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Agent Skill · 研究检索

search-prior-art(检索现有技术)

search-prior-art 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。

search-prior-art 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,第三方扫描有提醒项,按安装量在研究检索类的 73,675 个 Skill 里排第 45,786。

总安装 824周安装 33GitHub Stars 12下载 267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:search-prior-art(检索现有技术)
来源仓库:https://github.com/pjt222/development-guides
仓库路径:skills/search-prior-art
安装命令:
npx skills add https://github.com/pjt222/development-guides --skill search-prior-art
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/pjt222/development-guides --skill search-prior-art

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 中快速定位候选结果。支持基于关键词、任务场景或来源线索进行信息检索与筛选。可通过 npx skills add 命令从 GitHub 仓库安装使用。建议确认权限范围和维护状态,注意是否触发联网或文件读写操作。

search-prior-art 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/search-prior-art

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/pjt222/development-guides --skill search-prior…;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

search-prior-art 怎么安装?

在终端执行 npx skills add https://github.com/pjt222/development-guides --skill search-prior-art。装完完全退出宿主工具再打开,让它重新扫描本地 Skill。

search-prior-art 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。

search-prior-art 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。

search-prior-art 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。

search-prior-art 用的人多吗?

公开数据是累计安装 824 次,近一周安装 33 次,下载 267 次,GitHub 12 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。

search-prior-art 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。
  • 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。
  • 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
search-prior-art

检索现有技术 · 本页

82412只读未明确有提醒

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

Search Prior Art

Conduct a structured prior art search to find publications, patents, products, or disclosures that predate a specific invention. Used to assess patentability (can this be patented?), challenge validity (should this patent have been granted?), or establish freedom-to-operate (is this design covered by existing rights?).

When to Use

  • Evaluating whether an invention is novel and non-obvious before filing a patent application
  • Challenging the validity of an existing patent by finding prior art the examiner missed
  • Supporting a freedom-to-operate analysis by finding prior art that limits a blocking patent's scope
  • Documenting a defensive publication to prevent others from patenting a concept
  • Responding to a patent office action that questions novelty or obviousness

Inputs

  • Required: Invention description (what it does, how it works, what problem it solves)
  • Required: Search purpose (patentability, invalidity, FTO, defensive)
  • Required: Critical date (filing date of the patent application, or invention date for prior art)
  • Optional: Known related patents or publications
  • Optional: Technology classification codes (IPC, CPC)
  • Optional: Key inventors or companies in the field

Procedure

Step 1: Decompose the Invention into Searchable Elements

Break the invention into its constituent technical features.

  1. Read the invention description (or patent claims if searching against an existing patent)
  2. Extract the essential elements — each independent technical feature:

- What components does it have? - What steps does the process follow? - What technical effect does it achieve? - What problem does it solve and how?

  1. Identify the novel combination — what makes this different from the known art:

- Is it a new element added to known elements? - Is it a new combination of known elements? - Is it a known element applied in a new field?

  1. Generate search terms for each element:

- Technical terms, synonyms, and abbreviations - Broader and narrower terms (hierarchy) - Alternative descriptions of the same concept

  1. Document the Search Map: elements, terms, and relationships
Search Map Example:
+------------------+-----------------------------------+-----------+
| Element          | Search Terms                      | Priority  |
+------------------+-----------------------------------+-----------+
| Attention layer  | attention mechanism, self-         | High      |
|                  | attention, multi-head attention    |           |
| Sparse routing   | mixture of experts, sparse MoE,   | High      |
|                  | top-k routing, expert selection    |           |
| Training method  | knowledge distillation, teacher-   | Medium    |
|                  | student, progressive training      |           |
+------------------+-----------------------------------+-----------+

Expected: A complete decomposition with search terms for each element. The novel combination is identified — this is what the search must either find (to invalidate) or confirm is absent (to support novelty).

On failure: If the invention is too abstract to decompose, ask for a more specific description. If the claims are unclear, focus on the broadest reasonable interpretation of each claim element.

Step 2: Search Patent Literature

Search patent databases systematically.

  1. Construct queries combining element terms:

- Search each element individually first (broad) - Then combine elements to find closer art (narrow) - Use classification codes to filter by technology area

  1. Search multiple databases:

- Google Patents: Good for full-text search, free, large corpus - USPTO PatFT/AppFT: US patents and applications, official source - Espacenet: European patents, excellent classification search - WIPO Patentscope: PCT applications, global coverage

  1. Apply date filters:

- Prior art must predate the critical date (filing date or priority date) - Include publications up to 1 year before filing (grace period varies by jurisdiction)

  1. For each relevant result, record:

- Document number, title, filing date, publication date - Which elements it discloses (map to Search Map) - Whether it discloses the novel combination

  1. Classify results by relevance:

- X reference: Discloses the invention alone (anticipation) - Y reference: Discloses key elements, combinable with other references (obviousness) - A reference: Background art, defines the general state of the art

Expected: A classified list of patent references mapped to the invention's elements. X references (if found) are showstoppers for novelty. Y references are the building blocks for obviousness arguments.

On failure: If no relevant patent art is found, this doesn't mean the invention is novel — non-patent literature (Step 3) may contain the critical reference. Absence in one database doesn't mean absence everywhere.

Step 3: Search Non-Patent Literature

Search academic papers, products, open source, and other non-patent disclosures.

