Openclaw mneme vision
/install mneme-vision
Visual Memory
Use this skill when the user wants to index, search, organize, or inspect local photo and video libraries.
When the user provides an uploaded photo/video/reel as an attachment, treat it
as temporary session context first. Use its local path to answer the current
question or run visual similarity search when appropriate. Do not call
media_index or otherwise add the attachment to durable visual memory unless
the user explicitly asks to add, save, index, catalog, or remember it.
Prefer media_index when the user points at a folder that has not been indexed.
Prefer media_search for natural-language searches such as finding shots,
finished videos, thumbnails, archive images, or clips matching a description.
Prefer media_search_by_image when the user provides an image and wants visually
similar items. Use media_describe when the user asks what is in a specific
media file.
Use gpu_status before GPU-heavy local tasks when the user is coordinating
video work, image generation, upscaling, VLM tagging, or another local model
process. Use gpu_release to unload resident Ollama models and hand VRAM to
that workflow, and use gpu_reclaim with the returned token when the workflow
is done. Use gpu_evacuate only when the user asks to free VRAM immediately
without creating a lease.
Return media results as previewable content cards when the host supports rich output. Each result should include:
title: filename or human-readable clip name.kind: image, video, audio, or unknown.path: absolute local path, kept available for copy/reveal actions.reason: short explanation for why this media matched.timestamportime_range: when available for video/audio hits.preview: true when the file can be rendered by the host UI.
Mneme returns neutral media_artifacts.v1 JSON. Preserve the host application's
native styling; do not introduce custom colors, cards, gradients, or branding
unless the host already provides that UI.
Do not dump long bare paths as the main answer. Put the path behind a Copy path
or equivalent action when rich output is available, and show the user the actual
image/video/audio preview first. When rich output is not available, use concise
Markdown links or a compact table with path values.
Do not invent matches when the tool returns none.
Do not upload local media to a cloud service unless the user explicitly asks for that separate action.
- 确保已安装 OpenClaw(本地或 Docker 部署)
- 在对话框中输入安装命令:
/install mneme-vision - 安装完成后,直接呼叫该 Skill 的名称或使用
/mneme-vision触发 - 根据 Skill 的参数说明提供必要输入,即可获得结构化输出
Openclaw mneme vision 是什么?
Use local visual memory tools to index and search photos and videos from creator media libraries. 它是一个面向 Claude Code / OpenClaw 的 AI Agent Skill 插件,目前累计下载 40 次。
如何安装 Openclaw mneme vision?
在 OpenClaw 或 Claude Code 对话框中运行命令「/install mneme-vision」即可一键安装,无需额外配置。
Openclaw mneme vision 是免费的吗?
是的,Openclaw mneme vision 完全免费,采用 MIT-0 许可证,可自由下载、安装和使用。
Openclaw mneme vision 支持哪些平台?
Openclaw mneme vision 跨平台运行,可在任意部署了 OpenClaw / Claude Code 的环境中使用(cross-platform)。
谁开发了 Openclaw mneme vision?
由 Billy Kennedy(@bkennedyshit)开发并维护,当前版本 v1.0.0。