1,543 件 ・ 関連度順
概要と使いどころ
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.
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。
Jevを使い、日本語中心・英語対応で文書、メール、メッセージ、提案書、技術資料、スライドの抽出テキストを多角的にレビューする。AIっぽさ、定型的な文体、冗長さ、直訳調、過剰敬語などを評価し、根拠引用と具体的な改善案を作成担当者へ返して改善ループを回すときに使う。Japanese-first bilingual editorial style review with Jev scores, source-grounded feedback and bounded revision loops; not an AI-authorship detector.
Use when evaluating a completed or in-progress project across scope, correctness, quality, testing, and learning outcomes using structured Praise-Critique-Grow feedback.
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。
Triage TestFlight crashes, beta feedback, and performance diagnostics using asc. Use when the user asks about TF crashes, TestFlight crash reports, beta tester feedback, app hangs, disk writes, launch diagnostics, or wants a crash summary for a build or app.
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。
Bei vorhandenem und ausdrücklich autorisiertem lokalem Entscheidungsprofil: wiederkehrende Entscheidungen aus belegtem Feedback vorhersagen, Konfidenz kalibrieren und Vorhersage, Entscheidung und Ausführung strikt trennen.
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。
Builds DRAFT user personas from the research notes, interview summaries, survey free text and support themes the user provides: for each persona the goals, pains, jobs to be done, context of use, quotes exactly as supplied with their participant codes, and the evidence count behind every attribute, with names, demographics and any detail no participant stated left UNKNOWN rather than invented. Use when the user asks to "build personas from these interviews", "who are our users based on this research", "draft user personas", "turn these research notes into personas" or "update our personas with the new interviews". Do not use for theming a batch of customer feedback into counts, use customer-feedback-theme-synthesis instead; for exit interviews, use exit-interview-synthesis; for the requirements those personas imply, use product-requirements-draft. Drafts for human review; never approves, authorises or signs off.
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。
Drafts a DRAFT self-assessment, peer feedback note or manager review narrative from the evidence the writer supplies (goals, examples, metrics, notes), in the review template where given: every sentence tied to a numbered evidence item, unsupported claims removed and logged, and a gaps list to complete before submitting. Never assigns, suggests or implies a rating, score, ranking, pay or promotion outcome. Use when the user asks to "write my self-assessment", "draft peer feedback for a colleague", "turn these notes into a performance review", "help me write the year-end review for my report", "summarise my achievements against my goals" or "draft the mid-year review". Do not use for a job description or role profile, use job-description-drafter instead; for a new hire's first 90 days, use onboarding-plan-builder. Drafts for human review; never approves, authorises or signs off.
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。
Reqordのデータモデル（Requirement, Specification, ProjectContext, Feedback）とCLI操作ルールの共通知識ベース。
Handle UTF-8 and text encoding safely in WordPress plugins, especially on WP 6.9+ where wp_is_valid_utf8(), wp_scrub_utf8(), and noncharacter helpers replace older seems_utf8-style checks. Covers when to validate, scrub, reject, or preserve invalid bytes; wp_check_invalid_utf8 behavior; XML/JSON/feed/export boundaries; and avoiding data loss from premature replacement. Use when processing imported text, CSV, XML, feeds, email, REST payloads, AI prompts, logs, filenames, or external API data.
