1,036 件 ・ 関連度順
概要と使いどころ
Addresses all review comments on a PR automatically. Escalates genuine human decisions. Use when asked to /pr-merge-ready, create and babysit a PR, batch-fix PR comments, or address review feedback quickly.
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 PR review comments from a GitHub PR URL. Fetch review comments, verify each finding against the actual codebase, assess validity (correct/incorrect/partial), present a structured summary with recommended actions, and optionally reply to each comment on GitHub. Use when given a PR review URL or when asked to check/analyze PR 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。
Teach Copilot how to plan, address, and respond to pull request review 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。
Helps users generate, edit, and validate mirrord.json configuration files for mirrord (MetalBear). Use when the user wants to connect their local process to a Kubernetes environment, configure features (env/fs/network), or needs feedback on an existing mirrord.json. Always ensures output JSON is valid and schema-conformant.
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。
Hunt HTML Injection — user-supplied input is rendered as raw HTML in the response without sanitisation, allowing an attacker to inject arbitrary HTML tags (but not necessarily JavaScript). Lower severity than XSS but enables phishing, UI manipulation, and credential harvesting via injected forms. Use when testing text-display surfaces (search results, profile fields, comments, error messages, feedback forms). For markup that executes JavaScript, escalate to hunt-xss.
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。
Simulates academic peer review, evaluating papers across Originality, Methodology, Results, and Writing to provide Major/Minor Revision recommendations with actionable feedback. Triggers when a user asks to "review my paper," "simulate peer review," or "give my paper a peer 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。
Run the R code review protocol on R scripts. Checks code quality, reproducibility, domain correctness, and professional standards. Produces a report without editing files. Make sure to use this skill whenever the user wants their existing R code evaluated or audited — not when they want new analysis written. Triggers include: "review my R script", "check my R code", "is my code replication-ready", "audit this R file", "does this code follow conventions", "will this reproduce", "check my analysis script", "code review", "review-r", or when the user has an existing .R file and wants quality feedback rather than new 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。
Run the proofreading protocol on academic writing — papers or manuscripts. Checks grammar, typos, layout issues, consistency, and academic writing quality. Produces a report without editing files. Make sure to use this skill whenever the user wants surface-level writing errors found — not substantive academic critique. Triggers include: "proofread", "check for typos", "grammar check", "look for errors in my draft", "proofread all", "polish this", "check my writing", "are there any mistakes", "proofread before I send this", or when the user wants a clean-up pass rather than feedback on arguments or methods.
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。
Generate a complete academic literature survey from scratch using multi-agent orchestration. Searches academic databases (OpenAlex, CrossRef, Unpaywall), downloads PDFs, builds BibTeX, drafts a LaTeX review, compiles it, reviews for quality, and revises based on feedback — all automated. Use this skill whenever the user asks to "generate a literature review", "write a survey paper", "review recent papers on [topic]", "create a survey of [field]", "综述", "文献综述", "survey papers in top journals", or wants a multi-agent pipeline to produce a publishable-quality literature review. Also trigger when the user wants to search multiple journals for papers on a topic and synthesize findings into a structured document. Works for any academic field but optimized for economics journals.
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。
Collaboratively build and refine paper screening rubrics through brainstorming, test-driven development, and iterative 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。
Experimental workflow for auditing recurring feedback, telemetry, errors, and brittle delivery paths to find systemic fixes. Use for periodic or requested cross-source lookbacks, not routine single-item intake.
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。
Experimental workflow for summarizing work that still needs human judgment across configured pull requests, issues, feedback, errors, and delivery signals. Use for a human decision queue or bounded 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。
Experimental workflow for configuring an autonomous software delivery factory. Use when choosing feedback sources, schedules, worktree behavior, autonomy gates, or host automations.
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。
Experimental workflow for collecting and triaging product feedback, product telemetry, runtime errors, and issue reports. Use when scanning configured signal sources and applying separate fix, reply, or close rules.
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。
Read and triage existing pull request review comments, or address them when requested. Use for PR comment requests or /pr-comments; use review to inspect code without existing reviewer 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。
CRO analysis for landing pages evaluating headline clarity, CTA placement, trust signals, mobile friction, and conversion killers. Use when uploading a landing page screenshot, pasting a URL for review, requesting conversion rate optimization feedback, or auditing page effectiveness prioritized by impact. Platform: Google and Meta.
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。
Inspects Observal traces, sessions, rankings, feedback, telemetry health, logs, and Agent insight reports. Use when the user wants operational evidence, current activity, telemetry diagnosis, ratings, report generation, regression analysis, or recommendations grounded in Agent usage.
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。
Master effective code review practices to provide constructive feedback, catch bugs early, and foster knowledge sharing while maintaining team morale. Use when reviewing pull requests, establishing review standards, or mentoring developers.
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。
Debug a reproducible symptom with a bounded feedback loop and original-scenario 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。
Use when a reviewer, CI bot, or another AI leaves feedback to address
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。
Structured manuscript/grant review with checklist-based evaluation. Use when writing formal peer reviews with specific criteria methodology assessment, statistical validity, reporting standards compliance (CONSORT/STROBE), and constructive feedback. Best for actual review writing, manuscript revision. For evaluating claims/evidence quality use scientific-critical-thinking; for quantitative scoring frameworks use scholar-evaluation.
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。
Systematically evaluate scholarly work using the ScholarEval framework, providing structured assessment across research quality dimensions including problem formulation, methodology, analysis, and writing with quantitative scoring and actionable 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。
Choose supported scope and compatibility boundaries for SDK behavior changes; revisit when feedback changes the design.
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。
群众路线：从持有真实情况的多方（用户、使用者、代码库、日志、运行结果）收集分散意见，系统化为方案，再带回去对齐与检验，循环改进。当多方意见分歧、需要汇总零散反馈、方案要拿回给真实使用者确认、或你发觉自己在闭门造车时触发；信息源单一且完整、处于执行阶段时不触发。 English: Mass line. Collect scattered input from everyone who holds ground truth (users, operators, codebase, logs, runtime results), synthesize it into a coherent plan, take it back for alignment and validation, and iterate. Trigger when inputs conflict, feedback must be consolidated, a plan needs sign-off from real users, or you sense you are designing in isolation; skip when there is a single complete source and the work is pure execution.
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。