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Figure Description

CommunityPopular
wanshuiyin
figure-description

Process user-provided patent figures and generate formal drawing descriptions. Use when user says "附图处理", "figure description", "附图说明", "drawings description", or wants to describe patent figures with reference numerals.

Overview

Publisherwanshuiyin
RepositoryAuto-claude-code-research-in-sleep
Skill namefigure-description
Stars
16.3K
Forks
1.4K
Bundled files
Instructions only
LicenseMIT
Links
  • Markdown instructions

    A SKILL.md file the model loads on demand, so it only costs tokens when a request actually matches.

  • Works with any LLM

    AI skills are plain Markdown, not provider-specific code, so this works with GPT, Claude, Gemini, Grok, or a local model.

  • Self-contained

    Everything the model needs lives in the instructions — no extra files to sync.

  • Open source

    Published by wanshuiyin on GitHub. Read the source before you install it.

Installation

Install the Figure Description AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

1

Install in TypingMind

TypingMind installs a skill straight from its GitHub folder — it reads SKILL.md, bundles the resource files, and stores the result locally.

  1. Open the app and go to Plugins → Skills.
  2. Choose "Install from GitHub".
  3. Paste the skill folder URL below and confirm.
  4. Enable the skill in any chat where you want it available.
Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.
2

Install in another agent

Any agent that reads the Agent Skills format can use this skill — copy the folder into that agent's skills directory.

Claude Code — .claude/skills
git clone --depth 1 https://github.com/wanshuiyin/Auto-claude-code-research-in-sleep.git /tmp/Auto-claude-code-research-in-sleep
mkdir -p .claude/skills
cp -r /tmp/Auto-claude-code-research-in-sleep/skills/figure-description .claude/skills/figure-description
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Figure Description in any TypingMind chat and the model takes it from there. Its name and description sit in the system prompt, and the moment a request matches, the model loads the full instructions itself — you never invoke it by hand, and it costs no tokens until it is actually used.

The model loads Figure Description on its own as soon as a request matches it.

Works with any AI model

AI skills are plain Markdown instructions rather than provider-specific code, so Figure Description is not tied to the model it was written for. Install it once in TypingMind and use it with GPT-5, Claude, Gemini, Grok, DeepSeek, Mistral, Llama, or a local model you run yourself — all on your own API keys.

  • Loaded only when it is needed

    The system prompt carries just the name and description. The instructions are fetched on the first matching request, so an idle skill costs nothing.

  • Switch models mid-chat

    Because the skill is instructions rather than code, changing model does not break it — the next model reads the same SKILL.md.

Skill instructions

This is the SKILL.md content the model loads. Read it before installing — a skill is instructions your model will follow.

Figure Description for Patents

Process patent figures and generate drawing descriptions based on: $ARGUMENTS

Unlike /paper-figure which generates data plots, this skill processes user-provided technical diagrams and assigns reference numerals.

Constants

  • FIGURE_DIR = "patent/figures/" — Output directory for figure descriptions
  • REFERENCE_NUMERAL_PREFIX = 100 — Starting numeral for first figure's components
  • NUMERAL_SERIES = 100 — Each figure uses a separate 100-series (Fig 1: 100-199, Fig 2: 200-299, etc.)

Inputs

  1. User-provided figures (PNG, JPG, SVG, PDF) — search for them in the project directory
  2. patent/INVENTION_DISCLOSURE.md — for understanding what components to identify
  3. patent/CLAIMS.md — for mapping numerals to claim elements

Workflow

Step 1: Discover Figures

  1. Search the project directory for figure files:
    • Check patent/figures/, figures/, root directory
    • Look for PNG, JPG, SVG, PDF files
    • Check INVENTION_BRIEF.md or INVENTION_DISCLOSURE.md for figure references
  2. List all discovered figures with their paths
  3. If figures are missing that claims require, note them as [MISSING: description needed]

Step 2: Analyze Each Figure

For each figure found:

  1. Read the image using the Read tool (supports image files)
  2. Identify components: What labeled or visually distinct components are shown?
  3. Identify connections: How do components relate to each other?
  4. Identify flow: If it's a flowchart or sequence, what is the step order?

