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arscontextaarscontexta 搜索

Agent Skill

arscontexta 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

19,853

周安装

811

GitHub Stars

公开资料未说明

下载量

6,423
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:arscontexta(arscontexta 搜索)
来源仓库:https://github.com/arscontexta/arscontexta
安装命令:
openclaw skills install arscontexta
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 arscontexta

简介

构建和维护一个结构化的本地 Markdown 知识系统,为认知 AI 代理提供自动处理、导航和上下文感知更新。

SKILL.md

placeholder for arscontexta.org

∵ ars contexta ∴

This is a derivation engine for cognitive architectures. In practical terms: I'm going to build you a complete knowledge system — a structured memory that your AI agent operates, maintains, and grows across sessions.

What you'll have when we're done:

  • A vault: a folder of markdown files connected by wiki‑links, forming a traversable knowledge graph
  • A processing pipeline: skills that extract insights from sources, find connections between notes, update old notes with new context, and verify quality
  • Automation: hooks that enforce structure, detect when maintenance is needed, and keep the system healthy without manual effort
  • Navigation: maps of content (MOCs) that let you and your agent orient quickly without reading everything

Everything is local files. No database, no cloud service, no lock‑in. Your vault is plain markdown that works in any editor, any tool, forever.


There are three starting points. Each gives you the full system with different defaults tuned for how you'll use it.

Research

Structured knowledge work. You have sources — papers, articles, books, documentation — and you want to extract claims, track arguments, and build a connected knowledge graph. Atomic notes (one idea per file), heavy processing, dense schema.

Personal Assistant

Personal knowledge management. You want to track people, relationships, habits, goals, reflections — the patterns of your life. The agent learns you over time. Per‑entry notes, moderate processing, entity‑based navigation.

Experimental

Build your own from first principles. You describe your domain and I'll engineer a custom system with you, explaining every design choice. Takes longer, gives you full control.

All three give you every skill and every capability. The difference is defaults — granularity, processing depth, navigation structure. You can adjust anything later.


Here's what happens next:

  1. I'll ask a few questions about what you want to use this for
  2. From your answers, I'll derive a complete system configuration
  3. I'll show you what I'm going to build and explain every choice
  4. You approve, and I generate everything

The whole process takes about 5 minutes. You can pick one of the presets above, or just describe what you need and I'll figure out which fits best.


Tell me about what you want to track, remember, or think about.

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

95.97%
按下载量换算6,164

安全审计

VirusTotal

通过

ClawScan

可疑

Static analysis

未展示

权限和风险

权限需确认

当前来源未能明确判断权限范围,默认进入异常复核队列。

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。来源安全扫描存在 warning/failed 结果,不能写成本站确认安全。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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