Results for “cursor”

Patterns for vibe coding that produce production-quality output instead of garbage. Covers prompt engineering for AI coding, verification without reading every line, accept/reject/refine decision framework, architectural guardrails, context management (CLAUDE.md, .cursor/rules), TDD-driven vibe coding, screenshot-driven development, diff review discipline, and the anti-patterns that destroy quality. Activate on: "vibe coding", "AI coding quality", "Claude Code workflow", "AI-assisted development", "how to use AI for coding", "coding with AI", "agentic engineering workflow", "AI code quality", "vibe code without garbage", "production quality AI code", "CLAUDE.md setup", "cursorrules setup", "pre-commit hooks for AI", "TDD with AI", "test-driven vibe coding". NOT for: multi-person collaborative coding sessions (use cooperative-vibe-coding), building AI/LLM applications (use ai-engineer), prompt engineering for non-coding LLM use cases (use prompt-engineer).

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Stop AI agents from secretly bypassing your rules. Mechanical enforcement with git hooks, secret detection, deployment verification, and import registries. Born from real production incidents: server crashes, token leaks, code rewrites. Works with Claude Code, Clawdbot, Cursor. Install once, enforce forever.

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Use when the user explicitly wants a ChatGPT App, Apps SDK project, MCP server plus widget UI, ChatGPT-compatible tool UI, or submission/deployment work for that surface. Build, scaffold, refactor, or troubleshoot those projects from Cursor, consult openai-docs before generating code, and use openai-platform-api-key before any app path that requires live OpenAI API credentials.

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Use when Cursor is asked to build, run, test, debug, or configure an OpenAI-backed or provider-unspecified AI app, UI, script, CLI, generator, or tool, especially requests phrased only as "using AI" or generators driven by forms/user input; also use for OPENAI_API_KEY or sk-proj setup. Treat this as the credential gate: inspect safely, ask reuse-vs-new before API work, guide manual local setup when needed, verify presence, and never expose plaintext.

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Use when the user wants to build, adapt, run, or evaluate an OpenAI Agents SDK app from Cursor. Prefer a docs-first workflow and route API credential decisions through openai-platform-api-key before API-backed work.

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Identifies Oracle-to-PostgreSQL migration risks by cross-referencing code against known behavioral differences (empty strings, refcursors, type coercion, sorting, timestamps, concurrent transactions, etc.). Use when planning migration of a procedure, trigger, query, or refcursor client, and again to validate the finished port.

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Detects early-stage ransomware indicators in network traffic before encryption begins, including initial access broker activity, command-and-control beaconing, credential harvesting, reconnaissance scanning, and staging behavior. Uses network detection tools (Zeek, Suricata, Arkime), SIEM correlation rules, and threat intelligence feeds to identify ransomware precursor patterns such as Cobalt Strike beacons, Mimikatz network signatures, and RDP brute-force attempts. Activates for requests involving pre-ransomware detection, network-based ransomware indicators, or early warning ransomware monitoring.

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METAINFORMANT rules for directory .cursor. Use when editing, adding tests, or reviewing code under this path. Read the linked AGENTS.md first; use uv only, write outputs to output/, real implementations.

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METAINFORMANT rules for directory cursorrules. Use when editing, adding tests, or reviewing code under this path. Read the linked AGENTS.md first; use uv only, write outputs to output/, real implementations.

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Cursorで実装済みコードを検証するnative入口。共有testerとtest-procedureを読み、親が検証範囲と結果を確定する。

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Cursorで複数の資料や観点を集め、根拠付きの結論・仮説をまとめる。一次資料まで引用・参照を追跡する deep research にも使う。

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Cursorで計画と実装の各ステップ、実測結果を記録文書として作成・更新する。後続作業の記録を残すことが依頼の目的の場合に使う。計画だけを作る場合は deepplan、単一の変更を完了まで進める場合は pir2。

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Cursorで原因が未確定のエラーや不具合を、ログ・再現・コードの実測から調査して修正する。症状やエラーログなどから原因調査が必要な場合に使う。

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Cursorで実装前に複雑な変更の探索・設計判断を整理して実行可能な計画を作る。計画作成が依頼の成果物で、実装を始めない場合に使う。

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Cursorで判断に迷う重要な論点を独立した熟考担当に検討させ、結論と未解決点を整理する。選択肢の比較や設計判断に確信を持てない場合に使う。要件をユーザーと決める場合は brainstorm、計画作成は deepplan。

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Cursorで複雑な実装・設計変更を計画から受入まで一つの作業単位として進める。設計判断や影響範囲の整理、実装・独立確認まで必要な変更に使う。原因と範囲が明確な小変更は ir、独立したサブタスクへ分割する大規模作業は epic。

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Cursorでコード・設計・指示のレビュー依頼を受けたときのnative入口。共有reviewer Skillを読み、対象・担当配分・結果集約を親が行う。

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Cursorで差分または既存コードの説明依頼を受け、実コードに基づく説明を整理する。説明の詳細化や、指定保存先へのHTML化にも対応する。

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Cursorでローカルの差分・ファイルからリファクタリング改善案を返すnative入口。変更は適用せず、共有refactor-advisorとrefactor-guidanceを読み、reviewerのVERDICTから分離する。

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Cursorで大規模な変更を独立したサブタスクへ分割し、依存関係に沿って段階的に実装・統合する。複数サブシステムや機能をまたぎ、単一の作業単位では扱いにくい改修に使う。

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Cursorでreviewer等から割り当てられた観点を評価する担当用native入口。共有code-review-guidanceと担当referenceを読み、結果を親へ返す。

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Cursorで問いに応じて根拠や比較を加えて答える深掘り対話。明示的な /chat の指定でだけ使い、通常の会話には自動適用しない。

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Cursorでユーザーとの対話を通じて要件や設計の選択肢を整理し、実装前の決定事項を確定する。曖昧な要件や複数案のどれを採るかをユーザーと決める場合に使う。独立した熟考は deepthink、計画作成は deepplan。

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runtime 組込みのメモリ機能とは別に、プロジェクト横断の学び・失敗・意思決定・中断点を長期記憶から検索し、確定した知見を記録する。最上位のセッションで過去の経緯や判断が今回の方針に関わる長い作業の開始・中断後の再開、過去の経緯の参照、知見の確定、終了時の要約で使う。委譲された担当では自動発動しない。Cursor の非同期入口はこのSkillで定める。

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