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Openclaw mneme vision

作者 Billy Kennedy · GitHub ↗ · v1.0.0 · MIT-0
cross-platform ✓ 安全检测通过
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在 OpenClaw 中安装
/install mneme-vision
功能描述
Use local visual memory tools to index and search photos and videos from creator media libraries.
使用说明 (SKILL.md)

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.
  • timestamp or time_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.

安全使用建议
Install this only if you are comfortable with a local MCP server indexing selected media folders and temporarily storing uploaded media for session use. Review the external mneme-mcp and OpenClaw plugin packages, and avoid indexing sensitive folders unless you explicitly want them searchable.
能力评估
Purpose & Capability
The skill indexes and searches local photo/video libraries, returns local media paths/previews, and manages GPU/Ollama memory; these capabilities match its stated visual-memory purpose but involve private local media.
Instruction Scope
Runtime instructions limit durable indexing to explicit user requests and say not to upload media to cloud services unless separately requested; README also says uploaded media is saved to a local inbox as temporary session context, but retention details are not specified.
Install Mechanism
The artifact itself contains only markdown and JSON, but installation depends on an external MCP server via mcporter/uvx and an OpenClaw plugin package, so users should trust those external components separately.
Credentials
Local file access, media indexing, preview generation, and GPU memory controls are proportionate for local visual search and creator media workflows.
Persistence & Privilege
The skill can create durable local visual-memory indexes when asked and temporarily store uploaded media locally; no hidden persistence, background worker, credential access, or exfiltration behavior appears in the skill artifacts.
如何使用
  1. 确保已安装 OpenClaw(本地或 Docker 部署)
  2. 在对话框中输入安装命令:/install mneme-vision
  3. 安装完成后,直接呼叫该 Skill 的名称或使用 /mneme-vision 触发
  4. 根据 Skill 的参数说明提供必要输入,即可获得结构化输出
版本历史
v1.0.0
Initial release of mneme-vision skill. - Enables local indexing and search of photo and video libraries. - Supports natural-language and visual similarity search across media. - Handles GPU status and memory management for intensive workflows. - Returns media results as rich content cards when supported. - Ensures strong privacy: does not upload media to cloud unless explicitly requested.
元数据
Slug mneme-vision
版本 1.0.0
许可证 MIT-0
累计安装 0
当前安装数 0
历史版本数 1
常见问题

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。

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