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.
- Make sure OpenClaw is installed (local or Docker)
- Run the install command in chat:
/install mneme-vision - After installation, invoke the skill by name or use
/mneme-vision - Provide required inputs per the skill's parameter spec and get structured output
What is Openclaw mneme vision?
Use local visual memory tools to index and search photos and videos from creator media libraries. It is an AI Agent Skill for Claude Code / OpenClaw, with 40 downloads so far.
How do I install Openclaw mneme vision?
Run "/install mneme-vision" in the OpenClaw or Claude Code chat to install it in one step — no extra setup required.
Is Openclaw mneme vision free?
Yes, Openclaw mneme vision is completely free, licensed under MIT-0. You can download, install and use it at no cost.
Which platforms does Openclaw mneme vision support?
Openclaw mneme vision is cross-platform and runs anywhere OpenClaw / Claude Code is available (cross-platform).
Who created Openclaw mneme vision?
It is built and maintained by Billy Kennedy (@bkennedyshit); the current version is v1.0.0.