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Agent Skill · 研究检索

llm-wiki-skill(LLM wiki 技能)

llm-wiki-skill 用于查找、检索和筛选相关信息,适合在 Codex、Claude、Cursor、Gemini CLI 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。

llm-wiki-skill 是研究检索类 Agent Skill,可用宿主为 Codex、Claude、Cursor、Gemini CLI,通过GitHub 仓库获取,权限为只读;许可证信息还不明确,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 43,584。

总安装 974周安装 41GitHub Stars 21下载 341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
unknown

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:llm-wiki-skill(LLM wiki 技能)
来源仓库:https://github.com/aaronoah/llm-wiki-skill
仓库路径:skills/llm-wiki-skill
安装命令:
npx skills add https://github.com/aaronoah/llm-wiki-skill --skill llm-wiki-skill
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 npx skills 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。

skills.shnpx skills
npx skills add https://github.com/aaronoah/llm-wiki-skill --skill llm-wiki-skill

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。

llm-wiki-skill 用于持续构建和维护一个由相互链接的 markdown 文件组成的知识库。适合在创建、维护或查询知识库时,对原始内容进行收集、去重、交叉引用和结构化总结。通过 CLI 命令安装,需确认权限范围和维护状态,避免触发不必要的联网或文件操作。

安装前建议检查仓库维护状态,以及是否会执行命令或读写文件,确保符合使用场景。可结合来源仓库和 README 进一步核验具体用法和功能边界。

来源仓库内路径:skills/llm-wiki-skill

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 Codex、Claude、Cursor、Gemini CLI;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 npx skills add https://github.com/aaronoah/llm-wiki-skill --skill llm-wiki-skill;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

    它标注为只读,先用只读任务试一次,确认行为符合预期再扩大使用范围。

常见问题

6 条

llm-wiki-skill 怎么安装?

在终端执行 npx skills add https://github.com/aaronoah/llm-wiki-skill --skill llm-wiki-skill。装完完全退出宿主工具再打开,让它重新扫描本地 Skill。

llm-wiki-skill 支持哪些 AI 工具?

公开资料标注支持 Codex、Claude、Cursor、Gemini CLI。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。

llm-wiki-skill 需要什么权限?

权限级别是只读。该 Skill 主要提供规则、说明或参考内容,本身偏只读;真正读写文件、联网或执行命令仍取决于宿主 Agent 的任务。

llm-wiki-skill 是免费的吗?

公开资料没有标注明确许可证,收费和商用限制都无法确认。正式使用前请到来源仓库核对授权说明。

llm-wiki-skill 用的人多吗?

公开数据是累计安装 974 次,近一周安装 41 次,下载 341 次,GitHub 21 星。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。

llm-wiki-skill 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

  • 同时适配 4 种工具,换客户端不用重新找替代品。
  • 第三方扫描已通过,常见的高风险行为没有命中。
  • 标注为只读权限,试用阶段不容易误改本地文件。

先想清楚的地方

  • 许可证没有明确标注,能不能商用、能不能再分发都不确定。
  • 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 Codex,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。
  • 只想先试试效果、不希望它改动本地文件的人。

不太适合

  • 需要明确授权才能用到公司项目里的场景。
  • 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
llm-wiki-skill

LLM wiki 技能 · 本页

97421只读未明确通过

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

LLM Wiki Skill

Continuously update and grow a persistent knowledge base composed of interlinked markdown files. Raw contents are curated by humans and the agent uses this skill to collect, dedupe, cross-reference and summarize raw contents into structured markdown files. This skill is activated when the user wants:

  • Create, or start a wiki or knowledge base
  • Ingest, add, or process original content into a wiki
  • Asks questions about a wiki or knowledge base
  • Lint, audit, or health-check the wiki, make sure they are in good shape

