Testing & Security skills

Premium brand-kit image generation skill for creating high-end brand-guidelines boards, logo systems, identity decks, and visual-world presentations. Trained for minimalist, cinematic, editorial, dark-tech, luxury, cultural, security, gaming, developer-tool, and consumer-app brand systems. Optimized for intentional logo concepting, refined composition, sparse typography, strong symbolic meaning, premium mockups, art-directed imagery, and flexible grid layouts.

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Use when the user wants to design, redesign, shape, critique, audit, polish, clarify, distill, harden, optimize, adapt, animate, colorize, extract, or otherwise improve a frontend interface. Covers websites, landing pages, dashboards, product UI, app shells, components, forms, settings, onboarding, and empty states. Handles UX review, visual hierarchy, information architecture, cognitive load, accessibility, performance, responsive behavior, theming, anti-patterns, typography, fonts, spacing, layout, alignment, color, motion, micro-interactions, UX copy, error states, edge cases, i18n, and reusable design systems or tokens. Also use for bland designs that need to become bolder or more delightful, loud designs that should become quieter, live browser iteration on UI elements, or ambitious visual effects that should feel technically extraordinary. Not for backend-only or non-UI tasks.

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Guide for when to use and when not to use return validators in Convex functions. Use this skill whenever the user is writing Convex queries, mutations, or actions and needs guidance on return value validation. Also trigger when the user asks about Convex type safety, runtime validation, AI-generated Convex code, Convex AI rules, Convex security best practices, or when they're debugging return type issues in Convex functions. Trigger this skill when users mention "validators", "returns", "return type", or "exact types" in the context of Convex development. Also trigger when writing or reviewing Convex AI rules or prompts that instruct LLMs how to write Convex code.

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Audits Convex performance for reads, subscriptions, write contention, and function limits. Use for slow features, insights findings, OCC conflicts, or read amplification.

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Audits and realigns UI to match design system standards, spacing, tokens, and patterns. Use when the user mentions consistency, design drift, mismatched styles, tokens, or wants to bring a feature back in line with the system.

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Run convex-doctor static analysis, interpret findings, and fix issues across security, performance, correctness, schema, and architecture categories. Use when running convex-doctor, fixing convex-doctor warnings or errors, improving the convex-doctor score, or when asked about Convex code quality, static analysis, or linting Convex functions.

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Security review checklist for Convex functions, auth logic, public queries, admin routes, webhooks, uploads, components, and AI-generated code. Use when reviewing code that touches user data, PII, or access control, or before any deploy of an app with auth.

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Run technical quality checks across accessibility, performance, theming, responsive design, and anti-patterns. Generates a scored report with P0-P3 severity ratings and actionable plan. Use when the user wants an accessibility check, performance audit, or technical quality review.

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Evaluate design from a UX perspective, assessing visual hierarchy, information architecture, emotional resonance, cognitive load, and overall quality with quantitative scoring, persona-based testing, and actionable feedback. Use when the user asks to review, critique, evaluate, or give feedback on a design or component.

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Run every Convex audit (authz, reviewer, advisor, insights) into one scored, deduped readiness report with an ordered fix plan — Lighthouse for your backend.

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Audit and harden a Convex app's authorization: identity-from-arg impersonation, missing per-document ownership checks, public queries leaking data by a client-supplied id, and writes into a parent/container the caller doesn't own. Scans for the 4 shapes, applies requireIdentity/requireOwner, verifies with tsc. TRIGGER on 'secure my app', 'audit auth/authz', 'who can access this data'. SKIP when there is no convex/ directory.

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Convex code reviewer — security, auth, validators, performance, and pattern checks for code in a convex/ directory. Use to review or audit Convex functions before shipping.

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Audit and optimize an existing Convex app: security, scale, upgrades, observability.

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Generate convex-test tests for the app's Convex functions.

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Security review checklist for Convex functions, auth logic, public queries, admin routes, webhooks, uploads, and AI-generated code. Use when reviewing code that touches user data, PII, or access control.

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Prove a Convex feature works — seed, drive as multiple mocked users via convex-test, assert behavior including the negative authz cases (wrong user refused, data-scope enforced).

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Use when adding or repairing Spark regression tests for asynchronous ownership, cancellation, persistence, restart recovery, or cross-surface projections. Not a coverage campaign, performance benchmark, source-text policy check, or full delivery review.

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Use when GitHub may have shipped a GraphQL schema update affecting timeline event unions (PullRequestTimelineItems / IssueTimelineItems), when the gh-timeline dispatcher fallback is hitting more than expected, before a gh-timeline release, or when the user requests phrases like "verify timeline coverage", "audit gh-timeline schema", "check for new timeline events", "GitHub schema changed". Walks through schema diff → patch → test update → live verification → optional fixture refresh, marking each spot where a human decision is required.

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プロジェクト監査。「監査して」「audit」「/audit」で発火。設計/UX/品質/テストなどの観点でコードベース全体を監査し、課題をissuesディレクトリに書き出す。実行ログで重複実行を防止。特定の差分・コミットのレビューには使わない（codex-review / cross-review を使う）。

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macOS アプリのクラッシュログ (.ips) を解析し、根本原因を特定するスキル。「クラッシュした」「crash」「.ips」「DiagnosticReports」「SIGSEGV / SIGABRT」で発火。**macOS 専用**（.ips の読み方が macOS の DiagnosticReports 前提。iOS の .ips は未対応）。解析は crash-analyzer subagent に委譲する。クラッシュログが存在しない一般のバグ調査・テスト失敗には使わない。

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テストの追加・修正・削除、または実装後の検証方針を判断するときに使う。タスクごとに反射的な回帰テストを増やさず、守るべき仕様、不安な仕様、実際に使われる経路、事前条件と事後条件を中心にテストを設計するためのスキル。

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実装要求に、要求が答えていない設計判断が残るとき、または誤りが後段で黙って通る変更を扱うときに使う。具体的には、API・設定の与え方・データモデル・新しい型や概念・責務や層境界を決める必要がある、複数の実現方法から選ぶ設計判断がある、変更範囲を事前に局所化できない、認可・公開範囲・データ消失・外部送信のように誤りをテストや型検査で検出しにくい、のどれかに当たるタスクで発火する。原因と修正箇所が特定済みで期待結果と検証方法が明確な修正、既存パターンの適用、機械的な rename、CI/CD・ドキュメント・設定値・依存バージョンだけの変更では使わない。要求を出典付きの決定と質問に分解する解釈ゲート、判断の重さに応じた階層(直接実装 / 軽量 / 標準)の判定、subagent への分担、実物差分での検収、独立レビューをフェーズ順に管理するスキル。

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開発作業のテスト手順書（testing.md）を単体で生成・再生成します。全ドキュメントの一括生成には generate-working-docs（新規機能開発）または generate-performance-docs（パフォーマンス改善）を使用してください。

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新規機能開発の作業ドキュメントを自動生成します。YYYYMMDD_要件名の形式でディレクトリを作成し、requirements.md、design.md、tasklist.md、testing.mdを生成します。「開発作業ドキュメント作成」「新規開発のドキュメント作って」「ドキュメント生成」などで呼び出されます。パフォーマンス改善作業には generate-performance-docs を使用してください。

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