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Drive a GitHub Copilot (or any bot reviewer) pull-request review to a clean pass without babysitting it: fix each finding in its own commit, reply to the review thread with the fix sha, resolve the thread, re-request the bot, and poll for the async re-review. Covers the thread node-id (PRRT_...) vs comment databaseId distinction, the resolveReviewThread GraphQL mutation, the copilot-pull-request-reviewer[bot] slug, and how to read the bot's verdict (COMMENTED plus a "human review recommended" banner is not a blocking finding). Use when Copilot has left review comments on your PR, when bot review threads must be closed out with an auditable fix-reply-resolve trail before merge, or when you need to verify that a re-review actually landed on the new HEAD rather than the old one.

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。

Simulate a Nature-style reviewer assessment from the referee perspective rather than an author rebuttal. Use when the user wants a pre-submission review, reviewer report, peer-review style critique, novelty/significance/technical soundness assessment, reviewer-style manuscript evaluation, 审稿人视角评估, 预审稿意见, or Nature reviewer report. Return 3 reviewer reports plus a cross-review synthesis, grounded only in the local Nature reviewer source basis. Also trigger on general pre-submission review requests during academic writing even without the word "Nature", such as getting a mock peer review for any journal, critiquing a draft as a reviewer would, assessing novelty/rigor before submission, and Chinese phrasings like 审稿人视角、模拟审稿、预审、帮我审一下论文、投稿前自审、审稿意见模拟、找论文问题.

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。

review-all を実行し、指摘内容をコードに反映、bun run c / bun run lint / bun test で自己検証し、CONVERGED/NOT_CONVERGED の収束判定付き完了レポートを /tmp/arima-review-fix-result.md に出力する。レビュー→修正→検証→レポートを一気通貫で行うスキル。スコープ引数は /review-all と同じ（wt / PR #N / vs:<branch> / range / ファイル列挙）。review-fix-loop からの自動呼び出し（mode=non-interactive）にも対応。Use when user says 'レビューして直して', 'review and fix', '自動修正', 'レビュー反映', or when invoked by review-fix-loop.

Provides comprehensive code review guidance for React 19, Vue 3, Angular 17+, Svelte 5, Rust, TypeScript, Java, Java 8, PHP, Ruby, Rails, Python, Django, FastAPI, Go, C#/.NET, Kotlin, Swift, Dart, Flutter, NestJS, C/C++, Zig, CSS/Less/Sass, Qt, and more. Covers architecture review, performance review, security audit, code quality anti-patterns, and common bugs across all ecosystems. Use when: reviewing pull requests, conducting PR reviews, code review, reviewing code changes, establishing review standards, mentoring developers, architecture reviews, security audits, performance reviews, checking code quality, finding bugs, giving feedback on code.

