TypeScript types from Rust structs for type safety| Anti-Pattern | Why It Fails | Correct Approach |
|---|---|---|
| No command allowlist | All Rust functions exposed to frontend; attack surface maximized | Allowlist only specific commands needed by the frontend |
| Trusting frontend input | Malicious payloads can exploit Rust code | Validate and sanitize all IPC inputs on the Rust side |
| Synchronous I/O in commands | Blocks the Tauri event loop; UI freezes | Use async Rust for all I/O operations in command handlers |
| Missing TypeScript types | Runtime type mismatches between Rust and frontend | Use tauri-specta to generate TypeScript types from Rust structs |
| Large synchronous data transfers | IPC bottleneck causes UI stuttering | Stream or chunk large data; avoid transferring full datasets over IPC |
Before starting:
cat .claude/context/memory/learnings.md
After completing: Record any new patterns or exceptions discovered.
ASSUME INTERRUPTION: Your context may reset. If it's not in memory, it didn't happen.
まだレビューはありません。使ってみた感想をお寄せください。
概要と使いどころ
Ensure accessibility in UI components including semantic HTML, ARIA attributes, keyboard navigation, and WCAG 2.2 AA compliance.
日本語の概要は準備中です。原文の説明を表示しています。
Use when you want to improve response quality through meta-cognitive reasoning. Applies 15+ reasoning methods to reconsider and refine initial outputs.
日本語の概要は準備中です。原文の説明を表示しています。
N-round opposing-stance debates for trade-off analysis. Assigns pro/con roles to agents, runs structured debate rounds with quality scoring, and produces a moderator synthesis with confidence-rated recommendation. Generalizable to architecture, technology, security, and design decisions.
日本語の概要は準備中です。原文の説明を表示しています。
Force adversarial code review stance that eliminates confirmation bias — reviewer must find issues or re-analyze
日本語の概要は準備中です。原文の説明を表示しています。
Creates specialized AI agents on-demand when no existing agent matches a request. Use when the Router cannot find a suitable agent for a task. Enables self-evolution by generating persistent agents.
日本語の概要は準備中です。原文の説明を表示しています。
LLM-as-judge evaluation framework with 5-dimension rubric (accuracy, groundedness, coherence, completeness, helpfulness) for scoring AI-generated content quality with weighted composite scores and evidence citations
日本語の概要は準備中です。原文の説明を表示しています。