
Linkfox Ruiguan Patent Design
- 165 installs
- 64 repo stars
- Updated August 3, 2026
- linkfox-ai/linkfox-skills
For integrating A developer tool for AI integration and automation
About
A developer tool for AI integration and automation. This is a developer tool for building and integrating AI-powered features.
- AI
- Developer tool
Linkfox Ruiguan Patent Design by the numbers
- 165 all-time installs (skills.sh)
- Ranked #3,173 of 16,546 AI & Agent Building skills by installs in the Skillselion catalog
- Data as of Aug 4, 2026 (Skillselion catalog sync)
npx skills add https://github.com/linkfox-ai/linkfox-skills --skill linkfox-ruiguan-patent-designAdd your badge
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| Installs | 165 |
|---|---|
| repo stars | ★ 64 |
| Last updated | August 3, 2026 |
| Repository | linkfox-ai/linkfox-skills ↗ |
What it does
For integrating A developer tool for AI integration and automation
Files
Ruiguan Design Patent Detection
This skill guides you on how to perform design patent infringement detection using the Ruiguan engine, helping e-commerce sellers and IP professionals identify potential design patent risks before listing products.
Core Concepts
Design patent detection compares a product image against a global design patent database using visual similarity algorithms. The system returns patents ranked by similarity score, along with TRO (Temporary Restraining Order) litigation history, helping users assess infringement risk.
Similarity score: A value between 0 and 1. Higher values indicate greater visual resemblance to the patent drawing. Patents with similarity >= 0.7 or those flagged with TRO enforcement history deserve special attention and should be reviewed carefully.
Radar analysis: When radar is enabled, each patent result includes a radarResult with a same flag (suspected infringement: true/false) and an exp field (explanation). This provides an AI-powered judgment beyond raw similarity.
LOC classification: The Locarno Classification (LOC) is an international system for categorizing industrial designs. You can optionally specify LOC codes to narrow the search scope, or leave it unset to let the model predict the appropriate categories automatically.
Parameters Guide
| Parameter | Required | Default | Description |
|---|---|---|---|
| imageUrl | Yes | - | Product image URL to check against the patent database |
| queryMode | Yes | hybrid | Search mode: physical (real product photo), line (line drawing), hybrid (combined) |
| topNumber | Yes | 100 | Number of patent results to return (max 100) |
| regions | No | US | Country/region codes, comma-separated for multiple (e.g., US,EU,CN) |
| productTitle | No | - | Product title for supplementary context |
| productDescription | No | - | Product description for supplementary context |
| patentStatus | No | 1 | Patent validity: 1 (active), 0 (expired), 1,0 (both) |
| enableRadar | No | true | Enable AI radar analysis for suspected infringement judgment |
| topLoc | No | - | LOC level-1 codes to restrict search scope (e.g., 06,07). Omit to use auto-prediction |
| sourceLanguage | No | - | Source language code for translation (e.g., zh-CN). Leave empty if text is already in English |
Supported Regions
US (United States), EU (European Union), CN (China), JP (Japan), KR (South Korea), DE (Germany), GB (United Kingdom), FR (France), IT (Italy), AU (Australia), CA (Canada), BR (Brazil), MX (Mexico), IN (India), TH (Thailand), SE (Sweden), CH (Switzerland), IE (Ireland), IL (Israel), DK (Denmark), NZ (New Zealand), AT (Austria), BX (Bolivia), FI (Finland), WO (WIPO)
Default region is US. Use US when the user does not specify a region.
