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wiki-query维基查询

Agent Skill

wiki-query 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。

总安装

1,448

周安装

58

GitHub Stars

3,678

下载量

469
CodexClaudeCursorGemini CLI

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

unknown

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:wiki-query(维基查询)
来源仓库:https://github.com/agricidaniel/claude-obsidian
仓库路径:skills/wiki-query
安装命令:
npx skills add https://github.com/agricidaniel/claude-obsidian --skill wiki-query
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/agricidaniel/claude-obsidian --skill wiki-query

简介

wiki-query 提供多层级知识检索能力,支持快速、标准与深度查询模式。

  • 依据问题复杂度选择 hot、默认或 deep 模式,控制上下文范围。
  • 优先利用已有合成信息作答,减少重复计算与 token 浪费。
  • 鼓励将优质答案回写至维基,持续丰富知识资产。
  • wiki-query 属于研究检索类 Skill,可作为该场景下的辅助能力补充。

SKILL.md

wiki-query: Query the Wiki

The wiki has already done the synthesis work. Read strategically, answer precisely, and file good answers back so the knowledge compounds.


Query Modes

Three depths. Choose based on the question complexity.

ModeTriggerReadsToken costBest for
Quickquery quick:... or simple factual Qhot.md + index.md only~1,500"What is X?", date lookups, quick facts
Standarddefault (no flag)hot.md + index + 3-5 pages~3,000Most questions
Deepquery deep:... or "thorough", "comprehensive"Full wiki + optional web~8,000+"Compare A vs B across everything", synthesis, gap analysis

Quick Mode

Use when the answer is likely in the hot cache or index summary.

  1. Read wiki/hot.md. If it answers the question, respond immediately.
  2. If not, read wiki/index.md. Scan descriptions for the answer.
  3. If found in index summary, respond and do not open any pages.
  4. If not found, say "Not in quick cache. Run as standard query?"

Do not open individual wiki pages in quick mode.


Standard Query Workflow

  1. Read wiki/hot.md first. It may already have the answer or directly relevant context.
  2. Read wiki/index.md to find the most relevant pages (scan for titles and descriptions).
  3. Read those pages. Follow wikilinks to depth-2 for key entities. No deeper.
  4. Synthesize the answer in chat. Cite sources with wikilinks: (Source: [[Page Name]]).
  5. Offer to file the answer: "This analysis seems worth keeping. Should I save it as wiki/questions/answer-name.md?"
  6. If the question reveals a gap: say "I don't have enough on X. Want to find a source?"

Deep Mode

Use for synthesis questions, comparisons, or "tell me everything about X."

  1. Read wiki/hot.md and wiki/index.md.
  2. Identify all relevant sections (concepts, entities, sources, comparisons).
  3. Read every relevant page. No skipping.
  4. If wiki coverage is thin, offer to supplement with web search.
  5. Synthesize a comprehensive answer with full citations.
  6. Always file the result back as a wiki page. Deep answers are too valuable to lose.

Token Discipline

Read the minimum needed:

Start withCost (approx)When to stop
hot.md~500 tokensIf it has the answer
index.md~1000 tokensIf you can identify 3-5 relevant pages
3-5 wiki pages~300 tokens eachUsually sufficient
10+ wiki pagesexpensiveOnly for synthesis across the entire wiki

If hot.md has the answer, respond without reading further.


Index Format Reference

The master index (wiki/index.md) looks like:

## Domains
- [[Domain Name]]: description (N sources)

## Entities
- [[Entity Name]]: role (first: [[Source]])

## Concepts
- [[Concept Name]]: definition (status: developing)

## Sources
- [[Source Title]]: author, date, type

## Questions
- [[Question Title]]: answer summary

Scan the section headers first to determine which sections to read.


Domain Sub-Index Format

Each domain folder has a _index.md for focused lookups:

---
type: meta
title: "Entities Index"
updated: YYYY-MM-DD
---
# Entities

## People
- [[Person Name]]: role, org

## Organizations
- [[Org Name]]: what they do

## Products
- [[Product Name]]: category

Use sub-indexes when the question is scoped to one domain. Avoid reading the full master index for narrow queries.


Filing Answers Back

Good answers compound into the wiki. Don't let insights disappear into chat history.

When filing an answer:

---
type: question
title: "Short descriptive title"
question: "The exact query as asked."
answer_quality: solid
created: YYYY-MM-DD
updated: YYYY-MM-DD
tags: [question, <domain>]
related:
  - "[[Page referenced in answer]]"
sources:
  - "[[wiki/sources/relevant-source.md]]"
status: developing
---

Then write the answer as the page body. Include citations. Link every mentioned concept or entity.

After filing, add an entry to wiki/index.md under Questions and append to wiki/log.md.


Gap Handling

If the question cannot be answered from the wiki:

  1. Say clearly: "I don't have enough in the wiki to answer this well."
  2. Identify the specific gap: "I have nothing on [subtopic]."
  3. Suggest: "Want to find a source on this? I can help you search or process one."
  4. Do not fabricate. Do not answer from training data if the question is about the specific domain in this wiki.

适合场景

01

用户想查找某类 Agent Skill 时

02

需要根据任务场景推荐可安装能力包时

03

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

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

Codex

34.13%
按下载量换算160

Claude

28.42%
按下载量换算133

Cursor

20.1%
按下载量换算94

Gemini CLI

10.92%
按下载量换算51

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。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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