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Zhihuiya Fulltext Image

作者 linkfox-ai · GitHub ↗ · v1.0.0 · MIT-0
cross-platform ⚠ suspicious
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在 OpenClaw 中安装
/install linkfox-zhihuiya-fulltext-image
功能描述
通过专利ID或公开号获取专利文件中的全文附图(图纸、示意图、图表)。当用户询问专利图片、专利图纸、专利示意图、专利插图、全文附图、专利图表、专利技术图或想查看、下载专利文件中的嵌入图片、patent fulltext drawings, patent diagrams, technical drawings, p...
使用说明 (SKILL.md)

Zhihuiya Patent Fulltext Image

This skill guides you on how to retrieve fulltext images (drawings, figures, diagrams) from patent documents using the Zhihuiya patent data service, helping users access and analyze visual content within patents.

Core Concepts

Patent fulltext images are the figures, drawings, and diagrams embedded in patent documents. They are essential for understanding the technical details of an invention. This tool queries the Zhihuiya patent database and returns image metadata including download paths and image types for a given patent.

Lookup methods: You can look up images by either patent ID (an internal identifier) or publication number (the publicly visible patent number such as US20230012345A1 or CN115000000A). At least one of these must be provided.

Parameter Guide

Parameter API Name Required Description Example
Patent ID patentId No* Internal patent identifier 8a7b6c5d-...
Publication Number patentNumber No* Public patent publication/grant number US20230012345A1
Limit limit No Maximum number of images to return (max 100, default 100) 50
Offset offset No Pagination offset for image results 0

*At least one of patentId or patentNumber must be provided.

Response Fields

Field Description
total Total number of image records available
data Array of image entries
data[].patentId Patent identifier
data[].pn Publication/grant number
data[].fulltextImagePath URL path to download the image
data[].imageType Type/category of the image
columns Column rendering metadata
costToken Token cost of the request
type Rendering style hint

API Usage

This tool calls the LinkFox tool gateway API. See references/api.md for calling conventions, request parameters, and response structure. You can also execute scripts/zhihuiya_fulltext_image.py directly to run queries.

Usage Examples

1. Get all images for a patent by publication number

Retrieve fulltext images for patent US20230012345A1.

Parameters: {"patentNumber": "US20230012345A1"}

2. Get images for a patent by patent ID

Fetch the drawings for patent ID abc123def456.

Parameters: {"patentId": "abc123def456"}

3. Paginated retrieval of images

Get the first 20 images for patent CN115000000A.

Parameters: {"patentNumber": "CN115000000A", "limit": "20", "offset": "0"}

4. Get the next page of images

Get images 21-40 for patent CN115000000A.

Parameters: {"patentNumber": "CN115000000A", "limit": "20", "offset": "20"}

Display Rules

  1. Present data clearly: Show image results in a structured table with image type, download path, and patent number
  2. Image links: Always present fulltextImagePath values as clickable links so users can view or download images directly
  3. Pagination notice: When total exceeds the number of returned results, inform the user that more images are available and offer to fetch the next page
  4. Error handling: When a query fails, explain the reason and suggest verifying the patent ID or publication number
  5. No fabrication: Never invent patent IDs, publication numbers, or image URLs -- only display data returned by the API
  6. Total count: Always mention the total number of images available for the patent

Important Limitations

  • Image limit: Each request returns a maximum of 100 images
  • Identifier required: At least one of patentId or patentNumber must be supplied
  • All parameters are strings: Even numeric values like limit and offset must be passed as strings

User Expression & Scenario Quick Reference

Applicable -- Requests involving patent visual content:

User Says Scenario
"Show me the drawings for patent XX" Fulltext image retrieval
"Get the figures from this patent" Fulltext image retrieval
"Download patent images for XX" Fulltext image retrieval
"What diagrams does patent XX contain" Fulltext image listing
"How many figures are in patent XX" Image count query
"Show me the technical drawings" Fulltext image retrieval

Not applicable -- Needs beyond patent fulltext images:

  • Patent text/abstract/claims search
  • Patent family or citation analysis
  • Patent legal status queries
  • Patent assignee or inventor search
  • General image search unrelated to patents

Feedback:

Auto-detect and report feedback via the Feedback API when any of the following apply:

  1. The functionality or purpose described in this skill does not match actual behavior
  2. The skill's results do not match the user's intent
  3. The user expresses dissatisfaction or praise about this skill
  4. Anything you believe could be improved

Call the feedback API as specified in references/api.md. Do not interrupt the user's flow.