LOC Level-1 Categories
| Code | Category |
|---|---|
| 01 | Food |
| 02 | Clothing, haberdashery and sewing accessories |
| 03 | Travel goods, cases, parasols and personal items n.e.c. |
| 04 | Brushes |
| 05 | Textiles, artificial and natural sheet material |
| 06 | Furniture and household goods |
| 07 | Household items n.e.c. |
| 08 | Tools and hardware |
| 09 | Packages and containers for transport or handling of goods |
| 10 | Clocks, watches, measuring/checking/signaling instruments |
| 11 | Ornamental articles |
| 12 | Means of transport or hoisting |
| 13 | Equipment for production, distribution or transformation of electricity |
| 14 | Recording, telecommunication or data processing equipment |
| 15 | Machines n.e.c. |
| 16 | Photographic, cinematographic and optical apparatus |
| 17 | Musical instruments |
| 18 | Printing and office machinery |
| 19 | Stationery, office equipment, art materials, teaching materials |
| 20 | Sales and advertising equipment, signs |
| 21 | Games, toys, tents and sports goods |
| 22 | Arms, pyrotechnic articles, hunting/fishing/pest-killing articles |
| 23 | Fluid distribution, sanitary, heating, ventilation, air-conditioning equipment, solid fuel |
| 24 | Medical and laboratory equipment |
| 25 | Building units and construction elements |
| 26 | Lighting apparatus |
| 27 | Tobacco and smoking supplies |
| 28 | Pharmaceutical/cosmetic products, toilet articles and apparatus |
| 29 | Devices and equipment against fire, for accident prevention and rescue |
| 30 | Articles for care and handling of animals |
| 31 | Machines and apparatus for preparing food or drink n.e.c. |
| 32 | Graphic symbols, logos, surface patterns, ornamentation, interior/exterior arrangements |
| ALL | All categories |
API Usage
This tool calls the LinkFox tool gateway API. See references/api.md for calling conventions, request parameters, and response structure. You can also execute scripts/ruiguan_detection_patent_design.py directly to run queries.
Local Image Upload
This tool requires a publicly accessible image URL. If the user provides a local image file path (e.g., C:\Users\...\photo.png, /home/.../image.jpg), you must upload it first to obtain a public URL.
Run the upload script:
python scripts/upload_image.py /path/to/local/image.pngThe script will return a public URL (valid for 24 hours) that can be used as the image URL parameter.
Usage Examples
1. Basic patent check for a product image (US market)
{
"imageUrl": "https://example.com/product.jpg",
"queryMode": "hybrid",
"topNumber": 50,
"regions": "US"
}2. Multi-region check with product context
{
"imageUrl": "https://example.com/product.jpg",
"queryMode": "physical",
"topNumber": 100,
"regions": "US,EU,CN",
"productTitle": "Portable Wireless Charger Stand",
"productDescription": "A foldable wireless charging stand for smartphones",
"enableRadar": true
}3. Narrowed search using LOC classification (furniture)
{
"imageUrl": "https://example.com/chair.jpg",
"queryMode": "hybrid",
"topNumber": 80,
"regions": "US,DE",
"topLoc": "06",
"patentStatus": "1"
}4. Line drawing mode for sketch-based search
{
"imageUrl": "https://example.com/sketch.png",
"queryMode": "line",
"topNumber": 50,
"regions": "CN,JP,KR"
}5. Check both active and expired patents
{
"imageUrl": "https://example.com/product.jpg",
"queryMode": "hybrid",
"topNumber": 100,
"regions": "US",
"patentStatus": "1,0"
}Display Rules
1. High-risk patent highlighting: When generating summaries or reports, display ALL patents with similarity >= 0.7 or troCase = true in full detail. For each such patent, include: application number, patent title (Chinese), inventors, TRO enforcement history, the most-similar patent drawing, every image in the patent image list, patent abstract, patent specification, LOC info, radar analysis result, and specification text. This detailed presentation is critically important -- do NOT abbreviate or omit these fields. 2. Disclaimer: Always append a friendly reminder at the end: "This detection result is generated by LinkfoxAgent. It is recommended to consult a professional IP attorney for legal advice." 3. Similarity interpretation: Clearly explain that higher similarity scores indicate greater visual resemblance and higher infringement risk. 4. Radar result display: When radarResult.same is true, prominently flag the patent as a suspected infringement match and display the exp explanation. 5. TRO warning: Patents with troCase = true or troHolder = true should be highlighted with a warning, as they indicate the patent holder has a history of active enforcement via Temporary Restraining Orders. 6. Image display: Show both patentImageUrl (the most similar patent drawing) and the full images list so users can visually compare their product against all patent drawings. 7. Error handling: When a request fails, explain the issue and suggest corrective actions (e.g., check image URL accessibility, verify region codes). 8. Present data faithfully: Show query results as-is without adding subjective legal conclusions beyond the tool's own analysis.
