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Agent Skill · 研究检索

luci-memory(露西记忆)

luci-memory 用于查找、检索和筛选相关信息,适合在 OpenClaw 中需要根据关键词、任务场景或来源线索快速定位候选结果时使用。可结合来源仓库、安装命令和原始 README 继续核验具体用法。安装前建议确认权限范围、维护状态,以及是否会触发联网、命令执行或文件读写。

luci-memory 是研究检索类 Agent Skill,可用宿主为 OpenClaw,通过ClawHub获取,权限为需要联网;许可证为 MIT-0,第三方扫描已通过,按安装量在研究检索类的 73,675 个 Skill 里排第 13,921。

总安装 8,986周安装 360GitHub Stars 公开资料未说明下载 2,909核验 2026-05-01

安装说明

本站只整理中文说明,不托管安装包,也不代用户安装。
GitHub
许可证
MIT-0
版本
1.0.6

安装方式

通过对话安装

复制提示词发给支持本地命令或 Skills 的 AI 助手,先确认命令和权限,再让它执行。

请帮我安装这个 Agent Skill:luci-memory(露西记忆)
来源仓库:https://github.com/gimlettt/luci-memory
安装命令:
openclaw skills install luci-memory
安装前请先检查当前环境是否支持对应 CLI,并向我确认将要执行的命令、安装目录、联网范围和文件读写权限;确认后再执行。

命令行安装

复制命令到本机终端执行。该命令会通过 OpenClaw 从第三方来源获取 Skill;本站只展示命令,不托管安装包,也不自动执行。

ClawHubOpenClaw
openclaw skills install luci-memory

这个 Skill 是做什么的

研究检索类 Skill 主要解决「找资料、核对事实、把来源整理清楚」的问题,通常会让助手先检索再总结。

luci-memory 用于搜索个人视频记忆库,包括媒体内容和特征数据。适合回顾历史记录、分析行为模式或提取关键事件信息的场景。支持按时间、标签或语义关键词检索,整合图像、语音和文本元数据。安装需授权访问本地媒体文件,建议检查存储路径和网络传输安全性。注意隐私保护,避免在未加密环境下处理敏感视听资料。

上手步骤

4 步
  1. 1

    确认自己的宿主工具

    公开资料标注支持 OpenClaw;先确认自己用的是其中之一,再按对应工具的 Skills 目录放置。

  2. 2

    拿到安装命令

    可以直接复制的命令是 openclaw skills install luci-memory;命令里的占位符换成自己的路径或密钥再执行。

  3. 3

    安装后重启宿主

    命令执行完要完全退出宿主工具再打开,让新装的 Skill 被重新扫描到,否则列表里可能看不到。

  4. 4

    按最小权限试用

    它需要需要联网,先在测试目录或测试账号里跑,确认没问题再放到正式项目。

常见问题

6 条

luci-memory 怎么安装?

在终端执行 openclaw skills install luci-memory。装完完全退出宿主工具再打开,让它重新扫描本地 Skill。

luci-memory 支持哪些 AI 工具?

公开资料标注支持 OpenClaw。其他工具只要能读取本地 Skill 目录,一般也能手动放进去,但要自己确认触发方式是否一致。

luci-memory 需要什么权限?

权限级别是需要联网。该 Skill 可能需要联网访问来源站点、仓库或外部 API;具体网络访问范围需要结合源码和 README 复核。

luci-memory 是免费的吗?

来源标注的许可证是 MIT-0。本站不代收任何费用,也不托管安装包;能否商用、要不要署名,以许可证原文为准。

luci-memory 用的人多吗?

公开数据是累计安装 8,986 次,近一周安装 360 次,下载 2,909 次。这些数字来自第三方目录统计,只能当作热度参考,不代表质量或安全性。

luci-memory 安全吗?

