Patsnap Patent Paper Search

# Patent or Paper Markdown Fetch Tool ## Tool Description This is a data retrieval tool designed for AI Agents to fetch patent and paper data. It supports batch retrieval of Markdown-formatted content based on a list of keys (URLs containing patentId or paperId, or patent publication numbers), enabling AI to perform content analysis, reasoning, and Q&A. ## Core Features - **Batch Query**: Supports querying one or multiple patents or papers at once (up to 100) - **Auto Detection**: Automatically identifies whether the input is a patent URL (containing patentId), a paper URL (containing paperId), or a patent publication number (pn) - **Format Conversion**: Converts structured data into readable Markdown format - **Image Handling**: Optionally includes image links (for patents) - **Content Compression**: Optionally compresses returned content to reduce transfer size - **Module Selection**: Optionally specify which data modules to retrieve (basic, citations, legal, family) - **Structured Data**: Optionally returns the raw structured JSON data alongside Markdown, grouped by module ## Input Parameters ### keys (required) - **Type**: Array of strings - **Description**: List of keys (URLs containing patentId or paperId, or patent publication numbers) - **Patent URL format**: e.g. `https://eureka.zhihuiya.com/view/#/fullText'figures/?patentId=07c38692-9ccf-4ead-8f0f-484f7aa929b7` - **Paper URL format**: e.g. `https://eureka.zhihuiya.com/literature/#/abst?paperId=c53a8bcb-b7a3-42c9-8a6f-a26d6b5dec9a` - **Patent publication number (pn) format**: e.g. `US20240368139A1` - **Count limit**: 1–100 (10–20 recommended for best performance) ### key_type (optional) - **Type**: String - **Default**: `"url"` - **Description**: Key type — either a URL (containing patentId or paperId) or a patent publication number (pn) - **Usage**: Set to `"url"` when the input keys are URLs; set to `"pn"` when the input keys are patent publication numbers - **Allowed values**: `url`, `pn` ### compress (optional) - **Type**: Boolean - **Default**: `false` - **Description**: Whether to compress the returned Markdown content (using gzip + base64 encoding) - **Usage**: Recommended when the returned content is large ### include_images (optional) - **Type**: Boolean - **Default**: `false` - **Description**: Whether to include image links (only applicable to patents) - **Note**: When enabled, image URLs will be automatically signed ### module (optional) - **Type**: Array of strings - **Default**: `["basic"]` - **Description**: List of data modules to retrieve (only applicable to patents) - **Allowed values**: - `basic` — Core patent info (biblio, title, abstract, claims, description, etc.) - `citation` — Citation and cited-by records - `legal` — Legal status, assignment, license records - `family` — Patent family members (original, INPADOC, extended) - **Note**: `citation`, `legal`, and `family` are only supported for patents, not papers - **Examples**: `["basic"]`, `["basic", "citation"]`, `["basic", "citation", "legal", "family"]` ### include_structured (optional) - **Type**: Boolean - **Default**: `false` - **Description**: Whether to return the raw structured JSON data (the `structured` field) alongside the Markdown content - **Usage**: Enable when you need the original source data for further processing ## Output ### Successful Response Returns a JSON object with the following fields: - `total`: Total number of keys submitted - `success_count`: Number of successfully converted items - `failed_count`: Number of failed items - `results`: List of results, each containing: - `key`: The original input key (URL or patent publication number) - `key_type`: The type of the original input key (`url` or `pn`) - `markdown`: The converted Markdown content - `images`: List of image info (only present for patents when `include_images` is enabled) - `success`: Whether the conversion was successful - `message`: Processing message - `source`: Data source (`patent` or `paper`) - `modules`: The list of modules queried for this item - `structured`: Raw structured JSON data grouped by module (`basic`, `citation`, `legal`, `family`); unqueried modules are `null`. Only present when `include_structured` is `true` ## Usage Examples ### Example 1: Query a Patent ```json { "keys": ["https://eureka.zhihuiya.com/view/#/fullText'figures/?patentId=07c38692-9ccf-4ead-8f0f-484f7aa929b7"], "compress": false, "include_images": true, "modules": ["basic", "citation", "legal", "family"] } ``` ```json { "keys": ["CN115885075B"], "key_type": "pn", "compress": false, "include_images": true, "modules": ["basic"] } ``` ### Patent