mpep-search
Skill206 starsChanged 8 months agoMITView on GitHub
Expert system for searching USPTO MPEP, 35 USC statutes, 37 CFR regulations, and post-Jan 2024 updates.
In this repository17 other files it gives its agents.
- CLAUDE.mdCLAUDE.md
- bigquery-patent-searchSkill
- development-assistantSkill
- epc-searchSkill
- epo-patent-analyzerSkill
- epo-patent-searchSkill
- index-managerSkill
- patent-application-creatorSkill
- patent-claims-analyzerSkill
- patent-diagram-generatorSkill
- patent-reviewerSkill
- patent-searchSkill
- pct-applicationSkill
- prior-art-searchSkill
- setup-assistantSkill
- testing-assistantSkill
- troubleshooting-assistantSkill
The file
We split this skill into the rules it gives an agent
2 rules. About 0 are common, 2 are distinctive, and 0 are very specific to this project.
≈0
Common · estimate
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≈2
Distinctive · estimate
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0
Very specific
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- Common
- Distinctive
- Very specific
- Distinctive: line 8
Search MPEP corpus through hybrid RAG (FAISS vector + BM25 keyword + HyDE + cross-encoder reranking).
- Distinctive: line 119
No empty/whitespace-only queries
≈ “Common” is an estimate: at least 1 in 5 of the 350,495 skill files we read have a rule of the same kind, not the same words. “Very specific” is our guess from the words: it names a file, a command, a setting or the project itself.
Files
MPEP Search Skill
Search MPEP corpus through hybrid RAG (FAISS vector + BM25 keyword + HyDE + cross-encoder reranking).
Sources:
- MPEP: Manual of Patent Examining Procedure
- 35 USC: United States Code Title 35
- 37 CFR: Code of Federal Regulations Title 37
- Subsequent Publications: Federal Register updates (post-Jan 2024)
Core Operations
1. search_mpep
Inputs:
query(string, required): Search query (minimum 3 characters)top_k(int, optional): Number of results (default: 5, max: 20)retrieve_k(int | None, optional): Candidates before reranking (default: top_k * 4, max: 100)source_filter(string | None, optional): Filter by source ("MPEP","35_USC","37_CFR","SUBSEQUENT", orNone)is_statute(bool | None, optional): Filter for statute contentis_regulation(bool | None, optional): Filter for regulation contentis_update(bool | None, optional): Filter for recent updates
Outputs:
{
"rank": int,
"source": str,
"section": str,
"file": str,
"page": int,
"has_statute": bool,
"has_mpep_ref": bool,
"has_rule_ref": bool,
"is_statute": bool,
"is_regulation": bool,
"is_update": bool,
"relevance_score": float,
"text": str,
# Optional for SUBSEQUENT:
"doc_type": str,
"fr_citation": str,
"effective_date": str
}Examples:
# Basic search
search_mpep("enablement requirement 35 USC 112", top_k=5)
# Search only statutes
search_mpep("written description", top_k=10, is_statute=True)
# Search recent updates
search_mpep("AI inventorship", is_update=True)
# Filter by source
search_mpep("fee schedule", source_filter="37_CFR")2. get_mpep_section
Retrieve all content from specific MPEP section.
Inputs:
section_number(string, required): MPEP section number (e.g.,"2100","608.01")max_chunks(int, optional): Maximum chunks to return (default: 50)
Outputs:
{
"section": str,
"total_chunks": int,
"chunks": [
{
"text": str,
"metadata": {
"source": str,
"file": str,
"page": int,
"section": str,
"has_statute": bool,
"has_mpep_ref": bool,
"has_rule_ref": bool,
"is_statute": bool,
"is_regulation": bool,
"is_update": bool
}
}
]
}Error Response:
{"error": "No content found for MPEP section {section_number}"}Examples:
# Get MPEP 2100 (Patentability)
get_mpep_section("2100", max_chunks=50)
# Get subsection
get_mpep_section("608.01")Input Validation
Query validation:
- Minimum 3 characters
- Case-insensitive
- No empty/whitespace-only queries
Section number validation:
- Numeric with optional decimal (e.g., "100", "2100", "608.01")
Limits:
top_kcapped at 20retrieve_kcapped at 100
Implementation Notes
Index Location:
- FAISS index:
mcp_server/index/mpep_index.faiss - Metadata:
mcp_server/index/mpep_metadata.json - BM25 index:
mcp_server/index/mpep_bm25.json
Search Architecture:
- HyDE Query Expansion (hypothetical documents)
- Hybrid Retrieval (FAISS vector + BM25 keyword via RRF)
- Cross-Encoder Reranking (final relevance scores)
- Metadata Filtering (source/type filters)
Dependencies:
- sentence-transformers (BGE-base-en-v1.5)
- FAISS (vector search)
- rank-bm25 (keyword search)
- Cross-encoder (reranking)
- HyDE (optional, graceful degradation)
Error Handling:
- Clear error messages for missing index/invalid queries
- Graceful degradation if HyDE fails
- Input validation before processing
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