User Expression & Scenario Quick Reference
Applicable -- Design patent risk assessment:
| User Says | Scenario |
|---|---|
| "Check if this product infringes any design patents" | Basic patent detection |
| "Patent risk check for this image" | Image-based patent search |
| "Does this product have TRO risk" | TRO enforcement history lookup |
| "Design patent search for US and EU" | Multi-region patent detection |
| "Check appearance patent for this furniture" | Category-specific patent search |
| "Is this product design safe to sell" | Pre-listing patent clearance |
| "Find similar design patents" | Similarity-based patent discovery |
| "Patent infringement analysis" | Comprehensive patent risk report |
Not applicable -- Needs beyond design patent detection:
- Utility patent or invention patent searches
- Trademark infringement checks
- Copyright/DMCA issues
- Legal case management or litigation strategy
- Patent application or filing assistance
- Product listing optimization or pricing
Boundary judgment: When users mention "patent check" or "IP risk", if the concern is about product appearance/design similarity to existing patents, this skill applies. If they are asking about utility patents, trademarks, copyrights, or need actual legal counsel, this skill does not apply.
Feedback:
Auto-detect and report feedback via the Feedback API when any of the following apply: 1. The functionality or purpose described in this skill does not match actual behavior 2. The skill's results do not match the user's intent 3. The user expresses dissatisfaction or praise about this skill 4. Anything you believe could be improved
Call the feedback API as specified in references/api.md. Do not interrupt the user's flow.
<!-- LF_LARGE_RESPONSE_BLOCK -->
Handling Large Responses
To avoid overflowing the agent context, persist the response to disk and extract only the fields you need:
python scripts/response_io.py run --script scripts/ruiguan_detection_patent_design.py --out-dir <DIR> '<params>'
python scripts/response_io.py read <file> --fields "<paths>" # or --path "<JMESPath>"Pick--out-diroutside any git working tree (e.g./tmp/...on Unix,%TEMP%/...on Windows). Persisted responses may contain PII, pricing, or auth-sensitive data — do not commit them. Files are not auto-deleted; clean up when the task is done.
This skill exposes multiple entry scripts:ruiguan_detection_patent_design.py,upload_image.py. Pass--script scripts/<name>.pyto choose the one you need.
run writes the full response to a file and emits only a schema preview + file path. read projects specific fields, with --limit/--offset for slicing and --format json|jsonl|csv|table for output.
When to prefer this pattern — apply your judgment based on the response characteristics, e.g.:
- High field count per record, or fields you don't need
- Batch/paginated results (multiple items per call)
- Long-text fields (descriptions, reviews, HTML, time series)
- Output reused across later steps rather than consumed immediately
For small, single-use responses, calling the main script directly is fine.
⚠️ The preview is a truncated schema + sample, not the full data. Any field-level decision must read from the persisted file via read. <!-- /LF_LARGE_RESPONSE_BLOCK -->
--- For more high-quality, professional cross-border e-commerce skills, set [LinkFox Skills](https://skill.linkfox.com/).