Quick Start

Directory Structure

Below is a sample wiki directory structure:

llm-wiki/               # Layer 0: the root level wiki folder name
├── SCHEMA.md           # Layer 3: A document for User and LLM to co-evolve the wiki conventions, structure of wiki and tag taxonomy
├── index.md            # Always exists, regardless of SCHEMA.md definition. Catalog of everything, organizaed by categoies (entities, concepts etc), each page listed with a link and a one-line summary
├── log.md              # Always exists, regardless of SCHEMA.md definition. Chronological action log (append-only, rotated yearly)
├── raw/                # Layer 1: Always exists, regardless of SCHEMA.md definition. Immutable content curated by humans
│   ├── documents/      # Web articles, clippings, PDFs
│   └── assets/         # Images, diagrams referenced by sources
├── generated/          # Layer 2: Always exists, regardless of SCHEMA.md definition. LLM-generated directories and markdown files
│   ├── entities/       # Always exists, regardless of SCHEMA.md definition. Entity pages (people, orgs, products, models)
│   ├── topics/         # Always exists, regardless of SCHEMA.md definition. Topic pages (concepts, terms)
│   ├── comparisons/    # Side-by-side analysis (between entities or between topics)

3 layers will be explained in next secion. The Wiki or the knowledge base is built using above structure, user can ONLY apply this skill when the CLI agent (Codex, Claude Code, Gemini etc) is invoked at the llm-wiki/ (or user customized folder name) folder root level given that agents have scoped file-system permissions, that means there should be SCHEMA.md, index.md, log.md and raw/, generated/ folders underneath. If user invokes CLI agent anywhere else inside the wiki subfolders this skill will abort.

index.md Template

The index is sectioned by type. Each entry is one line: wikilink + summary.

# Wiki Index

> Format: `## Last Updated: [YYYY-MM-DDThh:mm:ss] | subject | Total pages: N`
> Subject: the term (entity/topic/comparison etc)
> Total pages: how many pages the term is brought up

## Entities
<!-- Alphabetical within section -->

## Topics

## Comparisons

log.md Template

# Log File

> Format: `## [YYYY-MM-DDThh:mm:ss] action | subject | files`
> Actions: ingest, update, lint, archive, delete
> Subject: the summary of what happened within 300 characters
> Files: related files such as raw documents locations, generated wikis
> When log.md exceeds 500 entries, rotate: rename to log-YYYY.md, start fresh.

SCHEMA.md Template

Adapt to the user's preference. The schema constrains agent behavior and ensures consistency:

# Wiki Schema

## Conventions
- Raw files can be broken down to several markdown files that live in `entities/`, `topics/` etc.
- Only create the wiki pages when an entity/topic is mentioned in 2+ sources or is central to one source.
- File names: lowercase, hyphens, no spaces (e.g., `transformer-architecture.md`)
- Every wiki page starts with YAML frontmatter (see below)
- Use `[[wikilinks]]` to cross-link between pages (minimum 2 outbound links per page)
- Every new or updated page must link to at least 2 other pages via `[[wikilinks]]`.
- When updating a page, always bump the `updated` date
- When new information conflicts with existing content:
   1. Check the dates — newer sources generally supersede older ones
   2. If genuinely contradictory, note both positions with dates and sources
   3. Mark the contradiction in frontmatter: `contradictions: [page-name]`
   4. Flag for user review

## Frontmatter
>  ---
>  title: Page Title
>  created: YYYY-MM-DDThh:mm:ss
>  updated: YYYY-MM-DDThh:mm:ss
>  type: entity | topic | comparison
>  sources: [raw/documents/source-name.md]
>  ---

## Layer 1 (User can specify, otherwise default to this file)

### Documents
Any single document in different formats user put in

### Assets
Any media files, images, video links etc.

## Layer 2 (User can specify, otherwise default to this file)

### Entities
One markdown page per notable entity. Include:
- Overview / what it is
- Key facts and dates
- Relationships to other entities ([[wikilinks]])
- Source references

### Topics
One markdown page per concept or topic. Include:
- Definition / explanation
- Current state of knowledge
- Open questions or debates
- Related concepts ([[wikilinks]])

### Comparison Pages
Side-by-side analysis in markdown. Include:
- What is being compared and why
- Dimensions of comparison (table format preferred)
- Verdict or synthesis
- Sources

Architecture

Three Layers

Layer 1 — Raw Contents: Immutable directory and files. The agent can read but can never modify them. Layer 2 — The Wiki or knowledge base: Agent-owned directories and markdown files. Created, updated, and cross-referenced by the agent. Layer 3 — The Schema: SCHEMA.md defines user preferences of llm-wiki/ (or user customized folder name) conventions, and tag taxonomy.