第三方扫描结果为通过,但这只覆盖已知的静态检查项,不能替代自己读一遍源码和安装命令。

值得选的地方和要先想清楚的地方

值得选的地方

  • 专注 OpenClaw 一种宿主,触发方式和使用习惯不用来回切换。
  • 许可证明确为 MIT-0,商用和分发边界好判断。
  • 第三方扫描已通过,常见的高风险行为没有命中。

先想清楚的地方

  • 第三方目录整理,版本更新和行为细节以来源仓库为准。

适不适合你

更适合

  • 已经在用 OpenClaw,想直接扩展它能力的人。
  • 需要处理研究检索类任务、又不想每次都手写提示词的人。
  • 需要许可证清楚、并且有第三方扫描结果的团队项目。

不太适合

  • 需要厂商级技术支持和 SLA 的生产系统。

研究检索类 Skill 对比

6 个同类
Skill总安装GitHub 星权限许可证扫描
find-skills

寻找技能 · Codex、Claude

31,199,81316,486操作浏览器MIT有提醒
self-improving-agent

自我改进 Agent · OpenClaw

16,464,0023,396接触敏感数据MIT-0通过
soultrace

灵魂追踪 · Codex、Claude

7,588,94412需要联网未明确有提醒
self-improving

自我完善 · OpenClaw

6,829,2841,046需要联网MIT-0通过
microsoft-foundry

微软代工厂 · Codex、Claude

6,614,144764调用外部服务未明确有提醒
luci-memory

露西记忆 · 本页

8,986—需要联网MIT-0通过

按安装量取同分类前几名;数字来自第三方目录统计,只作热度参考,不代表质量结论。

SKILL.md 原文

name
luci-memory
description
Search personal video memory — media content (videos, images, keyframes, transcripts) and portrait data (traits, events, relationships, speeches). Use when the user asks about their videos, what happened, what was said, who they know, or their personality.
metadata
{"clawdbot":{"emoji":"🧠","requires":{"bins":["python3"],"env":["MEMORIES_AI_KEY"]},"primaryEnv":"MEMORIES_AI_KEY"}}

luci-memory

Setup

Requires an MEMORIES_AI_KEY. On first use, if no key is found, the script will error and ask for one.

When the user provides their key, save it to {baseDir}/.env:

MEMORIES_AI_KEY=sk-their-key-here

After that, everything just works — the key is loaded automatically from .env on every run.

Timezone

All timestamps in Luci-memory are stored and returned in UTC. Skill output labels them with " UTC" so this is unambiguous. The user's local timezone is in USER.md (e.g. Asia/Shanghai). You are responsible for converting in both directions:

  1. Reading results. When presenting captured_time to the user, convert from UTC to the user's local timezone. Never show raw UTC labels to the user.
  1. Writing filters. --after and --before are interpreted as UTC. If the user says relative dates like "yesterday" or "this morning", convert their local-time intent to a UTC range before passing the dates.

Example (user in Asia/Shanghai, UTC+8, asks "what did I do yesterday" on 2026-04-08):

  • Local intent: 2026-04-07 00:00 → 2026-04-08 00:00 (Asia/Shanghai)
  • UTC range to pass: --after 2026-04-06T16:00:00 --before 2026-04-07T16:00:00

If USER.md has no timezone and the user uses relative dates, ask them first.

Unified search across personal media and portrait data from the Luci-memory API.

The user's videos go through two processing pipelines that produce different data:

  • Media content (personal): video summaries, audio transcripts, visual transcripts, keyframes, images
  • People & knowledge (portrait): traits, events with participants, relationships, speeches attributed to speakers

When to use

  • User asks to find or search videos, images, or photos
  • User asks what was said or shown in a video
  • User asks to list recent videos or images
  • User asks about media at a specific location or time
  • User asks about traits, personality, hobbies, interests
  • User asks what events happened, or events involving specific people
  • User asks about relationships between people
  • User asks about what someone said
  • User mentions "luci memory" or wants to use their video memory

Choosing the right type

  • About content (what happened, what was said/shown, find media) → use media types (search_video, query_audio, etc.)
  • About people (who, traits, relationships, named individuals) → use portrait types (traits, events, speeches, etc.)
  • Ambiguous questions like "What happened with Alice last week?" → use both: portrait types to identify the person and events, media types to get detailed video content and transcripts.
  • Person name fallback: Portrait data only exists for people who have appeared in at least 5 videos AND been named by the user in the app. If a portrait query by person name returns no results, fall back to media types — search video summaries, audio transcripts, or visual transcripts for mentions of that name instead.

