Build a persistent personality profile from everyday AI conversations, stored locally as plaintext JSON.
by dqsjqian32 installs2 stars
Publisher
Skills by dqsjqian
5 published skills, 33 installs in total.
智能体协会（agent-guild）— cross-agent shared memory. 本机多个 AI agent 共享 同一份身份、规则、记忆与交接消息 — 纯本地 Markdown/JSON，无服务器。 触发（任何自然等价表达都算）： · 身份/习惯："我是谁" "我的身份/习惯/偏好" "who am I" "my routine" · 回忆/历史："你记得吗" "之前聊过" "上次我们" "what did we discuss" · 写记忆："帮我记住" "记一下" "沉淀一下" "remember this" "记到日志" · 跨 agent："告诉其他 agent" "交接给" "让 XX 也知道" "hand off to" · 当前状态："现在在做什么" "当前任务/焦点/进度" "current focus" · 数据卫生："整理一下协会" "清理过期数据" "协会瘦身/归档" "防止数据劣化" "groom" "cleanup" "archive old data" · 跨设备："换了台电脑" "另一台机器" "Windows/Linux 上用不了" "这台设备" "这个工具在哪" "cross-device" "another machine" "which platform" · 加入："加入协会" "初始化协会" "join agent guild" "install this skill" 能力：读/写共享身份、规则、焦点；收件箱交接；每日日志；会话闭环 （`ag recall` 检索共享记忆 / `ag finish` 收尾沉淀，3.9.0+）；并发追加 咨询锁防丢写；跨 agent 学习台账 （错误/纠正/特性请求 → 复发追踪 → 晋升为规则或共享 skill）；数据卫生 （bootstrap 后自动 groom 归档过期数据）；跨设备可移植（shared/platform/host 三层作用域，`ag platform` / `ag tool <name>` / `ag port`）； `ag init/adopt/link-root/bootstrap/recall/finish/doctor/groom/upgrade/learn/review/resolve`。 未加入？先跑 docs/ONBOARDING.md。
by dqsjqian1 installs
用「编写 SVG」的方式生成图片——让没有多模态生图能力的模型也能产出任意宽高比、任意复杂度的矢量图，并导出为 SVG / PNG / 动图(GIF/APNG/WebP/MP4)，或内嵌进 HTML。 适用场景：用户要「生成一张图 / 画个图 / 做张配图 / 做海报 / 信息图 / 图表 / 流程图 / 架构图 / 图标 / 封面 / OG 图」，要求指定宽高比(16:9 / 1:1 / 9:16 等)或导出 PNG；也包括「做个动图 / GIF / 加载动画 / loading 动效」。 能力：① 按指令编写复杂 SVG（图表/插画/流程图/海报）；② SVG→PNG 高清渲染(Chrome 优先，cairosvg/resvg 兜底)；③ 多帧/模板 SVG→GIF/APNG/WebP/MP4 动图；④ 任意宽高比与 DPR。 关键词：生图、画图、SVG、矢量图、配图、海报、信息图、图表、流程图、架构图、图标、封面、OG image、转 PNG、动图、GIF、动画、loading。
by dqsjqian
通用「图文笔记发布」框架：把本地 markdown 文案 + 配图，通过你指定的 MCP 发布后端，一键发布为图文笔记（含 note_id 回查）。 只负责登录与发布编排，不碰内容创作；不绑定任何特定平台，后端地址由用户自己配置。 触发词：图文笔记发布、笔记发布、社交笔记发布、登录发布、发布失败重试。
by dqsjqian
AI 八信条（AI Eight Creed）—— 一套最高优先级的 AI 行为守则（八耻八荣）。 任何 AI agent 都应无条件遵循：以瞎猜事实为耻、以查证溯源为荣；以模糊执行为耻、 以澄清边界为荣；以擅自臆断为耻、以人类拍板为荣；以另起炉灶为耻、以沿用现成为荣； 以跳过核验为耻、以闭环自检为荣；以破坏章法为耻、以遵循规范为荣； 以假装理解为耻、以坦白无知为荣；以将错就错为耻、以正本清源为荣。 Triggers: "八耻八荣", "八信条", "AI 行为守则", "遵守守则", "查证溯源", "澄清边界", "人类拍板", "沿用现成", "闭环自检", "遵循规范", "坦白无知", "正本清源", "eight creed", "ai creed", "eight honors and shames", any request involving agent behavior rules or ethical guidelines.
by dqsjqian
About Ottermind skills
Every published skill from dqsjqian. Following a publisher whose work already fits how you operate is often faster than evaluating individual skills one at a time.
Skills cover the full range of what an Ottermind agent does: building editable PowerPoint decks, generating product and brand images, writing and running code on a machine you connect, producing video from a script or a still, and cleaning and analysing spreadsheet data. A skill is what turns a general model into something that handles your specific version of one of those jobs the same way every time.
A skill is a plain Markdown file with a short frontmatter header, which means you can read exactly what it will do before running it, edit it to match your own conventions, and share it with colleagues. Once a skill produces the result you wanted, it can be attached to an agent or scheduled as an automation so the same work happens again without anyone rewriting the prompt.
- What is an Ottermind skill?
- A reusable instruction package written in Markdown. It gives an agent the context, steps, and constraints for one kind of task, so results stay consistent instead of depending on how well you phrased the prompt that day.
- How do I install and use a skill?
- Open any skill's detail page, read the full document, and install it into your workspace. From then on the agent can use it automatically when the task matches, or you can invoke it by name.
- Can I create my own skill?
- Yes. A skill is a Markdown file with frontmatter naming it and describing when it should be used. If you have a workflow you keep re-explaining to an agent, writing it down once as a skill is usually the shortest path to making it repeatable.
- Do skills cost extra?
- Browsing and installing skills from this library does not cost anything on its own. Running one consumes the same credits as any other agent task, depending on the model you choose and how much work the task involves.