Create a New Wiki

  1. Ask user preference of Layer 0 then create the directory structure as in Directory Structure.
  2. Ask user preferences of Layer 1 and Layer 2 directory structures and print the directory structure to confirm user intent.
  3. Print conventions based on SCHEMA.md, ask user preferences of conventions if they want to change.
  4. Write updated template of SCHEMA.md to SCHEMA.md with user preferences based on 2 and 3.
  5. Write initial index.md based on index.md template with sectioned header.
  6. Write initial log.md based on log.md template with creation entry.
  7. Confirm the wiki is ready and suggest first sources to ingest.

Ingest original content into a Wiki

  1. Read the files in raw/ using the code block below, the output is a list of each file metadata with mtime.
python3 $HOME/.agents/skills/llm-wiki-skill/scripts/ingest.py --collect ./raw
  1. Read last line of log.md to retrieve the "date time", use the below code block to retrieve its mtime
python3 $HOME/.agents/skills/llm-wiki-skill/scripts/ingest.py --iso-to-mtime "date time"

then find files generated in step 1 that are added after the "date time". 3. Based on SCHEMA.md convetions section, summarize each newly added file. 4. Find files that are added before and on the date time to prepare for step 4 and 5. 5. For file content conflicts, refer to conventions section defined in SCHEMA.md. 6. New files are created, existing files are updated, all with newly added cross-links under generated/. 7. Update index.md with sectioned header. 8. Update log.md with creation entry. 9. List out all files that are newly added or changed for user.

Ask questions about a Wiki

  1. Find relevant headings in index.md.
  2. Locate similar pages under the Wiki and summarize them based on SCHEMA.md using the format like "Based on [[page-1]], [[page-2]],...".
  3. present to user in markdown fashion.
  4. Ask user if they want to store the answers back in Wiki, if so take the following steps:

- create a queries/ folder if that does not exist - if the question is for comparisons, put the file in comparisons/, otherwise put in queries/

  1. Update index.md with sectioned header.
  2. Update log.md with creation entry.
  3. List out all files just created to the user, filenames should be enough no need to show content.

Lint, Audit or health-check a Wiki

Note: Below are 4 rules we lint, after they are checked, add a entry in log.md with lint action, subject should be "Rules passed: N, rules failed: M, which rule failed and a brief summary within 200 characters".

  1. Always read the SCHEMA.md first, find any violations and unresolved contradictions in the wiki.
  2. Find any orphan pages that no cross-link to other pages, using below code. The output is a list of orphan page file names.
python3 $HOME/.agents/skills/llm-wiki-skill/scripts/links.py --orphan ./generated
  1. and find any cross-links that are broken (unreachable), using below code. The output is a dictionary of file name to all its own broken links
python3 $HOME/.agents/skills/llm-wiki-skill/scripts/links.py --broken ./generated
  1. Every wiki page under generated/ should be listed in index.md, flag any pages that are not listed.

Rules (MUST FOLLOW)

  • **Always print a message to user when a task is finished, follow the below template:

|-------Your request has been taken care of!---------|

  • Never modify files in raw/ — sources are immutable. Corrections go in wiki pages.
  • Always orient first — read SCHEMA + index + recent log before any operation in a new session. Skipping this causes duplicates and missed cross-references.
  • Always update index.md and log.md — skipping this makes the wiki degrade. These are the navigational backbone.
  • Don't create pages without cross-references — isolated pages are invisible. Every page must link to at least 2 other pages.
  • Frontmatter is required — it enables search, filtering, and staleness detection.
  • Keep pages scannable — a wiki page should be readable in 30 seconds. Split pages over 200 lines. Move detailed analysis to dedicated deep-dive pages.
  • Ask before mass-updating — if an ingest would touch 10+ existing pages or create 10+ new pages, confirm the scope with the user first.
  • Rotate the log — when log.md exceeds 500 entries, rename it log-YYYY.md and start fresh. The agent should check log size during lint.
  • Handle contradictions explicitly — don't silently overwrite. Note both claims with dates, mark in frontmatter, flag for user review.

平台分布

Codex

35.64%
按下载量换算122

Claude

29.59%
按下载量换算101

Cursor

20.02%
按下载量换算68

Gemini CLI

9.4%
按下载量换算32

安全审计

Gen Agent Trust Hub

通过

Socket

通过

Snyk

通过

权限和风险

只读

该 Skill 主要提供规则、说明或参考内容,本身偏只读;真正读写文件、联网或执行命令仍取决于宿主 Agent 的任务。

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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