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。

SwiftUI のレイアウト落とし穴・ベストプラクティス・非推奨パターンと、 iOS / watchOS アプリの実機配布 (Provisioning / App Group / Code Signing / Apple Watch Developer Mode / Xcode 15+ Debug dylib) トラブルシューティング のガイド。コード生成・修正時に既知のレイアウトバグを防ぎ、 App Group + watchOS + Apple Watch の実機インストール失敗を 7 段階フレームワークで診断・解消する。 Use when: SwiftUI のコードを書く・修正するとき。 レイアウト崩れを修正するとき。safeAreaInset や ViewThatFits を使うとき。 マルチデバイス対応するとき。iOS + watchOS アプリの実機ビルド / 配布で provisioning / App Group / Manual Signing / Apple Watch の UDID / Xcode 自動署名の 罠に詰まったとき。Apple Watch に "Could not install at this time" が出たとき。 Triggers: "SwiftUI", "layout", "safeAreaInset", "ViewThatFits", "GeometryReader", "レイアウト", "崩れ", "表示バグ", "iPhone SE", "ATT", "ATTrackingManager", "requestTrackingAuthorization", "AdMob", "広告", "Provisioning Profile", "App Group", "Manual Signing", "Code Signing", "Apple Watch", "watchOS", "Install できない", "Could not install at this time", "Bundle ID 紐付け", "Xcode Automatic Signing", "embedded.mobileprovision", "Spaceship", "App Store Connect API", "WKCompanionAppBundleIdentifier", "Developer Mode", "Privacy & Security", "watchOS Developer Mode", "Apple Watch に App を入れられない", "整合性を確認できなかった", "integrity check", "ENABLE_DEBUG_DYLIB", "__preview.dylib", "debug.dylib", "Xcode 15 Preview", "SwiftUI Preview dylib", "ENABLE_PREVIEWS", "AppIntents", "AppShortcut", "AppShortcutsProvider", "AppEntity", "AppEnum", "Siri", "Siri に流れる", "Siri がリマインダーに流れる", "updateAppShortcutParameters", "Invalid parameter type", "Invalid Utterance", "applicationName", "CFBundleDisplayName", "CFBundleSpokenName", "TaskEntityQuery", "AppEntityQuery", "TimelineProvider", "recommendations", "WatchConnectivity", "WCSession", "updateApplicationContext", "sessionDidBecomeInactive", "iPhone と Watch でデータ共有", "App Group 共有できない", "scenePhase", "ポーリング", "watchOS バッテリー", "TextField 文字色 watchOS", "Picker 文字色 watchOS", "Single Size AppIcon", "watchOS AppIcon"

Monitor PR review comments and automatically classify and address reviewer feedback including code changes, questions, and nits. Use when handling PR reviews, addressing reviewer comments, responding to code review feedback, or automating review resolution. Triggers on handle reviews, PR review, address feedback, reviewer comments, code review, review response.

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。

Runs an autonomous review-and-fix improvement loop over the current branch's changes until a PR review comes back clean, scoped mechanically to the directories the branch touched. Reviews are performed by an installed PR-review skill (default: pr-review-toolkit's review-pr). Use to fix review findings on a branch before opening or updating a pull request ('clean up this branch', 'fix this PR until review passes', 'run review-and-fix on my changes'). NOT for a one-time review — run the PR-review skill directly.

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。

[omh] CRM pipeline or sales forecast to review: turn a supplied CRM export or pipeline snapshot into an evidence-bound pipeline health, forecast, and follow-up review. Aliases: pipeline-review, forecast-review, deal-review. Use when the user says: sales-pipeline-review, sales pipeline review, pipeline review, pipeline health, pipeline coverage, deal review, deal health, sales forecast review.

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。

Amazon niche market review analysis and consumer sentiment insights. Trigger when the user mentions niche market review analysis, consumer sentiment, user pain points, customer feedback insights, review topic analysis, positive/negative review breakdown, niche market opinion mining, product review sentiment analysis, niche market reviews, consumer sentiment, customer pain points, review topic analysis, positive/negative reviews, opinion mining, Nexscope data. Even if the user does not explicitly mention "niche market reviews", if their need involves analyzing consumer reviews within Amazon niche markets or understanding customer sentiment at the niche market level, this skill should also be triggered.

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。

Review owned or authorized code for security using structure-first evidence: AST/structure maps, call graphs, complexity, Source/Sink flow, and defensive findings. Use when asked for security review, vulnerability review, AST structure map review, SAST triage, Source/Sink, taint flow, parser/scanner hardening, CI/CD security, LLM/agent tool boundary review, 脆弱性レビュー, 構造マップ, セキュリティレビュー.

Multi-agent code review using the Pragmatic Quality framework. Orchestrates parallel review agents (CLAUDE.md compliance, bug scanning, git history, security) with independent confidence scoring to produce high-signal findings. Use when user runs /code-review, /review:code-review, requests a "code review", "review my changes", "PR review", or mentions "review diff", "review branch".

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。

Autonomous comprehensive review. Once-through pipeline over /review-health, /review-arch, /review-security, /review-perf, /review-a11y, /review-test, /review-release. Operator-configurable ticket creation at startup — when ON, auto-approves sub-skill ticket proposals per the orchestrator-family contract; when OFF, uniformly declines and surfaces findings in the consolidated report. Auto-detects sub-skills that do not apply (no web content → skip /review-a11y; no tests → skip /review-test).

