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Agent Skill · 研究检索

prior-art-search(现有技术检索)

prior-art-search 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。

prior-art-search 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,权限为接触敏感数据;许可证信息还不明确,第三方扫描有提醒项,按安装量在研究检索类的 73,674 个 Skill 里排第 45,663。

总安装 832周安装 34GitHub Stars 7,796下载 269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:prior-art-search(现有技术检索)
来源仓库:https://github.com/wanshuiyin/auto-claude-code-research-in-sleep
仓库路径:skills/prior-art-search
安装命令:
npx skills add https://github.com/wanshuiyin/auto-claude-code-research-in-sleep --skill prior-art-search
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/wanshuiyin/auto-claude-code-research-in-sleep --skill prior-art-search

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。

用于查找、检索和筛选相关信息。适合在 Codex、Claude、Cursor、Gemini CLI 中根据关键词、任务场景或来源线索快速定位候选结果。通过 npx skills add 命令从指定仓库安装,需结合原始 README 核验具体用法。安装前建议确认权限范围、维护状态及是否会触发联网、命令执行或文件读写。

prior-art-search 属于研究检索类 Skill,可作为该场景下的辅助能力补充。

来源仓库内路径:skills/prior-art-search

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/wanshuiyin/auto-claude-code-research-in-sleep…;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

    它需要接触敏感数据,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

prior-art-search 怎么安装?

在终端执行 npx skills add https://github.com/wanshuiyin/auto-claude-code-research-in-sleep --skill pr…。装完完全退出宿主工具再打开,让它重新扫描本地 Skill。

prior-art-search 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。

prior-art-search 需要什么权限?

权限级别是接触敏感数据。该 Skill 可能接触密钥、Token、环境变量或敏感配置,应进入高风险复核队列,默认不自动发布。

prior-art-search 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。

prior-art-search 用的人多吗?

公开数据是累计安装 832 次,近一周安装 34 次,下载 269 次,GitHub 7,796 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。

prior-art-search 安全吗?

第三方扫描有提醒项,说明存在需要人工确认的行为。安装前请打开源码看清它读了什么、联网到哪里。

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。
  • 来源仓库有 7,796 星,维护活跃度相对可查。

先想清楚的地方

  • 需要接触敏感数据,装到常用环境前要先评估影响面。
  • 许可证没有明确标注,能不能商用、能不能再分发都不确定。
  • 第三方扫描存在提醒项或未通过项,需要人工逐条确认。
  • 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。

不太适合

  • 环境里有大量密钥、凭证,不方便给第三方 Skill 读取的人。
  • 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
prior-art-search

现有技术检索 · 本页

8327,796接触敏感数据未明确有提醒

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

Prior Art Search

Search patents and literature for prior art relevant to: $ARGUMENTS

Adapted from /research-lit for patent-specific searching.

Constants

  • MAX_PATENT_RESULTS = 20 — Maximum patent documents to analyze in detail
  • MAX_PAPER_RESULTS = 15 — Maximum academic papers to analyze in detail
  • SEARCH_YEARS = 10 — How many years back to search
  • PATENT_DATABASES = "google-patents, espacenet" — Patent databases to search

Inputs

Read the invention description from:

  1. $ARGUMENTS if it contains technical details
  2. patent/INVENTION_BRIEF.md if it exists
  3. INVENTION_BRIEF.md if it exists at project root

Shared References

Load ../shared-references/prior-art-databases.md for search strategy templates and IPC/CPC classification guidance.