Result: ```json { "total": 1, "success_count": 1, "failed_count": 0, "results": [ { "key": "https://eureka.zhihuiya.com/view/#/fullText'figures/?patentId=07c38692-9ccf-4ead-8f0f-484f7aa929b7", "key_type": "url", "markdown": "# 专利详细信息\n\n...", "images": [ { "image_id": "HDA0003320126060000011", "image_url": "https://example.com/image.png" } ], "success": true, "compress": false, "message": "获取成功", "source": "patent", "modules": ["basic", "citation", "legal", "family"] } ] } ``` ### Example 2: Query a Paper ```json { "keys": ["https://eureka.zhihuiya.com/literature/#/abst?paperId=c53a8bcb-b7a3-42c9-8a6f-a26d6b5dec9a"], "compress": false, "include_images": false, "modules": ["basic"] } ``` ### Paper Result: ```json { "total": 1, "success_count": 1, "failed_count": 0, "results": [ { "key": "https://eureka.zhihuiya.com/literature/#/abst?paperId=c53a8bcb-b7a3-42c9-8a6f-a26d6b5dec9a", "key_type": "url", "markdown": "# 论文详细信息\n\n...", "images": [], "success": true, "compress": false, "message": "获取成功", "source": "paper", "modules": ["basic"] } ] } ```

# Patent / Paper Search Search one source per request (`source`: `patent` default, or `paper`). Returns a ranked page of matching documents with metadata and snippets. ## Use for Finding or listing patents/papers by topic, technical problem, company/applicant, author/inventor, identifier, classification, jurisdiction, date range, legal status, or citation threshold — for review, comparison, or ranking. ## Do NOT use for - Counts, trends, distributions, top-N, or citation statistics — this tool returns documents, not aggregates. - Full document content (full text, claims, descriptions, images, family, citation lists, legal detail) or raw source records. - Chit-chat or general knowledge unrelated to patents/papers. ## Invariants (MUST obey) 1. **Strategy ⇄ params binding is strict.** - `"semantic"` in `search_strategy` → MUST provide `semantic_query`; if `"semantic"` is NOT in `search_strategy` → MUST NOT provide `semantic_query`. - `"keyword"` in `search_strategy` → MUST provide `keywords`; if `"keyword"` is NOT in `search_strategy` → MUST NOT provide `keywords`. - `"filter"` in `search_strategy` → MUST provide `filters` with at least one field set; if `"filter"` is NOT in `search_strategy` → MUST NOT provide `filters`. 2. **`semantic_query` describes the technical topic or search intent in natural language.** - Use it for semantic retrieval of technical topics, questions, or mechanisms. For patents, also use it for target languages unsupported by keyword search. - Structured constraints such as companies, identifiers, dates, and jurisdictions belong in `filters`. 3. **`keywords` are atomic topic terms for BM25 text matching.** - Each item should be one technical term, product/standard name, abbreviation, method, material, or research concept. - Keyword search supports Chinese, English, and Japanese. Use terms in the requested target languages; for patents, use all three when no target language is specified. Use semantic search for other patent target languages. - Do not pass sentences, comma-joined strings, or generic filler such as "technology", "method", "system", "development". - Do not put applicant/company/assignee, inventor, author, or organization names in `keywords`; those belong in `filters`. 4. **`filters` are structured constraints, not text keywords.** - Use `filters` for company/applicant/assignee, inventor/author, organization, identifier, jurisdiction, IPC, legal status, date range, and citation threshold constraints. - Only set fields the user explicitly states. Do not infer dates, jurisdiction, IPC, assignees, inventors, authors, organizations, legal status, or citation thresholds. - `filters` must be a JSON object, never a stringified/escaped JSON string. 5. **Pagination limits are fixed.** - `limit` 1–100, `offset` ≥ 0, `offset + limit` ≤ 1000. ## Filter fields - `source="patent"`: pn, apno, assignees, assignee_ids, inventors, jurisdiction, ipc, legal_status, date_from, date_to, date_type, cited_min - `source="paper"`: authors, org_names, date_from, date_to, cited_min ## Examples ```json {"source":"paper","search_strategy":["semantic"],"semantic_query":"pharmaceutical technical solutions for treating glaucoma","limit":20} ``` ```json {"source":"patent","search_strategy":["keyword","filter"],"keywords":["5G","天线","antenna","アンテナ","MIMO"],"filters":{"assignees":["Huawei"],"jurisdiction":["CN","US"]},"limit":50} ``` ```json {"source":"paper","search_strategy":["filter"],"filters":{"authors":["Zhang San"],"date_from":20230101,"date_to":20241231},"limit":30} ```