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。

Sweeps a SharePoint library listing (an export or a listing the agent can reach, with file name, link, review-date column and owner column) for documents past their review date and returns a dated DRAFT review sweep report (Overdue, Due soon, No review date, Summary) plus one ready-to-paste reminder per document owner for the user to send. Never changes metadata, sends a message or invents a document, date or owner. Use when the user asks to "find the documents past their review date", "run the review sweep on the policies library", "which documents are overdue for review", "audit the review dates in this library export" or "draft reminders to owners about stale documents". Do not use for duplicate, conflict and ownership checks across knowledge files, use knowledge-base-hygiene-review instead; for gaps in an engineering deliverables register, use master-document-register-check. 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。

Review code changes for correctness, completeness, bugs, edge cases, and quality. Load when the user explicitly asks to review code, check a PR, review a diff, audit recent changes, or verify an implementation matches requirements. Also triggers on "review this code", "check this PR", "review my changes", "code review", "did this implement correctly", "audit this diff", or any explicit request for a formal code review. Do NOT load for "review changes for context" or "review what happened" — those are requests to read code, not to perform a formal review.

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。

Nuclear-grade 12-agent pre-publish release gate. Runs /get-unpublished-changes to detect all changes since last npm release, spawns up to 10 ultrabrain agents for deep per-change analysis, invokes /review-work (orchestrator manual QA plus one gate reviewer) for holistic review, and 1 oracle for overall release synthesis. Runs ONLY when the user explicitly asks for a pre-publish review — a plain publish/release request MUST NOT trigger this; /publish ships directly. Triggers: 'pre-publish review', 'review before publish', 'release review', 'pre-release review', 'ready to publish?', 'can I publish?', 'pre-publish', 'safe to publish', 'publishing review', 'pre-publish check'.

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。

Performs AI-powered code review on Git changes using the `ocr` CLI from alibaba/open-code-review. Use when the user asks to review code, review a pull request, review staged/unstaged changes, review a commit, or compare branches for code quality issues. Produces line-level review comments and can automatically apply fixes when requested. With appropriate review rules, can detect various types of issues including bugs, security vulnerabilities, performance problems, and code quality concerns.

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。

Runs a mock interview for a specific job description. Plays the interviewer in a chosen round (recruiter screen, hiring manager, behavioral, coding, system design, case, product sense, panel), persona and difficulty; asks one question at a time, probes vague answers, and gives quote-backed rubric scores after each answer (coach mode) or at the end (realistic). Model answers use only the user's real experience. Use when the user says "mock interview me", "interview me for this job", "practice interview", "pretend you're the interviewer", "grill me for this role", "run a behavioral round", "quick recruiter screen", "hiring-manager mock", "system design mock" or "case interview practice". With Reactive Resume MCP it reads the application and stories and logs the session. For a story bank, company brief, questions to ask or a real-interview debrief, interview-prep; for scheduling or thank-you notes, job-application-manager; for fixing the resume, resume-tailor; for negotiation practice, offer-negotiation.

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。

This skill helps users automatically extract Amazon product reviews via the Amazon Reviews API. Agent should proactively apply this skill when users express needs like getting reviews for Amazon product with ASIN B07TS6R1SF, analyzing customer feedback for a specific Amazon item, getting ratings and comments for a competitive product, tracking sentiment of recent Amazon reviews, extracting verified purchase reviews for quality assessment, summarizing user experiences from Amazon product pages, monitoring product performance through customer reviews, collecting reviewer profiles and links for market research, gathering review titles and descriptions for content analysis, scraping Amazon reviews without requiring a login.

