「comments」の検索結果

Turn an incoming set of findings — from an AI reviewer, a referee report, a code review, a linter, or a second model — into verified fixes, without letting a confident misread damage correct work. Every finding is a CANDIDATE until checked against the actual source. Use whenever you receive review comments, audit findings, or a critique you did not write yourself, especially when the reviewer is a model or when the volume is too large to check by feel.

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。

Fetch and analyze WeChat Official Account hot articles / 公众号爆款文章 by sector or keywords. Use when the user asks for 爆款文章分析, 赛道爆款, 公众号爆款数据, reading counts, likes, shares, comments, title patterns, writing style, 爆款原因分析, or writing references for content creation.

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。

读取 Word/WPS 审阅后的 docx，把批注（comments）与修订（track changes）提取成可逐条裁决的 markdown 对账表或 JSON。触发场景：对方批注完的合同/协议/书稿/报告回来了要读意见；「提取 docx 批注」「审阅意见对账」「读一下修订」「谁批了什么、批在哪」；WPS 云文档/Word 在线协作 导出的审阅稿；收到带修订模式改动的回稿要看对方改了什么。核心保证：修订感知——python-docx 裸读会漏掉修订插入（w:ins）的内容、认不出整段删除（w:del），本 skill 走 OpenXML SDK 引擎 不漏。只读，不改对方文件。边界：生成/排版 docx → docx-creator 或 minimax-docx；PDF 批注不在范围。

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 a community management playbook for a brand's social media channels. Use when asked to create guidelines for managing comments, DMs, and community interactions, define a moderation policy, or build response frameworks for social media community managers. Produces a complete playbook with response templates, escalation paths, moderation rules, and tone guidelines.

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。

Write a fair, enforceable community moderation policy. Use when standing up or overhauling moderation for a forum, Discord, Slack, subreddit, or any user community. Produces a clear code of conduct with examples, a graduated enforcement ladder tied to specific triggers, an appeals process, moderator guidelines, and the handling for the severe cases (threats, doxxing, brigading) that need immediate action. Governs member conduct in a user community — distinct from [[community-management-playbook]], which manages a brand's own social-media channels (comments, DMs, tone, response templates).

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 a pull request or diff like a thoughtful senior engineer — prioritized, kind, and focused on what matters. Use when reviewing code, giving PR feedback, or asked to 'review this change'. Produces a structured review: a correctness/design pass, comments ranked by severity (blocking → nit), what's done well, and a clear approve / request-changes call — feedback that improves the code and the author.

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 this skill any time a .docx file is involved -- as input, output, or both. This includes: creating Word documents, reports, letters, memos, or proposals; reading, parsing, or extracting text from any .docx file; editing, modifying, or updating existing documents; working with templates, tracked changes, comments, headers/footers, or tables of contents. Trigger whenever the user mentions 'Word doc', 'document', 'report', 'letter', 'memo', or references a .docx filename.

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 this skill any time a .pptx file is involved -- as input, output, or both. This includes: creating slide decks, pitch decks, or presentations; reading, parsing, or extracting text from any .pptx file; editing, modifying, or updating existing presentations; combining or splitting slide files; working with templates, layouts, speaker notes, or comments. Trigger whenever the user mentions 'deck', 'slides', 'presentation', 'pitch', or references a .pptx filename.

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。

Work with YouTube: read channels, videos, search, playlist items; upload videos and post comments (with confirmation). Trigger phrases: youtube, videos, upload video, youtube comment.

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。

Look up your Figma user, read file metadata, and post comments on files. Trigger phrases: figma, figma file, design file.

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。

Cut AI tells from text you write or edit for a human reader (commit messages, PR titles and bodies, docs, code comments, replies). Apply before committing, posting, or sending; leave prose you didn't touch alone.

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。

Iteratively improves a PR (GitHub), MR (GitLab), or shelved changelist (Perforce) until Greptile gives it a 5/5 confidence score with zero unresolved comments. Identical to greploop, but triggers reviews by tagging @greptile-apps, which bypasses Greptile's file-count limit on huge PRs that the plain @greptile mention refuses to review. Use when the user wants to fully optimize a large PR/MR/CL against Greptile's code review standards.

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。

Plan, draft, audit, and publish LinkedIn posts and comments. Use when the user wants to write a viral LinkedIn post, draft a comment or reply on any LinkedIn post URL, audit a draft against 2026 algorithm heuristics, remove AI tells, extract hook formulas from viral posts, or plan a week of content. Powered by the Publora API for publishing. User provides post/comment URLs, skill drafts content, user approves, then publishes.

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 reviewing a DataFusion Comet pull request. Covers the workflow that applies to every PR and routes to the area-specific review skills for expressions, FFI, memory management, shuffle, and Iceberg writes. Provides guidance to a human reviewer rather than posting comments.

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 an American Economic Journal: Macroeconomics (AEJ: Macro) decision letter has arrived (R&R or reject-with-comments) and you need a response-letter strategy and revision plan. Plans the rebuttal and revision; it does not run new identification, model, or robustness work itself (route to those skills).

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 drafting the response to an Administrative Science Quarterly (ASQ) R&R after the manuscript has been revised — structuring the response letter and handling reviewer/editor comments. Drafts the response; it does not perform the underlying revisions (do those first).

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 LinkedIn posts by keywords, sorted by engagement or date. Use when researching what people are saying about a topic on LinkedIn, finding high-engagement content, identifying thought leaders, or discovering warm leads through post engagement. Returns author, post text, reactions, comments, shares, post URL, and date. No LinkedIn cookies or login required.

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。

Extract and score leads from GitHub repositories by analyzing stars, forks, issues, PRs, comments, and contributions. Produces unified multi-repo CSV with deduplicated user profiles. No paid API credits required.

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。

Mine comments and replies on social posts, videos, and ads for recurring customer language, questions, objections, desired outcomes, complaints, product requests, purchase signals, and creative opportunities. Use for voice-of-customer research grounded in linked source evidence.

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。

Provider reference for collecting public profiles, posts, comments, transcripts, trends, and ad-library data from major social platforms through ScrapeCreators. Use as a dependency of research workflows, not as the final user-facing deliverable.

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。

Aggregate customer feedback from multiple sources — support tickets, NPS comments, Slack messages, G2 reviews, call transcripts, survey responses — into a unified VoC report with theme clustering, sentiment analysis, trend detection, and actionable recommendations for product, marketing, and CS teams. Chains review-site-scraper for public review 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。

Test product-demand hypotheses using public customer language, search and social signals, competitor offers, reviews, comments, creator content, and social-commerce evidence before committing to a product, launch, offer, or campaign.

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 Hacker News stories and comments using the free Algolia API. No Apify token needed. Use when you need to find HN discussions, track mentions, discover Show HN launches, or monitor tech community sentiment.

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。

Research LinkedIn profiles and write personalized messages for any LinkedIn message type — connection requests, InMails, DMs, message requests, post comments, and comment replies. Takes LinkedIn URLs as input, researches each person (profile data + recent posts via Apify), and generates messages tailored to each lead's background, interests, and recent activity. Exports tool-ready CSVs for Dripify, Expandi, Botdog, PhantomBuster, or generic format. No LinkedIn cookies or login required.

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。