Workflow

Step 1: Extract Search Concepts

From the invention description, identify:

  1. Core inventive concept: The primary technical contribution (1-2 sentences)
  2. Technical problem: What problem it solves
  3. Key technical features: 4-6 specific technical elements that define the invention
  4. IPC/CPC classes: Predict relevant classification codes (e.g., G06N, G06F)

Step 2: Patent Search

For EACH search concept, search via:

Google Patents (via WebSearch):

WebSearch: "site:patents.google.com [keywords]"
WebSearch: "[keywords] patent"
  • Try primary keywords + technical problem keywords
  • Search in English regardless of target jurisdiction
  • For CN inventions, also search Chinese keywords via WebSearch

Espacenet (via WebFetch):

  • WebFetch worldwide.espacenet.com/search results for key queries
  • Search by predicted IPC/CPC classes

Assignee/Inventor Search:

  • If known companies/universities work in this area, search their patent portfolios
  • WebSearch: "[assignee name] patent [technical area]"

For each potentially relevant patent found:

  • WebFetch the patent page to extract: title, abstract, representative claims, filing date, assignee, current status
  • Record IPC/CPC classification codes

Step 3: Academic Literature Search

Search the same concepts in academic databases:

  1. Google Scholar (via WebSearch): WebSearch "[keywords] site:scholar.google.com"
  2. arXiv (via /arxiv if available, or WebSearch): Search for preprints
  3. Semantic Scholar (via /semantic-scholar if API key set, or WebSearch)

For each relevant paper found:

  • Extract title, authors, venue, year, key contribution

Step 4: Classification and Analysis

For each reference found, assess:

  1. Relevance: How closely does it relate to the invention?
  2. Overlap Risk: Does it disclose the same or similar technical solution?

- HIGH: Anticipates one or more claim elements - MEDIUM: Discloses a related but different approach - LOW: Same general field, different approach

  1. Relationship: Is it anticipating, relevant, or merely background?

Organize results by IPC/CPC classification to see the technical landscape.

Step 5: Freedom-to-Operate Assessment (Preliminary)

Based on the search results:

  • Identify patents with claims that potentially cover the invention
  • Note any expired patents (public domain)
  • Flag areas where claim scope overlap is significant

Disclaimer: This is a preliminary assessment only. A professional freedom-to-operate analysis by a patent attorney is recommended before filing.

Step 6: Output

Write patent/PRIOR_ART_REPORT.md with:

## Prior Art Search Report

### Invention Summary
[1-2 sentence description of the searched invention]

### Search Strategy
- Keywords used: [...]
- IPC/CPC classes searched: [...]
- Databases searched: Google Patents, Espacenet, Google Scholar, arXiv
- Date range: [year] to present

### Patent References Found

| # | Patent No. | Title | Date | Assignee | IPC/CPC | Key Teaching | Overlap Risk |
|---|-----------|-------|------|----------|---------|-------------|-------------|
| 1 | CN... / US... | [title] | [date] | [assignee] | [codes] | [2-3 sentences] | HIGH/MEDIUM/LOW |

### Non-Patent Literature Found

| # | Reference | Title | Authors/Venue | Year | Key Contribution | Relevance |
|---|-----------|-------|--------------|------|-----------------|-----------|
| 1 | [DOI/link] | [title] | [authors] | [year] | [1-2 sentences] | HIGH/MEDIUM/LOW |

### Prior Art Landscape
[Organized by technical approach or IPC class, not just chronological]

### Freedom-to-Operate Preliminary Assessment
[Which existing patents might block the invention? What is the risk level?]

### Recommendations
- Suggested claim scope adjustments based on prior art
- Areas where novelty appears strongest
- References to watch during prosecution

Key Rules

  • Never fabricate patent numbers or citations. Mark uncertain references with [VERIFY].
  • Search in English AND the target jurisdiction language (Chinese for CN).
  • Patent prior art includes everything published before the priority date, not just patents.
  • Academic papers are valid prior art for both novelty and inventive step.
  • Include expired patents -- they are public domain but still relevant for novelty.

平台分布

Codex

31.82%
按下载量换算86

Claude

30.48%
按下载量换算82

Cursor

19.66%
按下载量换算53

Gemini CLI

10.11%
按下载量换算27

安全审计

Gen Agent Trust Hub

通过

Socket

通过

Snyk

可疑

权限和风险

接触敏感数据

该 Skill 可能接触密钥、Token、环境变量或敏感配置,应进入高风险复核队列,默认不自动发布。

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。来源安全扫描存在提醒或未通过项,安装前请自行复核。目前只有一个公开来源,建议同时核对源仓库。

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