Relevance guidelines

  • There is no rerank process — retrieved results may contain items irrelevant to the user's actual intent.
  • Always verify relevance: after receiving results, check each item against the user's original query. Only present results that are relevant. Discard anything that doesn't match.
  • Refine and retry: if results seem off or too broad, retry with a more specific query, narrower date range, or additional filters. Do not just dump low-quality results to the user.
  • Ask the user: if the query is ambiguous or too vague to produce good results, ask the user for more specific conditions before searching. It is better to clarify than to return noise. Do this no more than 1 time.

No hallucination — ground every claim in retrieved data

  • Never fabricate what the user did, said, or experienced. Every detail in your answer must come from actual search results.
  • Multi-step retrieval: for questions like "what did I do and say at XXX", do NOT answer from a single broad search. Follow this pattern:

1. Locate: search broadly (search_video, search_events) to find relevant video_ids or event_ids. 2. Retrieve: once you have IDs, prefer query_audio / query_visual with --video-ids to get complete transcripts. You can also use search_audio / search_visual scoped to those video IDs to find specific moments — use both flexibly as needed.

  • Do not stuff keywords into search queries. Each semantic search query should be a short, coherent natural-language query, rather than stacking multiple possible words. You are encouraged to try different ones and query various times though.
  • If data is missing, say so. Do not fill gaps with plausible-sounding guesses. "I couldn't find transcript data for that video" is always better than making something up.

How to invoke

Note: --after / --before are UTC. Convert from the user's local timezone first (see Timezone section above).

Returning Images/Keyframes to User

When search results include signed URLs (keyframes, images), follow this pipeline to send them in chat:

  1. Download the signed URL to the workspace:
   curl -sL -o /path/to/workspace/image.jpg "<signed_url>"
  1. Send via OpenClaw message CLI:

openclaw message send --channel <channel> --target <chat_id> --media /path/to/workspace/image.jpg --message "caption"

  1. Cleanup the file after sending:

rm /path/to/workspace/image.jpg ⚠️ Signed URLs expire after ~1 hour. Download promptly. ⚠️ Do NOT use /tmp or paths outside the workspace — some tools block external paths. ⚠️ The image tool only analyzes images — it cannot send them to the user. Use openclaw message send --media instead.

============ Media content (personal) ============

--- Video ---

bash {baseDir}/run.sh --query "cooking in kitchen" --type search_video bash {baseDir}/run.sh --query "what did I do" --type search_video --location "Heze" bash {baseDir}/run.sh --query "meeting" --type search_video --after 2025-12-01 --before 2026-01-01 bash {baseDir}/run.sh --type query_video bash {baseDir}/run.sh --type query_video --location "Suzhou" --after 2025-12-01

--- Image ---

bash {baseDir}/run.sh --query "sunset" --type search_image bash {baseDir}/run.sh --query "food" --type search_image --location "Beijing" bash {baseDir}/run.sh --type query_image

--- Audio Transcripts (what was said) ---

bash {baseDir}/run.sh --query "talking about work" --type search_audio bash {baseDir}/run.sh --query "budget" --type search_audio --video-ids VI123,VI456 bash {baseDir}/run.sh --type query_audio --video-ids VI123,VI456

--- Visual Transcripts (what was shown) ---

bash {baseDir}/run.sh --query "walking in park" --type search_visual bash {baseDir}/run.sh --type query_visual --video-ids VI123,VI456

--- Keyframes ---

bash {baseDir}/run.sh --query "person waving" --type search_keyframe bash {baseDir}/run.sh --type query_keyframe --video-ids VI123,VI456

============ People & knowledge (portrait) ============

--- Traits ---

bash {baseDir}/run.sh --type traits bash {baseDir}/run.sh --type traits --person "Alice" bash {baseDir}/run.sh --query "outdoor activities" --type search_traits

