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draft-patterns

Use when asked about UX patterns, interaction best practices, form design, navigation patterns, or loading states. Examples: "best practice for form validation", "navigation pattern for dashboard", "loading state UX"

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draft-patterns — UX Pattern Reference

Follow the output format defined in docs/output-kit.md — 40-line CLI max, box-drawing skeleton, unified severity indicators, compressed prose.

When to use

User asks about interaction patterns, best practices, form design, navigation, or loading/empty states.

Workflow

  1. Identify pattern category from user request (forms, navigation, loading, empty states, modals, etc.)
  2. Search UX knowledge base:
    python3 -m draft_agent.uiux search --domain ux --query "{pattern_category}" --limit 5
    
  3. Cross-reference severity ratings from results — surface Critical and High first
  4. Output structured do/don't table with code examples and severity

Output format

┌─ UX Patterns — {pattern_category} ──────────────────────────────────────────┐
│ Category    │ Issue              │ Do                  │ Don't    │ Severity │
├─────────────┼────────────────────┼─────────────────────┼──────────┼──────────┤
│ {category}  │ {issue}            │ {do}                │ {dont}   │ Critical │
│ {category}  │ {issue}            │ {do}                │ {dont}   │ High     │
│ {category}  │ {issue}            │ {do}                │ {dont}   │ Medium   │
└─────────────┴────────────────────┴─────────────────────┴──────────┴──────────┘

Code example ({do_example_label}):
{code_block}

Anti-patterns

  • Never recommend patterns without checking platform context (web vs. mobile vs. desktop)
  • Never ignore severity ratings — Critical issues must be called out explicitly
  • Never present more than 7 patterns per category without grouping
  • Never omit code examples for implementation-level questions

Delivery

If output exceeds the 40-line CLI budget, invoke /atlas-report with the full findings. The HTML report is the output. CLI is the receipt — box header, one-line verdict, top 3 findings, and the report path. Never dump analysis to CLI.

レビュー

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。

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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。

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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。

tonone-ai/tonone762026年10月5日 更新

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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。

tonone-ai/tonone762026年10月5日 更新

apex-plan

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Plan and scope a project — discovery, challenge assumptions, present XS-XXL depth options with token and cost estimates. Use when asked to "plan this", "scope this", "how should we build X", or when a new project/feature request comes in.

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。

tonone-ai/tonone762026年10月5日 更新

Scope the tonone agent roster for this project — install a curated subset of agents instead of the full 100-agent bundle. Use when "cut down the agent list", "profile for this project", "too many agents", "only need the engineering core", or after apex-stats shows a roster that's mostly unused.

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。

tonone-ai/tonone762026年10月5日 更新

Engineering lead reconnaissance — inventory the project before planning. Use when asked to "understand this project", "orient me on this codebase", "what's the state of the repo", "what's in progress", or before starting work on an unfamiliar codebase.

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。

tonone-ai/tonone762026年10月5日 更新

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