---
name: prior-art-search-8793fb26c522
description: "Search patent databases and academic literature for prior art relevant to an invention. Use when user says \"现有技术检索\", \"prior art search\", \"专利检索\", \"check patents\", or wants to find relevant prior art."
argument-hint: "[invention-description-or-path]"
allowed-tools: Bash(*), Read, Glob, Grep, WebSearch, WebFetch, Write
---

# Prior Art Search

Search patents and literature for prior art relevant to: **$ARGUMENTS**

Adapted from `/research-lit` for patent-specific searching.

## Constants

- `MAX_PATENT_RESULTS = 20` — Maximum patent documents to analyze in detail
- `MAX_PAPER_RESULTS = 15` — Maximum academic papers to analyze in detail
- `SEARCH_YEARS = 10` — How many years back to search
- `PATENT_DATABASES = "google-patents, espacenet"` — Patent databases to search

## Inputs

Read the invention description from:
1. `$ARGUMENTS` if it contains technical details
2. `patent/INVENTION_BRIEF.md` if it exists
3. `INVENTION_BRIEF.md` if it exists at project root

## Shared References

Load `../shared-references/prior-art-databases.md` for search strategy templates and IPC/CPC classification guidance.

## Workflow

### Step 1: Extract Search Concepts

From the invention description, identify:
1. **Core inventive concept**: The primary technical contribution (1-2 sentences)
2. **Technical problem**: What problem it solves
3. **Key technical features**: 4-6 specific technical elements that define the invention
4. **IPC/CPC classes**: Predict relevant classification codes (e.g., G06N, G06F)

### Step 2: Patent Search

For EACH search concept, search via:

**Google Patents** (via WebSearch):
```
WebSearch: "site:patents.google.com [keywords]"
WebSearch: "[keywords] patent"
```
- Try primary keywords + technical problem keywords
- Search in English regardless of target jurisdiction
- For CN inventions, also search Chinese keywords via WebSearch

**Espacenet** (via WebFetch):
- WebFetch worldwide.espacenet.com/search results for key queries
- Search by predicted IPC/CPC classes

**Assignee/Inventor Search**:
- If known companies/universities work in this area, search their patent portfolios
- WebSearch: "[assignee name] patent [technical area]"

For each potentially relevant patent found:
- WebFetch the patent page to extract: title, abstract, representative claims, filing date, assignee, current status
- Record IPC/CPC classification codes

### Step 3: Academic Literature Search

Search the same concepts in academic databases:

1. **Google Scholar** (via WebSearch): `WebSearch "[keywords] site:scholar.google.com"`
2. **arXiv** (via `/arxiv` if available, or WebSearch): Search for preprints
3. **Semantic Scholar** (via `/semantic-scholar` if API key set, or WebSearch)

For each relevant paper found:
- Extract title, authors, venue, year, key contribution

### Step 4: Classification and Analysis

For each reference found, assess:

1. **Relevance**: How closely does it relate to the invention?
2. **Overlap Risk**: Does it disclose the same or similar technical solution?
   - HIGH: Anticipates one or more claim elements
   - MEDIUM: Discloses a related but different approach
   - LOW: Same general field, different approach
3. **Relationship**: Is it anticipating, relevant, or merely background?

Organize results by IPC/CPC classification to see the technical landscape.

### Step 5: Freedom-to-Operate Assessment (Preliminary)

Based on the search results:
- Identify patents with claims that potentially cover the invention
- Note any expired patents (public domain)
- Flag areas where claim scope overlap is significant

**Disclaimer**: This is a preliminary assessment only. A professional freedom-to-operate analysis by a patent attorney is recommended before filing.

### Step 6: Output

Write `patent/PRIOR_ART_REPORT.md` with:

```markdown
## Prior Art Search Report

### Invention Summary
[1-2 sentence description of the searched invention]

### Search Strategy
- Keywords used: [...]
- IPC/CPC classes searched: [...]
- Databases searched: Google Patents, Espacenet, Google Scholar, arXiv
- Date range: [year] to present

### Patent References Found

| # | Patent No. | Title | Date | Assignee | IPC/CPC | Key Teaching | Overlap Risk |
|---|-----------|-------|------|----------|---------|-------------|-------------|
| 1 | CN... / US... | [title] | [date] | [assignee] | [codes] | [2-3 sentences] | HIGH/MEDIUM/LOW |

### Non-Patent Literature Found

| # | Reference | Title | Authors/Venue | Year | Key Contribution | Relevance |
|---|-----------|-------|--------------|------|-----------------|-----------|
| 1 | [DOI/link] | [title] | [authors] | [year] | [1-2 sentences] | HIGH/MEDIUM/LOW |

### Prior Art Landscape
[Organized by technical approach or IPC class, not just chronological]

### Freedom-to-Operate Preliminary Assessment
[Which existing patents might block the invention? What is the risk level?]

### Recommendations
- Suggested claim scope adjustments based on prior art
- Areas where novelty appears strongest
- References to watch during prosecution
```

## Key Rules

- Never fabricate patent numbers or citations. Mark uncertain references with `[VERIFY]`.
- Search in English AND the target jurisdiction language (Chinese for CN).
- Patent prior art includes everything published before the priority date, not just patents.
- Academic papers are valid prior art for both novelty and inventive step.
- Include expired patents -- they are public domain but still relevant for novelty.


---
Source attribution: wanshuiyin
Original project: https://github.com/wanshuiyin/Auto-claude-code-research-in-sleep/blob/18bceb3c71c638bef58096274e1c9a6d323dbc0a/skills/prior-art-search/SKILL.md
License: MIT
License information: https://opensource.org/license/mit
Original upstream instructions; downloaded from Dave AI.

## Upstream license notice

MIT License

Copyright (c) 2026 wanshuiyin

Permission is hereby granted, free of charge, to any person obtaining a copy
of this software and associated documentation files (the "Software"), to deal
in the Software without restriction, including without limitation the rights
to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
copies of the Software, and to permit persons to whom the Software is
furnished to do so, subject to the following conditions:

The above copyright notice and this permission notice shall be included in all
copies or substantial portions of the Software.

THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
SOFTWARE.



# Dave AI resource metadata

Creator / publisher: wanshuiyin
Original project: https://github.com/wanshuiyin/Auto-claude-code-research-in-sleep/blob/18bceb3c71c638bef58096274e1c9a6d323dbc0a/skills/prior-art-search/SKILL.md
Attribution basis: Source repository record

Fields of work: Education & Research, Legal, Product Management, Sales
Roles: Business Development, Legal Operations, Product Manager, Researcher, Technical Product Manager
Specialties: API
Tools: Arxiv, Espacenet, Google Patents, Google Scholar, Semantic Scholar
Country applicability: Country not specified
Classification basis: Source catalog labels
Instruction SHA-256: 8fff863936b9d08937e63a48b8e5d06120a59ce1a10ef8d6348f5916105c6965