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Get Started Free →Multi-jurisdiction prior art search across Google Patents, USPTO PatentsView, KIPRIS/KIPO, Espacenet, WIPO Patentscope, and Semantic Scholar. Generates bilingual keyword sets (English + Korean), IPC/CPC classification codes, and applicant spelling variants. Outputs structured search results with jurisdiction coverage flags. Suggests accelerated examination suitability and examination request timing for Korean filings. Use when the user asks to "search prior art", "find similar patents", "novelty
| Test case | Without → With | Effect | Δ tokens | Δ turns |
|---|---|---|---|---|
| case-16 | ✗→✓ | ▲ Improved | 131% | 0% |
| case-04 | ✗→✓ | ▲ Improved | 59% | 0% |
| case-06 | ✗→✓ | ▲ Improved | 13% | 0% |
| case-17 | ✗→✓ | ▲ Improved | 205% | 0% |
| case-14 | ✗→✓ | ▲ Improved | 93% | 0% |
Expert patent search analyst who identifies relevant prior art across multiple patent offices and academic databases, producing structured search reports with bilingual keyword coverage and jurisdiction-specific metadata.
outputs/patent-search/{date}/Before Step 1, confirm and normalize inputs. Required:
Graceful degradation:
Collect from the user:
If the user provides an existing draft or patent-scanner output, extract the technical features from those files.
Produce a keyword matrix:
| Category | English Keywords | Korean Keywords | IPC/CPC Codes | |----------|-----------------|-----------------|---------------| | Core concept | ... | ... | ... | | Variant terminology | ... | ... | ... | | Component terms | ... | ... | ... | | Effect/result terms | ... | ... | ... |
For Korean applicant/inventor names, generate multiple spelling variants:
Search these sources in parallel batches (max 4 concurrent):
| Source | URL Pattern | Coverage | |--------|------------|----------| | Google Patents | patents.google.com/?q=... | Global, full-text | | USPTO PatentsView | api.patentsview.org/patents/query | US patents/applications | | KIPRIS | kipris.or.kr | Korean patents/applications | | Espacenet | worldwide.espacenet.com | EP, WO, JP, CN | | WIPO Patentscope | patentscope.wipo.int | PCT applications | | Semantic Scholar | api.semanticscholar.org | Academic publications |
For each source, use WebSearch with jurisdiction-specific query construction:
For each result, extract and score:
| Field | Description | |-------|-------------| | title | Patent/paper title | | publication_number | Document number | | filing_date | Filing/priority date | | assignee | Applicant/assignee name | | abstract | Abstract text | | relevance_score | 1-10 relevance to invention (LLM-assessed) | | overlap_elements | Which invention features are disclosed | | kr_doc_included | Whether KR document was found (boolean) | | jurisdiction | US / KR / EP / WO / CN / JP | | ipc_codes | IPC classification codes |
Rank by relevance_score descending. Flag any result scoring 8+ as a potential blocking reference — these MUST appear in the blocking_references array in the final JSON output. If no result scores 8+, blocking_references must still be present as an empty array [].
Write the report to outputs/patent-search/{date}/search-results.json with:
json{ "search_date": "YYYY-MM-DD", "invention_summary": "...", "keywords": { "en": [...], "ko": [...] }, "ipc_codes": [...], "results": [...], "blocking_references": [...], "coverage_summary": { "us_results": 0, "kr_results": 0, "ep_results": 0, "wo_results": 0, "academic_results": 0 }, "kr_filing_recommendations": { "accelerated_exam_suitable": true, "accelerated_exam_reason": "...", "recommended_exam_request_timing": "..." } }
Also produce a human-readable summary at outputs/patent-search/{date}/search-summary.md.
When Korean jurisdiction is included:
overlap_elements from any result — every result must list which invention features are disclosed (use [] if none overlap).blocking_references array — any result with relevance_score ≥ 8 must be copied into this array; if none qualify, output [].Invention: LLM Agent Orchestration Platform that dynamically composes multi-agent workflows from a skill registry using semantic search-based routing, DAG-based execution ordering, and resource-aware model selection.
Sample keyword matrix (excerpt):
| Category | English Keywords | Korean Keywords | IPC/CPC Codes | |----------|-----------------|-----------------|---------------| | Core concept | multi-agent orchestration, skill registry composition, semantic routing LLM | 멀티에이전트 오케스트레이션, 스킬 레지스트리, 의미 기반 라우팅 | G06N 3/08, G06F 9/50 | | Mechanism | DAG execution order, workflow DAG, topological task schedule | DAG 실행 순서, 워크플로우 그래프, 작업 스케줄 | G06F 9/48 | | Resource | model tier selection, cost-aware LLM routing, latency SLO | 모델 티어 선택, 비용 인식 라우팅, 지연 목표 | G06N 20/00, G06F 9/455 |
Use this density of specificity — not generic “AI platform” terms alone.
Before presenting results or writing final artifacts, self-verify:
blocking_references array is present (populated with any result scoring ≥ 8, or [] if none qualify).relevance_score (1-10) AND overlap_elements (list of invention features disclosed).search-results.json and search-summary.md paths are populated or explicitly waived by user.kr_filing_recommendations is non-empty with accelerated exam and timing notes.relevance_score.If any check fails, fix or disclose before delivery.
| Artifact | Path | Format | |----------|------|--------| | Structured results | outputs/patent-search/{date}/search-results.json | JSON | | Human-readable summary | outputs/patent-search/{date}/search-summary.md | Markdown |
human review
the KIPRIS website
spelling variants
include Semantic Scholar
assessment, not publication dates
Other measured skills in the registry, with their headline benchmark lift.