communication
通过集成渠道撰写面向人类的文字时加载,包括聊天消息、审查评论、合并请求描述、邮件、文档正文和工单描述。包含 AI 作者身份归属规则。
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Load when composing human-facing prose through an integration — chat messages, review comments, merge request descriptions, emails, doc bodies, ticket descriptions. Carries the AI-authorship attribution rule.
适用对象:对象待分类。自动收录 · 待核查。
原作者说明节选
从固定版本的 SKILL.md 提取,保留原文语言。以下内容属于作者说明,本站尚未验证安装、兼容或运行结果。
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原文涵盖的主题
- Concision
- Voice
- Rollout announcements
- AI-authorship marker
Use Mnemopi recall for relevant agent-learned context. For authoritative collected facts, citations, or source verification, use OMP’s vault:// interface; never substitute memory, CQ, or direct backing-file access for the vault. For external communications—including initial issue/proposal bodies and replies—lead with the main point and keep the default short. For longer messages, use Minto Pyramid framing: conclusion first, grouped reasons next, supporting evidence last. For complex proposals, use an issue tree to group non-overlapping concerns, cover necessary scope, and prioritize high-impact branches; omit speculative branches and low-value detail. Keep the problem, recommendation, essential tradeoffs/evidence, and decision needed; cut repetition and tangents. Expand only for accuracy or when requested. Sound like a direct, relaxed colleague, not a formal announcement template. Prefer plain language, contractions, and short paragraphs; use warmth sparingly and naturally. Lead with the outcome or the specific question. Keep Slack updates especially brief; include only the context needed to understand the change or respond. Make status, uncertainty, risk, and the requested next st
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- 来源仓库
- athal7/dotfiles
- 源文件
- dot_agents/skills/communication/SKILL.md
- 固定版本
- 020f267ef55d4b97fc32c63bd9c077f9395faf9e
来源与内容状态
本条为自动发现的元数据,尚未完成人工文档核查;适用性与运行结果待核查。
原作者:athal7/dotfiles · 原作者仓库元数据。文档核查:未核查。最近来源检查:2026-11-10T02:00:28.592Z。
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