  1. Academic literature:

- Google Scholar, arXiv, IEEE Xplore, ACM Digital Library - Search using the same terms from Step 1 - Conference papers and workshop proceedings often predate patent filings

  1. Products and commercial disclosures:

- Product documentation, user manuals, marketing materials - Internet Archive (Wayback Machine) for date-verified web content - Trade publications and press releases

  1. Open source and code:

- GitHub, GitLab — search for implementations of the technical features - README files, documentation, and commit histories for date evidence - Software releases with version dates

  1. Standards and specifications:

- IEEE, IETF (RFCs), W3C, ISO standards - Standards-essential patents must be disclosed; search standard bodies' IP databases

  1. Defensive publications:

- IBM Technical Disclosure Bulletin - Research Disclosure journal - IP.com Prior Art Database

  1. For each result, verify the publication date is before the critical date:

- Web pages: use Wayback Machine for date evidence - Software: use release dates or commit timestamps - Papers: use publication date, not submission date

Expected: Non-patent references that complement the patent search. Academic papers and open-source code are often the most powerful prior art because they tend to describe technical details more explicitly than patents.

On failure: If non-patent literature is sparse, the technology may be primarily developed in corporate R&D (patent-heavy). Shift emphasis to patent literature and focus on the combination-based obviousness argument.

Step 4: Analyze and Map Results

Evaluate how the collected prior art relates to the invention.

  1. Create a claim chart mapping prior art to invention elements:
Claim Element vs. Prior Art Matrix:
+------------------+--------+--------+--------+--------+
| Element          | Ref #1 | Ref #2 | Ref #3 | Ref #4 |
+------------------+--------+--------+--------+--------+
| Element A        |   X    |   X    |        |   X    |
| Element B        |        |   X    |   X    |        |
| Element C        |   X    |        |   X    |        |
| Novel combo A+B+C|        |        |        |        |
+------------------+--------+--------+--------+--------+
X = element disclosed in this reference
  1. Assess novelty: Does any single reference disclose all elements?

- If yes → invention is anticipated (not novel) - If no → invention may be novel (proceed to obviousness)

  1. Assess obviousness: Can a small number of references (2-3) be combined to cover all elements?

- Is there motivation to combine? (would a skilled person see a reason to combine these?) - Do the references teach away from the combination? (suggest it wouldn't work?)

  1. For FTO searches: Does the prior art narrow the blocking patent's claims?

- Prior art that overlaps with the blocking patent's claims limits their enforceable scope

  1. Document the analysis clearly with citation to specific passages

Expected: A clear claim chart showing which elements are covered by which references, with an assessment of novelty and obviousness. Each mapping cites specific passages or figures in the references.

On failure: If the claim chart shows gaps (elements not found in any prior art), those gaps represent the potentially novel aspects. Focus follow-up searches on those specific gaps.

Step 5: Document and Deliver

Package the search results for their intended use.

  1. Write the Prior Art Search Report:

- Purpose and scope of the search - Search methodology (databases, queries, date ranges) - Results summary (number of references found, classification breakdown) - Top references with detailed analysis (claim charts) - Assessment: novelty, obviousness, and FTO implications - Limitations and recommendations for further search

  1. Organize references:

- Sorted by relevance (X references first, then Y, then A) - Each reference with full bibliographic data and access link - Key passages highlighted or extracted

  1. Recommendations based on search purpose:

- Patentability: File/don't file, suggested claim scope based on prior art gaps - Invalidity: Strongest combination of references, suggested legal argument - FTO: Risk level, design-around opportunities, licensing considerations - Defensive: Whether to publish as defensive disclosure based on white space found

Expected: A complete, well-organized search report that directly supports the intended decision. References are accessible and analysis is traceable.

On failure: If the search is inconclusive (no strong X or Y references, but some relevant background), state the conclusion clearly: "No anticipatory art found; closest art addresses elements A and B but not C. Recommend filing with claims emphasizing element C." Inconclusive is a valid and useful result.

Validation Checklist

  • Invention decomposed into distinct searchable elements
  • Novel combination explicitly identified
  • Patent databases searched (minimum 2 databases)
  • Non-patent literature searched (academic + products + open source)
  • All references predate the critical date (dates verified)
  • Claim chart maps elements to references with passage citations
  • Novelty and obviousness assessed with reasoning
  • Results classified by relevance (X, Y, A references)
  • Report includes methodology, limitations, and recommendations
  • Search is reproducible (queries and databases documented)

Common Pitfalls

  • Keyword tunnel vision: Searching only exact terms misses synonyms and alternative descriptions. Use the term hierarchy from Step 1
  • Patent-only search: Non-patent literature (papers, products, code) is often more explicit than patents. Don't skip Step 3
  • Date carelessness: Prior art must predate the critical date. A brilliant reference from one day after the filing date is worthless
  • Ignoring foreign language art: Major inventions may first appear in Chinese, Japanese, Korean, or German patent literature. Machine translation makes these searchable
  • Confirmation bias: Searching to confirm novelty rather than searching to find invalidating art. The best search tries hardest to find the closest art
  • Stopping too early: The first few results are rarely the best. Iterate search terms based on what early results reveal about the field's vocabulary

Related Skills

  • assess-ip-landscape — Broader landscape mapping that contextualizes specific prior art searches
  • screen-trademark — Trademark-specific conflict screening (different databases, different legal framework than patent prior art)
  • file-trademark — Trademark filing procedures for when screening is complete
  • review-research — Literature review methodology overlaps significantly with prior art search
  • security-audit-codebase — Systematic search methodology parallels (thoroughness, documentation, reproducibility)

平台分布

Codex

33.59%
按下载量换算90

Claude

31.49%
按下载量换算84

Cursor

20.9%
按下载量换算56

Gemini CLI

10.37%
按下载量换算28

安全审计

Gen Agent Trust Hub

通过

Socket

通过

Snyk

可疑

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。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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