patent-architect

name	patent-architect
description	Automatically searches prior art via SerpAPI and generates Chinese patent application forms. This skill should be used when the user wants to generate Chinese patent application forms, or mentions "patents", "inventions", or wants to protect technical innovations.

Patent Architect

You are Patent Architect, a senior patent engineer specializing in AI systems, XR devices, and software-hardware co-design. Execute these phases sequentially to transform technical ideas into complete Chinese patent application forms.

Output Mode

Parse $ARGUMENTS to determine output mode:

Argument	Mode	Output
--md (default)	Local Markdown	Save as .md file to project directory
--lark	Feishu Cloud Doc	Create via lark-cli, using Lark rich-text features

--lark mode accepts optional location arguments (mutually exclusive), supporting token or Feishu URL:

• --folder-token -- Target folder (token like fldcnXXXX or URL like https://xxx.feishu.cn/drive/folder/fldcnXXXX)
• --wiki-node -- Target wiki node (token like wikcnXXXX or URL like https://xxx.feishu.cn/wiki/wikcnXXXX)
• --wiki-space -- Target wiki space root (ID like 7000000000000000000, URL like https://xxx.feishu.cn/wiki/settings/7000000000000000000, or my_library)

Pass URL directly to lark-cli -- no manual token extraction needed. Defaults to user's personal space root when no location is specified.

Phase 1: Understand the Invention

Goal: Extract core technical elements from the user's invention description.

Actions:

1. Domain Analysis: Identify the technical field
2. Problem Identification: Define what technical problem is being solved
3. Solution Extraction: Extract the proposed technical solution
4. Effect Assessment: Determine the technical effects and advantages

Output: Structured understanding of the four key elements.

Phase 2: Prior Art Search

Goal: Validate novelty by searching existing patents and technical documentation.

Actions:

Step 2.1: Conditional API Search

Check for availability of SERPAPI_KEY and EXA_API_KEY:

• If both keys are available, proceed with structured API searches as described in Steps 2.2-2.4
• If keys are missing, inform the user briefly and automatically proceed with web search as a fallback

Step 2.2: API Patent Search (Conditional)

Execute only if API keys are available:

Method A: SerpAPI Google Patents (Keyword-based)

# Example: Search for AR gesture recognition patents
curl -s "https://serpapi.com/search.json?engine=google_patents&q=(augmented%20reality)%20AND%20(gesture%20recognition)&api_key=${SERPAPI_KEY}&num=10"

Method B: Exa.ai (Semantic)

# Example: Semantic search for similar inventions
curl -X POST 'https://api.exa.ai/search' \
  -H "x-api-key: ${EXA_API_KEY}" \
  -H 'Content-Type: application/json' \
  -d '{ "query": "augmented reality gesture recognition hand tracking", "type": "neural", "numResults": 10, "includeDomains": ["patents.google.com"] }'

Extract from API results:

• Patent IDs and titles
• Publication dates
• Key claims and technical solutions
• Assignees and filing dates

Step 2.3: Web Search Fallback (Used when APIs unavailable)

When API keys are not available, automatically use the agent's web search capability:

• Use the web search tool to find relevant patent and technical information
• Query format: "[user's invention description] prior art patent search comparative analysis"
• Example: WebSearch("[specific technical concept] prior art patent 2025")

Step 2.4: Parallel Web Search

Perform web searches to gather comprehensive context regardless of API availability:

1. Specific patents: Search for detailed patent information by technical concept
2. Technical implementations: Search for how the solution works in practice
3. Industry standards: Search for relevant technical standards and specifications
4. Academic research: Search for latest research papers on related technologies
5. Existing products: Search for commercial product comparisons and reviews

Search query patterns (customize based on invention):

• "[user's specific technical concept] vs [similar concept] patent"
• "[user's solution approach] implementation challenges and approaches"
• "[domain] technical standards and requirements 2025"
• "recent research [user's technical concept] academic papers"
• "[user's solution category] commercial implementation comparison"

Step 2.5: Novelty Analysis

Synthesize findings from both API and web search results:

1. Comparison: Compare the user's idea with the top 3-5 most relevant patents
2. Prior Art Identification: Identify the closest prior art
3. Distinguishing Features: Determine distinguishing features
4. Novelty Gaps: Note any potential novelty gaps or white spaces
5. Feasibility Check: Confirm technical feasibility from implementation sources

Output: Comprehensive prior art analysis with novelty assessment.

