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。
Ask the minimum clarifying questions before implementation when requirements are ambiguous or missing crucial details
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。
Identify which aspects are unclear or missing:
Do NOT ask about things you can determine by reading existing code and conventions.
Categorize each candidate question:
| Type | Ask or Decide? |
|---|---|
| Scope boundary (what to include) | Ask |
| Non-functional requirement (perf/security target) | Ask |
| Acceptance criteria | Ask |
| Implementation approach | Decide yourself |
| Code style / naming | Decide yourself (follow existing patterns) |
| Nice-to-have polish | Decide yourself (proceed with sensible default) |
For each blocking question:
Format:
I'll [proceed with X default assumption]. Quick questions before I start:
1. [Specific question]? (default: [assumption])
2. [Specific question]? (default: [assumption])
</execution_process>
<best_practices>
</best_practices> </instructions>
<examples> <usage_example> **Example — Underspecified feature request:**User: "Add a search feature to the dashboard"
Good response:
I'll implement client-side search with debouncing and case-insensitive matching. Quick questions before I start:
1. Should search cover all columns or just the name/title column? (default: name/title only)
2. Should results filter in place or open in a new panel? (default: filter in place)
Bad response:
Before I start, I need to know:
1. What search algorithm should I use?
2. Should it be case sensitive?
3. What debounce delay?
4. Should I use a library?
5. How many results to show?
</usage_example> </examples>
| Anti-Pattern | Why It Fails | Correct Approach |
|---|---|---|
| Asking 5+ questions before starting | Paralyzes user; feels like interrogation | Triage to max 3 blocking questions; decide the rest |
| Asking about implementation approach | That is the agent's job, not the user's | Ask about scope/constraints/acceptance criteria only |
| Questions without defaults | User must think from scratch; slower feedback loop | Always state: "default: X — correct?" |
| Sequential questioning (one at a time) | Creates a slow back-and-forth waterfall | Batch all questions into one message |
| Asking things visible in the codebase | Shows insufficient research effort | Read existing conventions before asking |
Before starting:
cat .claude/context/memory/learnings.md
After completing:
.claude/context/memory/learnings.md.claude/context/memory/issues.md.claude/context/memory/decisions.mdASSUME 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。