將工程師之間溝通的內容改寫成適合工程組織領導層（如副總裁、總監、技術長、專案經理、發行經理、技術高層）的語言，並根據不同傳遞管道（如 JIRA 留言、Slack 貼文、非同步站立會議紀錄、電子郵件或會議重點）調整格式。
這個 AI 技能能將工程師之間使用的專業技術語言轉換成更適合管理層或高層主管閱讀與理解的版本，並自動根據目標平台（如 JIRA、Slack、Email 或會議重點）調整內容結構與語氣。它特別適用於需要撰寫「高層摘要」、「領導更新」、「狀態報告」或將原始工程師對話改寫成「較不技術性 / 較少術語」的場景。支援的平台包括所有主流協作工具，並透過分析使用者輸入中的關鍵詞（如“for management”、“executive summary”、“make this less technical”）觸發。此技能能顯著節省工程師重新組織語言的時間，確保訊息能精準傳達給非技術背景的決策者。
npx skills add https://github.com/thananon/9arm-skills/tree/main/skills/management-talkInstalled? Explore more 寫作與編輯 skills: steipete/notion, langchain-ai/langchain, bytedance/podcast-generation · View all 6 →
將工程師之間溝通的內容改寫成適合工程組織領導層（如副總裁、總監、技術長、專案經理、發行經理、技術高層）的語言，並根據不同傳遞管道（如 JIRA 留言、Slack 貼文、非同步站立會議紀錄、電子郵件或會議重點）調整格式。當使用者要求為管理層/高層/副總裁/總監/技術長/專案經理/發行經理撰寫或改寫、要求「高層摘要/領導更新/狀態更新」、說「讓它比較不技術性/比較少術語」，或要求將原始工程師之間的工作內容轉換成 Slack/Email/站立會議/會議版本時觸發。
This repo contains 3 individual skills — each has its own dedicated page.
Four-mantra debugging discipline — reproduce, trace the fail path, falsify the hypothesis, cross-reference every breadcrumb. Recite the mantra block verbatim at the start of any debugging session, then apply the four steps in order before proposing any fix. Trigger on /debug-mantra and proactively whenever debugging starts — user reports a bug, says something is broken/throwing/failing, asks to debug/diagnose/investigate an issue, or pastes a stack trace or error log.
Write the canonical engineering record of a fixed bug — root cause, mechanism, fix, validation, and how it slipped through. Engineer-audience, code identifiers welcome. Use after a debug session lands a fix, before closing the ticket. Trigger on /post-mortem, when the user says "write the post-mortem / postmortem / RCA / root cause analysis", "document this fix", "write up the root cause", "close out this bug with a writeup", or hands you a fixed-and-validated bug and asks for the writeup.
Outsider-perspective end-to-end review of a plan, PR, or code change. First questions intent and whether a simpler/more elegant approach would achieve the same goal, then traces the actual code path (not just the diff) to verify the change does what it claims. Output is concise, actionable, and every call carries its rationale. Trigger on /scrutinize and proactively whenever the user asks to review, audit, sanity-check, or get a second opinion on a plan, PR, diff, design doc, or proposed code change.
Notion CLI/API for pages, Markdown content, data sources, files, comments, search, Workers, and raw API calls.
The agent engineering platform.
Use this skill when the user requests to generate, create, or produce podcasts from text content. Converts written content into a two-host conversational podcast audio format with natural dialogue.
Analyze and optimize tweets for maximum reach using Twitter's open-source algorithm insights. Rewrite and edit user tweets to improve engagement and visibility based on how the recommendation system ranks content.
Extracts and analyzes competitors' ads from ad libraries (Facebook, LinkedIn, etc.) to understand what messaging, problems, and creative approaches are working. Helps inspire and improve your own ad campaigns.
Context7 Platform -- Up-to-date code documentation for LLMs and AI code editors