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Zhihuiya Abstract Image

v1.0.0

通过专利ID或公开号从智慧芽专利数据库获取专利摘要附图。当用户提到专利摘要附图、专利图纸、专利示意图、专利图片、摘要附图检索、专利图片查询、patent abstract images, patent drawings, patent illustrations, PatSnap, abstract image...

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Install

OpenClaw Prompt Flow

Install with OpenClaw

Best for remote or guided setup. Copy the exact prompt, then paste it into OpenClaw for linkfox-ai/linkfox-zhihuiya-abstract-image.

Previewing Install & Setup.
Prompt PreviewInstall & Setup
Install the skill "Zhihuiya Abstract Image" (linkfox-ai/linkfox-zhihuiya-abstract-image) from ClawHub.
Skill page: https://clawhub.ai/linkfox-ai/linkfox-zhihuiya-abstract-image
Keep the work scoped to this skill only.
After install, inspect the skill metadata and help me finish setup.
Use only the metadata you can verify from ClawHub; do not invent missing requirements.
Ask before making any broader environment changes.

Command Line

CLI Commands

Use the direct CLI path if you want to install manually and keep every step visible.

OpenClaw CLI

Bare skill slug

openclaw skills install linkfox-zhihuiya-abstract-image

ClawHub CLI

Package manager switcher

npx clawhub@latest install linkfox-zhihuiya-abstract-image
Security Scan
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Purpose & Capability
Name, description, SKILL.md, references/api.md, and the Python script all align: they call LinkFox's Zhihuiya abstractImage endpoint to return patent drawing URLs. There are no unrelated binaries, packages, or absurd permissions requested for the stated task.
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Instruction Scope
Runtime instructions and the included script perform network calls to https://tool-gateway.linkfox.com/zhihuiya/abstractImage and advise using a Feedback API at https://skill-api.linkfox.com/api/v1/public/feedback. The SKILL.md and references instruct the agent to use an API key from an environment variable (LINKFOXAGENT_API_KEY). The instructions do not attempt to read unrelated local files, but they do instruct the agent to contact two external services (tool-gateway and skill-api).
Install Mechanism
No install spec is present (instruction-only skill with an included helper script). That is low-risk from an installation perspective — the skill will not automatically download or install third-party code. The provided Python script is readable and calls the external API; nothing is obfuscated.
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Credentials
The skill requires an API key (LINKFOXAGENT_API_KEY) per references/api.md and the script, but the registry metadata declared no required environment variables or primary credential. Requesting a single service API key is proportionate to the task, but the omission in metadata is an inconsistency that can hide the need to provide a secret.
Persistence & Privilege
The skill is not always-enabled and does not request elevated persistence. It does not modify other skills or system settings. It can be invoked by the model (normal behavior).
What to consider before installing
This skill appears to do what it says (retrieve patent abstract images) and its code is readable, but the package metadata omitted the required API key. Before installing or enabling: 1) Confirm you trust the domains tool-gateway.linkfox.com and skill-api.linkfox.com and the skill author (LinkFox) — the skill will send requests to those endpoints. 2) Be aware you must provide LINKFOXAGENT_API_KEY (an environment variable) — ensure the key is scoped/minimally privileged and revocable. 3) The skill will fetch image URLs that may be rendered by your client (external image loads); consider privacy implications. 4) If you expect the registry to declare required credentials, ask the publisher to update metadata to list LINKFOXAGENT_API_KEY explicitly. If you cannot verify trust in LinkFox or the API endpoints, do not provide credentials or enable the skill.

Like a lobster shell, security has layers — review code before you run it.

latestvk975vny4rv6bqkhvwker8rhx2d843fh4
80downloads
0stars
1versions
Updated 3w ago
v1.0.0
MIT-0

Zhihuiya Patent Abstract Image

This skill guides you on how to retrieve abstract images (drawings) from the Zhihuiya patent database, helping users quickly obtain the illustrative figures associated with specific patents.

Core Concepts

Abstract images (abstract drawings) are the representative figures attached to a patent document's abstract section. They provide a quick visual overview of the invention. This tool queries the Zhihuiya patent database and returns download paths for these images.

Lookup logic: You must provide at least one of two identifiers -- a patent ID or a publication number. If both are provided, patent ID takes priority. You can query up to 100 patents in a single request by separating values with commas.

Parameter Guide

ParameterAPI NameRequiredDescriptionExample
Patent IDpatentIdConditionally (one of the two must be provided)Internal patent identifier; multiple values separated by commas, max 1005e6f7a8b9c
Publication NumberpatentNumberConditionally (one of the two must be provided)Patent publication/announcement number; multiple values separated by commas, max 100CN115059423A, US11234567B2
  • At least one of patentId or patentNumber must be supplied.
  • If both are supplied, patentId takes precedence.
  • Multiple values are separated by commas (English commas), with an upper limit of 100.

Response Fields

FieldAPI NameDescription
Patent IDpatentIdThe internal patent identifier
Publication NumberpnThe publication/announcement number
Abstract Drawing PathabstractDrawingPathURL path to the abstract image file
TotaltotalTotal number of records returned
Cost TokencostTokenTokens consumed by the query

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_abstract_image.py directly to run queries.

Usage Examples

1. Single patent lookup by publication number

Retrieve the abstract image for patent CN115059423A.

2. Multiple patents lookup by publication number

Get abstract drawings for patents US11234567B2, EP3456789A1, and CN115059423A.

3. Lookup by patent ID

Fetch the abstract image for patent ID 5e6f7a8b9c.

4. Batch lookup with mixed identifiers

I have the following patent IDs: abc123, def456. Please get their abstract images.

Display Rules

  1. Show the image: When the response includes an abstractDrawingPath, display the image directly using Markdown image syntax so the user can see the drawing inline.
  2. Patent identification: Always show the publication number (pn) alongside each image so the user knows which patent each drawing belongs to.
  3. Missing images: If a patent has no abstract drawing (empty abstractDrawingPath), explicitly inform the user that no abstract image is available for that patent.
  4. Batch results: When multiple patents are queried, present results in a clear, organized list or table format.
  5. Error handling: When a query fails, explain the reason based on the response and suggest the user verify their patent IDs or publication numbers.
  6. No subjective analysis: Present the retrieved images and metadata without adding subjective patent analysis or legal interpretations.

User Expression & Scenario Quick Reference

Applicable -- Patent abstract image retrieval:

User SaysScenario
"Show me the abstract image for patent XX"Single patent image lookup
"Get the drawings for these patents"Batch patent image lookup
"What does the patent figure look like"Abstract drawing retrieval
"Retrieve patent illustrations for XX"Image download path retrieval
"I need the abstract drawing for publication number XX"Lookup by publication number

Not applicable -- Needs beyond abstract image retrieval:

  • Full patent text or claims analysis
  • Patent search by keyword or classification
  • Patent legal status or family information
  • Patent citation or prior art analysis
  • Patent valuation or infringement analysis

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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