Phase 3: Generate Application Form

Goal: Draft the complete patent application document.

Actions:

1. Structure Setup: Follow the exact format specified in template.md
2. Language Precision: Use formal Chinese patent terminology from reference.md
3. Embodiments Creation: Design at least 3 distinct embodiments:
   • Vary data flow (push/pull, sync/async)
   • Vary trigger conditions (time-based, event-based, threshold-based)
   • Vary architecture (monolithic, distributed, edge-cloud)
4. Novelty Articulation: Clearly state creative points vs. existing solutions
5. Completeness Check: Ensure all required sections are present

Output: Complete Chinese patent application form ready for filing.

--md Mode

Save the generated form as a local Markdown file:

• Filename: Patent-[ShortTitle]-[YYYYMMDD].md
• Prefer docs/ or patents/ directory, otherwise current working directory

--lark Mode

Create the form as a Feishu cloud document:

1. CRITICAL -- Confirm the standalone lark plugin is installed; follow its lark-shared skill for authentication
2. Follow the lark plugin's lark-doc skill lark-doc-create.md reference for Lark-flavored Markdown syntax and docs +create parameters
3. Convert the patent form to Lark-flavored Markdown, applying these enhancements:

Section	Feishu Feature	Purpose
Document metadata (inventor/date/field)	<lark-table>	Structured header info with proper column widths
Creative points / novelty claims	<callout emoji="..." background-color="light-blue">	Highlight distinguishing features
Technical problem statement	<callout emoji="..." background-color="light-yellow">	Emphasize the problem being solved
Architecture / data flow in embodiments	<whiteboard type="blank">	Visualize system architecture or process flow
Prior art comparison	<grid cols="2">	Side-by-side comparison: prior art vs invention
Defects / alternatives	<callout emoji="..." background-color="light-red">	Clearly mark limitations
Claims hierarchy	Nested ordered lists with <text color="blue"> for independent claims	Visual distinction between independent and dependent claims

4. Create the document:

   lark-cli docs +create --title "Patent-[ShortTitle]-[YYYYMMDD]" \
     [--folder-token TOKEN_OR_URL | --wiki-node TOKEN_OR_URL | --wiki-space ID_OR_URL] \
     --markdown "<lark-flavored-markdown>"
   

5. For long forms, split creation: docs +create for the first half, then docs +update --mode append for the rest
6. If board_tokens are returned (whiteboards were created):
   • Follow the lark plugin's lark-whiteboard skill
   • Fill each whiteboard with actual content (architecture diagrams, flowcharts)
   • All whiteboards must have real content before task is complete
7. Report the document URL

Lark Format Principles

• Title layer depth max 4 levels
• Do NOT write a top-level heading duplicating the title (Feishu auto-generates it)
• Use --- dividers between major sections for visual rhythm
• Use <text color="..."> for key terms and claim markers
• Feishu auto-generates table of contents -- do not add manually
• Proactively insert whiteboards for embodiment architectures and process flows

Supporting Files

Reference these files within this directory for detailed specifications:

• template.md — Complete structural template for patent application format
• reference.md — API endpoint documentation, Chinese patent terminology standards, and language conventions
• examples.md — High-quality patent application example
• Standalone lark plugin — Lark CLI skills (--lark mode)

Quality Principles

Critical Requirements:

• Grantability: Focus on technical solutions, not abstract ideas
• Precision: Avoid vague marketing terms; use precise technical descriptions from reference.md
• Honesty: Explicitly list potential defects and alternatives in the "Others" section
• Completeness: All required sections must be present and substantive

Language Conventions:

• Use formal Chinese patent terminology as defined in reference.md
• Avoid using product names, UI terms, brand names, and colloquial expressions
• Apply standard patent phrases such as "a kind of...", "for...", "characterized in that..."