--- Events ---

bash {baseDir}/run.sh --type events bash {baseDir}/run.sh --type events --person "Alice" bash {baseDir}/run.sh --type events --person "Alice,Bob" bash {baseDir}/run.sh --type events --after 2025-12-01 --before 2026-01-01 bash {baseDir}/run.sh --query "cooking in kitchen" --type search_events bash {baseDir}/run.sh --query "meeting" --type search_events --person "Bob" --after 2025-12-01

--- Relationships ---

bash {baseDir}/run.sh --type relationships bash {baseDir}/run.sh --type relationships --person "Alice"

--- Speeches ---

bash {baseDir}/run.sh --type speeches bash {baseDir}/run.sh --type speeches --person "Alice" bash {baseDir}/run.sh --type speeches --event-ids EVT123,EVT456 bash {baseDir}/run.sh --type speeches --person "Alice" --event-ids EVT123


## Parameters

| Flag | Short | Description |
|------|-------|-------------|
| `--query` | `-q` | Search term (required for `search_*` types) |
| `--type` | `-t` | Operation type (default: `search_video`) |
| `--top-k` | `-k` | Max results (default: 10) |
| `--location` | `-l` | Filter by location name, geocoded via Google Maps (e.g. "Suzhou") |
| `--after` | | Only results after this date (`YYYY-MM-DD` or `YYYY-MM-DDTHH:MM:SS`) |
| `--before` | | Only results before this date |
| `--video-ids` | | Comma-separated video IDs (media types) |
| `--person` | `-p` | Filter by person name(s), comma-separated (portrait types). Use `user` for self. |
| `--event-ids` | | Comma-separated event IDs (portrait types) |

## Signed URLs

Image and keyframe results include a `signed_url` field — a temporary (1-hour) direct link to view/download from Google Cloud Storage. No authentication needed, but they expire after 1 hour.

## Types reference

### Media search types (require `--query`)
| Type | What it searches | Supports |
|------|-----------------|----------|
| `search_video` | Video summaries by meaning | `--location`, `--after/before` |
| `search_image` | Image descriptions by meaning | `--location`, `--after/before` |
| `search_audio` | Audio transcripts by meaning | `--video-ids`, `--after/before` |
| `search_visual` | Visual transcripts by meaning | `--video-ids`, `--after/before` |
| `search_keyframe` | Keyframe images by meaning | `--video-ids`, `--after/before` |

### Media query types (list/filter)
| Type | What it returns | Requires | Supports |
|------|----------------|----------|----------|
| `query_video` | Recent videos | — | `--location`, `--after/before` |
| `query_image` | Recent images | — | `--location`, `--after/before` |
| `query_audio` | Audio transcripts for videos | `--video-ids` | `--after/before` |
| `query_visual` | Visual transcripts for videos | `--video-ids` | `--after/before` |
| `query_keyframe` | Keyframes for videos | `--video-ids` | `--after/before` |

### Portrait query types (list/filter)
| Type | What it returns | Supports |
|------|----------------|----------|
| `traits` | Personality traits, hobbies, interests | `--person` |
| `events` | Events with participants | `--person`, `--after/before`, `--event-ids` |
| `relationships` | How user relates to people | `--person` |
| `speeches` | What people said | `--person`, `--event-ids` |

### Portrait search types (semantic, require `--query`)
| Type | What it searches | Supports |
|------|-----------------|----------|
| `search_events` | Events by meaning | `--person`, `--after/before` |
| `search_traits` | Traits by meaning | — |

平台分布

OpenClaw

87.07%
按下载量换算2,533

安全审计

VirusTotal

通过

ClawScan

通过

Static analysis

通过

权限和风险

需要联网

该 Skill 可能需要联网访问来源站点、仓库或外部 API;具体网络访问范围需要结合源码和 README 复核。

安装前确认

本站仅展示第三方公开信息,不托管安装包,不提供自动安装或运行环境。安装前应自行审查源码、依赖和命令行为。目前只有一个公开来源,建议同时核对源仓库。

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