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lorelore 搜索

Agent Skill

lore 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。

总安装

42,494

周安装

1,719

GitHub Stars

公开资料未说明

下载量

13,339
OpenClaw

安装说明

本站只整理中文说明和来源信息,不托管安装包,也不代用户安装。

GitHub

来源数

2

许可证

MIT-0

最后核验

2026-05-01

来源状态

来源可访问

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:lore(lore 搜索)
来源仓库:https://github.com/mishkinf/lore
安装命令:
openclaw skills install lore
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 lore

简介

从 Lore 研究存储库中搜索和获取带引文的知识内容。

  • 适用于 OpenClaw 中进行学术资料、研究报告或文献检索的场景。
  • 提供结构化知识提取与引用溯源,支持深度研究任务辅助。
  • 通过 clawhub 安装,需确认是否允许联网抓取外部数据库资源。
  • 建议核查数据更新频率、授权范围及内容准确性后再用于正式分析。

SKILL.md

name
lore
description
Search and ingest knowledge from Lore, a research repository with citations
version
1.0
user-invocable
false

Lore Knowledge Base

Lore is a research knowledge repository you have access to via MCP tools. It stores documents, meeting notes, interviews, and decisions with full citations — not just summaries, but the original content linked back to its source. Use it to ground your answers in evidence and to preserve important context from your conversations.

When to Ingest Content into Lore

Push content into Lore using the ingest tool whenever you encounter information worth preserving:

  • After conversations: When a user shares meeting notes, interview transcripts, or important documents, ingest them so they're searchable later.
  • External content: When you fetch content from Slack, Notion, GitHub, email, or other systems, ingest the relevant parts into Lore.
  • Decisions and context: When important decisions are made or context is shared that future conversations will need.

Always include:

  • source_url: The original URL (Slack permalink, Notion page URL, GitHub issue URL) for citation linking.
  • source_name: A human-readable label like "Slack #product-team" or "GitHub issue #42".
  • project: The project this content belongs to.

Ingestion is idempotent — calling ingest with the same content twice is safe and cheap (returns immediately with deduplicated: true).

When to Search Lore

Before answering questions about past decisions, user feedback, project history, or anything that might already be documented:

  1. Use search for quick lookups. Pick the right mode:

- hybrid (default): Best for most queries - keyword: For exact terms, names, identifiers - semantic: For conceptual queries ("user frustrations", "pain points")

  1. Use research only when the question requires cross-referencing multiple sources or synthesizing findings. It costs 10x more than search — don't use it for simple lookups.
  1. Use get_source with include_content=true when you need the full original text of a specific document.

When to Retain Insights

Use retain (not ingest) for short, discrete pieces of knowledge:

  • Key decisions: "We chose X because Y"
  • Synthesized insights: "3/5 users mentioned Z as their top issue"
  • Requirements: "Must support SSO for enterprise"

Citation Best Practices

When presenting information from Lore, always cite your sources:

  • Reference the source title and date
  • Quote directly when possible
  • If a source_url is available, link to the original

Example Workflows

User asks about past decisions:

  1. search("authentication approach decisions", project: "my-app")
  2. Review results, get full source if needed: get_source(source_id, include_content: true)
  3. Present findings with citations

User shares meeting notes:

  1. ingest(content: "...", title: "Sprint Planning Jan 15", project: "my-app", source_type: "meeting", source_name: "Google Meet", participants: ["Alice", "Bob"])
  2. Confirm ingestion to user

User asks a broad research question:

  1. research(task: "What do users think about our onboarding flow?", project: "my-app")
  2. Present the synthesized findings with citations

适合场景

01

OpenClaw 用户查找和安装 Skill 时

02

用户想查找某类 Agent Skill 时

03

需要根据任务场景推荐可安装能力包时

04

需要对比不同来源的安装命令和来源信息时

能力概览

能力 1

按任务关键词查找相关 Skills

能力 2

展示可复制的安装命令

能力 3

保留来源站点、仓库和原始说明,方便继续核验

能力 4

补充不同宿主或平台的使用分布数据

能力 5

展示第三方安全扫描或审计结果

安装后应在对应宿主中按原始 README 的触发条件使用;具体调用方式请以来源页面和 README 为准。

平台分布

OpenClaw

96.56%
按下载量换算12,880

安全审计

VirusTotal

通过

ClawScan

通过

Static analysis

未展示

权限和风险

external-service

该 Skill 可能调用第三方服务、云服务或外部模型 API,使用前需要确认账号、额度、数据发送范围和服务条款。

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。当前只有一个来源,正式发布前建议补源仓库或其他目录站核验。

来源信息

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