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安全使用建议
This skill appears to implement exactly what it claims (fetch patent images from a LinkFox/Zhihuiya API), but there are a few issues to consider before installing: - Manifest mismatch: the skill's code and API docs require LINKFOXAGENT_API_KEY, yet the registry metadata does not declare any required environment variables or a primary credential. Confirm with the publisher and avoid installing until the manifest correctly lists LINKFOXAGENT_API_KEY. - External endpoints: the skill sends requests to https://tool-gateway.linkfox.com/zhihuiya/fulltextImage (authorized via your API key) and also documents a separate feedback endpoint (https://skill-api.linkfox.com) that will receive skillName and user-provided content. If you plan to query with confidential patent text or proprietary snippets, be aware those could be transmitted as feedback if the skill auto-reports; verify when and how feedback is sent, and whether it requires consent. - API key handling: only provide LINKFOXAGENT_API_KEY if you trust LinkFox/this skill. Store the key securely (not in shared shells) and use a least-privilege key if possible. Rotate/revoke the key after testing. - Ask the publisher to correct the skill manifest to declare required env vars and to clarify the feedback behavior and whether feedback posts are authenticated or public. If you cannot verify the endpoints or publisher trustworthiness, avoid installing or limit usage to non-sensitive queries.
功能分析
Type: OpenClaw Skill Name: linkfox-zhihuiya-fulltext-image Version: 1.0.0 The skill is a legitimate tool for retrieving patent drawings and diagrams from the Zhihuiya database via the LinkFox API gateway. The Python script (zhihuiya_fulltext_image.py) correctly handles authentication via environment variables and performs standard API requests without any signs of data exfiltration, obfuscation, or malicious execution.
能力评估
Purpose & Capability
The skill's stated purpose (retrieve patent fulltext images) matches the code and SKILL.md: it POSTs to https://tool-gateway.linkfox.com/zhihuiya/fulltextImage and returns image URLs. However the registry metadata says "Required env vars: none" while the code and API docs clearly require LINKFOXAGENT_API_KEY; this mismatch is an incoherence worth flagging.
Instruction Scope
SKILL.md and the Python script limit behavior to querying the Zhihuiya/LinkFox tool gateway and presenting image links, with provisions for pagination and error handling. One notable instruction set in the SKILL.md (and references/api.md) describes calling a separate Feedback API (https://skill-api.linkfox.com/api/v1/public/feedback) to report user feedback; that will transmit skillName, sentiment, category and content (potentially including user-provided text) to an external endpoint. This is within the skill's declared docs but could leak user input if confidential content is included.
Install Mechanism
There is no install spec; it's instruction-only plus a small Python script. Nothing is downloaded or written by an installer, which minimizes surface risk.
Credentials
The code and API reference require an API key via the LINKFOXAGENT_API_KEY environment variable (used as Authorization header), but the skill registry metadata lists no required env vars or primary credential—this inconsistency is problematic. Requiring a single service API key is proportionate for the stated purpose, but the manifest should declare it. Also note that feedback calls post user content to a separate endpoint (no auth shown), which may be unexpected and could expose sensitive input.
Persistence & Privilege
The skill is not always-enabled and doesn't request persistent privileges or modify other skills or system settings. It runs ad-hoc when invoked and does not require elevated or persistent presence.
如何使用
  1. 确保已安装 OpenClaw(本地或 Docker 部署)
  2. 在对话框中输入安装命令:/install linkfox-zhihuiya-fulltext-image
  3. 安装完成后,直接呼叫该 Skill 的名称或使用 /linkfox-zhihuiya-fulltext-image 触发
  4. 根据 Skill 的参数说明提供必要输入,即可获得结构化输出
版本历史
v1.0.0
Initial release
元数据
Slug linkfox-zhihuiya-fulltext-image
版本 1.0.0
许可证 MIT-0
累计安装 0
当前安装数 0
历史版本数 1
常见问题

Zhihuiya Fulltext Image 是什么?

通过专利ID或公开号获取专利文件中的全文附图(图纸、示意图、图表)。当用户询问专利图片、专利图纸、专利示意图、专利插图、全文附图、专利图表、专利技术图或想查看、下载专利文件中的嵌入图片、patent fulltext drawings, patent diagrams, technical drawings, p... 它是一个面向 Claude Code / OpenClaw 的 AI Agent Skill 插件,目前累计下载 88 次。

如何安装 Zhihuiya Fulltext Image?

在 OpenClaw 或 Claude Code 对话框中运行命令「/install linkfox-zhihuiya-fulltext-image」即可一键安装,无需额外配置。

Zhihuiya Fulltext Image 是免费的吗?

是的,Zhihuiya Fulltext Image 完全免费,采用 MIT-0 许可证,可自由下载、安装和使用。

Zhihuiya Fulltext Image 支持哪些平台?

Zhihuiya Fulltext Image 跨平台运行,可在任意部署了 OpenClaw / Claude Code 的环境中使用(cross-platform)。

谁开发了 Zhihuiya Fulltext Image?

由 linkfox-ai(@linkfox-ai)开发并维护,当前版本 v1.0.0。

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