Step 3: Assign Reference Numerals

For each figure, assign numerals using the series convention:

FigureNumeral Range
FIG. 1100-199
FIG. 2200-299
FIG. 3300-399

For each identified component:

  • Assign the next available numeral in the series
  • Cross-reference to the claim elements it supports
  • Note if a component appears in multiple figures (use same numeral across figures)

Step 4: Generate Drawing Descriptions

Write formal drawing descriptions (附图说明):

For CN jurisdiction (Chinese):

图1是[发明名称]的系统结构示意图;
图2是[发明名称]的方法流程图;
图3是[具体组件]的详细结构示意图;

For US/EP jurisdiction (English):

FIG. 1 is a block diagram illustrating the system architecture according to one embodiment;
FIG. 2 is a flowchart illustrating the method steps according to one embodiment;
FIG. 3 is a detailed view of the processing module of FIG. 1;

Step 5: Generate Reference Numeral Index

Create a complete mapping:

markdown
## Reference Numeral Index

| Numeral | Component Name | Figure(s) | Claim Element |
|---------|---------------|-----------|---------------|
| 100 | System | FIG. 1 | Claim X preamble |
| 102 | Processor | FIG. 1 | Claim X, element 1 |
| 104 | Memory | FIG. 1 | Claim X, element 2 |
| 106 | Communication bus | FIG. 1 | Claim X, element 3 |
| 200 | Method | FIG. 2 | Claim 1 preamble |
| 202 | Receiving step | FIG. 2 | Claim 1, step 1 |
| 204 | Processing step | FIG. 2 | Claim 1, step 2 |

Step 6: Cross-Reference to Claims

Verify that every claim element has at least one reference numeral:

Claim ElementFigureNumeralStatus
[element][which fig][numeral]Covered / [MISSING]

If any claim element has no corresponding figure or numeral, flag it:

  • [MISSING FIGURE: Need a diagram showing {element description}]
  • [MISSING NUMERAL: Component {name} in figure {X} needs a numeral]

Step 7: Output

Write patent/figures/figure_descriptions.md:

markdown
## Figure Descriptions

### FIG. 1 — [Description]
[Formal one-paragraph description with all reference numerals]

### FIG. 2 — [Description]
[Formal one-paragraph description with all reference numerals]
...

Write patent/figures/numeral_index.md:

markdown
## Reference Numeral Index

[Complete table of all numerals, components, figures, and claim mappings]

Key Rules

  • Every component in every figure must have a reference numeral.
  • Every reference numeral must be explained in the specification.
  • Numeral series must be consistent: 100-series for FIG. 1, 200-series for FIG. 2.
  • If the same component appears in multiple figures, use the SAME numeral.
  • Do NOT modify user-provided figures -- only describe them.
  • Flag missing figures that the claims require but the user has not provided.
  • Drawing descriptions are one sentence each, in a consistent format.

Frequently asked questions

What does the Figure Description AI skill do?

Process user-provided patent figures and generate formal drawing descriptions. Use when user says "附图处理", "figure description", "附图说明", "drawings description", or wants to describe patent figures with reference numerals.

Why use Figure Description on TypingMind?

Because you install it once and use it with any model. Figure Description is plain Markdown rather than provider-specific code, so the same skill runs on GPT-5, Claude, Gemini, Grok, or a local model — and you can switch model mid-chat without it breaking. TypingMind runs on your own API keys, so you pay providers directly instead of a per-seat subscription, and your skills and chats stay in your own storage.

How do I install Figure Description in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/wanshuiyin/Auto-claude-code-research-in-sleep/tree/main/skills/figure-description. TypingMind reads its SKILL.md and installs it as a skill you can enable per chat.

Which AI models can use Figure Description?

Any model you connect in TypingMind. AI skills are plain Markdown instructions rather than provider-specific code, so GPT, Claude, Gemini, Grok, and local models can all load this skill when a request matches it.

How many AI models can I use with Figure Description?

As many as you like. As long as a model supports skills, you can use Figure Description with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.

Is the Figure Description AI skill free?

Yes. It is published on GitHub by wanshuiyin under the MIT license. You only pay your own AI provider for the tokens you use.

What are AI skills?

An AI skill is a reusable instruction bundle that teaches an AI model how to do one specific task. It follows the open Agent Skills format: a SKILL.md file with a name and description, plus any scripts, templates or reference files the model may need. The model reads the instructions only when your request matches the skill, so an installed skill costs nothing until it is used.

How are AI skills different from plugins or MCP servers?

A plugin or MCP server gives a model new tools to call — code that runs somewhere and returns a result. An AI skill gives the model knowledge and process instead: how to approach a task, which steps to follow, what good output looks like. Skills are plain Markdown, so they need no server, no API key and no runtime, and they work with any model.

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