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。

Performs a full AWS Well-Architected Framework review evaluating every framework question across all pillars discovered from the live AWS documentation by analyzing code, IaC, and configurations to produce evidence-backed findings with Eisenhower-prioritized remediation. Supports full reviews (every framework best practice with BP ID citations), quick reviews (question-level), pillar-scoped reviews, score-mode reviews (a maturity scorecard with per-pillar scores and filtered findings), and lens-specific reviews using lenses discovered from the live AWS documentation. Triggers on mentions of Well-Architected review, WA review, WAR, pillar assessment, architecture review across pillars, workload assessment, cloud readiness evaluation, or a Well-Architected score, grade, or scorecard request. Does not apply to single-pillar deep-dives, learning WA concepts, ADRs, or migration readiness assessments.

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。

Facilitate a structured conversation to customize how the review molecule works -- atom loading rules, severity classification, report format, scope rules, insight capture, and health logging. Produces a formal review-standards.md document that the review molecule will use as its process configuration. Use when the user says 'customize review', 'configure review', 'review preferences', 'review settings', 'change review process', or 'set up review'.

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。

Delegate code review to a subagent running a specific model. Use ONLY when user explicitly names a model to review changes ("review with opus", "use sonnet to review", "review with gemini"). The root agent reconstructs changes from conversation history and spawns a subagent with the code-review skill using the specified model. Do NOT use for general code review (use code-review skill instead), for reviewing PRs from git history, or when no model is specified by the user.

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。

🇺🇸 User Interview & Cold-Start Operations Playbook — Battle-tested framework from HeyGen's 937 interviews to PMF. Complete SOP for user screening, interview execution, Beta testing methodology, cold-start user operations, churn analysis, and user grading systems. 🇨🇳 用户访谈与冷启动运营实战手册 — 基于 HeyGen 937 场访谈验证的 PMF 方法论。包含用户筛选、访谈执行、Beta 测试设计、冷启动用户运营、流失分析、用户分级体系完整 SOP。 🇯🇵 ユーザーインタビュー＆コールドスタート運営プレイブック — HeyGenの937回インタビューで検証されたPMF方法論。ユーザースクリーニング、インタビュー実行、Betaテスト設計、コールドスタートユーザー運営、離脱分析、ユーザーグレーディング。 🇰🇷 사용자 인터뷰 & 콜드 스타트 운영 플레이북 — HeyGen 937회 인터뷰로 검증된 PMF 방법론. 사용자 스크리닝, 인터뷰 실행, Beta 테스트 설계, 콜드 스타트 사용자 운영, 이탈 분석, 사용자 등급 시스템. Triggers: "user interview" | "user research" | "customer discovery" | "PMF" | "product-market fit" | "beta test" | "beta testing" | "cold start users" | "cold start operations" | "churn analysis" | "user grading" | "用户访谈" | "用户调研" | "冷启动" | "冷启动运营" | "Beta测试" | "流失分析" | "用户分级"

Handles PR review comments and feedback resolution. Use when user wants to resolve PR comments, handle review feedback, fix review comments, address PR review, check review status, respond to reviewer, verify PR readiness, review PR comments, analyze review feedback, evaluate PR comments, assess review suggestions, or triage PR comments. Fetches comments via GitHub CLI, classifies by severity, applies fixes with user confirmation, commits with proper format, replies to threads.

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。

Simulate rigorous, fair peer review on a paper — in two modes. (A) Red-team YOUR OWN draft before submission to predict the reviews you'll get and get a fix list. (B) Review SOMEONE ELSE'S paper when you're an assigned reviewer or helping your advisor — produce a fair, venue-formatted, submission-ready review. Use whenever the user gives a paper (PDF, .tex, .md, arXiv link, or pasted text) and wants to predict reviews, find weaknesses before reviewers do, stress-test a submission, OR write a real review of another paper. Grounded in official NeurIPS/ICLR/ACL reviewer guidelines; every criticism pinned to a location, and checked against ACL's H1–H17 list of illegitimate critiques. 两种模式:审自己的稿(投稿前红队)/ 审别人的稿(当审稿人或帮导师),按会议官方标准评,绝不脑补、绝不发不正当批评。

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。