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 the user asks to "triage our comments, DMs, and mentions", "draft replies to this thread", "can we repost this fan post", or "set up inbox SLAs and an escalation path"; produces a ranked triage queue with register detection (sincere / ironic / performative / parasocial, sentiment-inversion table included — "this is so bad" under a comedy register is praise), a commenter taxonomy (troll monitor-only / rager / misguided / unhappy-customer / advocate) with a response-tier ladder and per-channel SLAs, an escalation matrix ending at the crisis path, a moderation ladder plus house rules for owned spaces, and a UGC curation-and-rights mode whose dated permission entries route to the channel registry — every reply is a ranked DRAFT a human posts; nothing is ever auto-sent. Not for launch-window feedback triage — use launch-feedback-synthesizer. 评论私信提及分诊/语域识别/回复草稿/UGC授权
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。
差分が「その差分自身を審査するレビュー基準・品質ゲート」を弱めていないかを diff-time で検出する。Check 1 レビュールールの削除・弱体化（.river/rules.md / .river/rules.d/*）、Check 2 実行時コンフィグの閾値・ゲート緩和（.river-review.{json,yaml,yml} の review.severity 引き下げ / exclude 拡大 / memory.suppressionEnabled 無効化 / selection.skills.exclude 追加）、Check 3 suppression entry の新規追加、Check 4 lint・静的解析設定からのルール削除や無効化、Check 5 branch protection・required check の緩和、の 5 Check を対象とし、これらが機能変更と同一 PR に混在し、かつ意図の宣言が無い場合に指摘する。report-only。workflow の permissions / action pin は gha-workflow-security、既存 suppression entry の使い分けは suppression-feedback、設定ファイルの一般的妥当性は config-json、.only / .skip / @ts-ignore / @ts-nocheck は heuristic-review.mjs の決定論検出器、リファクタと機能追加の混在は behavior-structure-separation へ委譲する
River Review のメインエントリポイント。 レビュー依頼の intent classification → 専門 skill 選択 → 実行 → finding verification → feedback classification → fixture / reference / suppression への還元までを束ねる improvement-loop orchestrator。
Expert en developer advocacy (communauté, contenu, docs, demos, feedback loop, métriques)
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。
Expert en agents avec boucle humaine (workflows d'approbation, escalade, intégration feedback, supervision)
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。
Precise language for design feedback. Ban vague words. Name what you actually see. Use when giving design feedback, running critiques, or training teams to communicate about quality.
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。
Search and analyze Reddit discussions for market research, product feedback, and community insights using Xpoz. Use when asked to "search Reddit", "what does Reddit think about X", "Reddit feedback on X", "subreddit analysis", or "Reddit market research".
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。
Analyze and improve existing Ozor.ai video prompts for better output quality. Use this skill whenever the user has an Ozor prompt that produced mediocre results, wants to improve a video prompt, needs help debugging why a video didn't turn out well, or wants expert feedback on their prompt before running it. Trigger on phrases like 'improve this prompt', 'optimize my Ozor prompt', 'why did my video look bad', 'fix this prompt', 'make this prompt better', 'review my Ozor prompt', 'the video didn't turn out right', 'prompt feedback', 'better results from Ozor', or any request to refine, debug, or enhance an existing Ozor video prompt.
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。
Triage TestFlight crashes, beta feedback, and performance diagnostics using asc. Use when the user asks about TF crashes, TestFlight crash reports, beta tester feedback, app hangs, disk writes, launch diagnostics, or wants a crash summary for a build or app.
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。
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.
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。
Triage TestFlight crashes, beta feedback, and performance diagnostics using asc. Use when the user asks about TF crashes, TestFlight crash reports, beta tester feedback, app hangs, disk writes, launch diagnostics, or wants a crash summary for a build or app.
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 receiving code review feedback, before implementing suggestions, especially if feedback seems unclear or technically questionable - requires technical rigor and verification, not performative agreement or blind implementation
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。
やりたいことを1行で言うと、B 型 loop engineering の 7 要素 (context / feedback / verification gate / termination / error handling / state / cost guard) を埋めた loop spec をコピペ可能な形で生成する。生成した spec は現行 Claude Code の実行プリミティブ (Workflow ツール / /loop skill / ralph-loop plugin / claude -p) に落とせる骨格になる (旧 `claude --goal` は廃止)。10 件 failure mode (F1-F10) の対策フックも自動挿入。Hybrid モード: 1 行入力 → デフォルト埋めで一発出力 → 「ここを調整したい」場所だけ短く聞き直す。Use when ユーザーが「loop を作りたい / loop-design / 自走ループ書いて / Workflow 用の spec 作って / 7 要素埋めて / verification gate ありで」と言ったとき、または `/loop-design` を実行したとき。Loop engineering の理論背景は Cards/loop-engineering-autonomous-agents、失敗モード対策は Cards/loop-failure-modes-mechanism-2026 を参照。
Insurance-industry App-in-Skill for read-only data governance, backed by an operator-provisioned Busabase workspace (one Drive node for the file drive plus four Bases for QA pairs, featured information, insurer notices, and user feedback) and trusted export/restore/PDF-text-backfill scripts. Use when the user invokes $kelly-insure-data or /kelly-insure-data, wants an insurance data workspace with UI, needs to review insurance files, metadata completeness, QA pairs, featured information, insurer notices, or user feedback, wants to back up or restore a Kelly Insure Data Busabase workspace from local PDFs, or wants Busabase Drive/Base data surfaced for data quality review and ongoing data governance.
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。
Build and verify Feedback submission widget for Mobile-first interface with Bootstrap v5.3 using a working semantic implementation, responsive RTL/LTR behavior, theme tokens, test plan and design verification.
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。