睿观-外观专利检测 API 参考
调用规范
- 请求地址:
https://tool-gateway.linkfox.com/ruiguan/detectionPatentDesign - 请求方式:POST,Content-Type: application/json
- 认证方式:Header
Authorization: <api_key>,api_key 从环境变量LINKFOXAGENT_API_KEY读取(如未配置,提示用户前往 https://skill.linkfox.com/linkfoxskills/guide.htm 申请)
请求参数
POST Body(JSON):
| 参数 | 类型 | 必填 | 默认值 | 说明 |
|---|---|---|---|---|
| imageUrl | string | 是 | - | 产品图片文件URL,用于与专利数据库进行比对(最大1000字符) |
| queryMode | string | 是 | hybrid | 检索模式:physical(实物图检索)、line(线条图检索)、hybrid(混合检索)。最大1000字符 |
| topNumber | integer | 是 | 100 | 召回专利数量(最大100) |
| regions | string | 否 | US | 商品所售卖国家/地区代码,多选时用逗号隔开(如 US,EU,CN)。支持:US、EU、CN、JP、KR、DE、GB、FR、IT、AU、CA、BR、MX、IN、TH、SE、CH、IE、IL、DK、NZ、AT、BX、FI、WO。最大1000字符 |
| productTitle | string | 否 | - | 产品标题,用于补充检索上下文(最大1000字符) |
| productDescription | string | 否 | - | 产品描述,用于补充检索上下文(最大1000字符) |
| patentStatus | string | 否 | 1 | 专利有效性筛选:1(有效专利)、0(失效专利)、1,0(全部)。最大1000字符 |
| enableRadar | boolean | 否 | true | 是否启用雷达图(AI侵权判定分析) |
| topLoc | string | 否 | - | 指定检索的一级LOC范围(如 06,07)。格式:`^(0[1-9]\ |
| sourceLanguage | string | 否 | - | 原语言代码,需要标记以便统一翻译成英文(如 zh-CN)。文本为英语时传空即可。最大1000字符 |
响应结构
| 字段 | 类型 | 说明 |
|---|---|---|
| total | integer | 返回的专利记录总数 |
| data | array | 专利列表(详见下方专利对象) |
| columns | array | 渲染的列定义 |
| costToken | integer | 消耗token |
| type | string | 渲染的样式 |
专利对象(data 数组中的每个元素)
| 字段 | 类型 | 说明 |
|---|---|---|
| applicationNumber | string | 专利申请号 |
| publicationNumber | string | 专利公开号 |
| patentProd | string | 专利标题(英文) |
| patentProdCn | string | 专利标题(中文) |
| similarity | string | 专利与产品图片的相似度(0-1) |
| patentImageUrl | string | 与产品图片相似度最高的专利附图URL |
| images | array | 专利图片列表 |
| abstracts | string | 专利摘要 |
| specification | string | 专利说明书 |
| inventors | array | 发明人列表 |
| applicants | array | 申请人列表 |
| applicantAddresses | array | 申请人地址 |
| troCase | boolean | 是否有TRO维权史 |
| troHolder | boolean | 是否是TRO权利人的专利 |
| radarResult | object | AI雷达分析结果 |
| radarResult.same | boolean | 是否疑似侵权 |
| radarResult.exp | string | 预期描述(雷达判定说明) |
| patentLoc | string | 该专利的LOC分类(多个用逗号隔开) |
| locOneInfo | string | LOC一级详情 |
| locTwoInfo | string | LOC二级详情 |
| patentValidity | string | 专利有效性 |
| applicationDate | string | 专利申请日 |
| publicationDate | string | 专利公开日 |
| grantDate | string | 专利授权日 |
| estimatedDueDate | string | 预估到期日 |
| registrationOfficeCode | string | 专利注册受理局 |
| patentFamily | array | 同族专利列表 |
| globalPatentId | string | 全球专利ID |
| globalImageId | string | 专利图片的ID |
| isSketchText | string | 是否线稿图 |
错误码
正常情况下,接口的 HTTP 状态码均为 200,业务的成功与否通过响应体中的 errorCode 字段区分(errorCode = 200 表示成功,其他值表示业务错误)。当遇到未授权等情况时,HTTP 状态码为 401,且对应的 errorCode 也是 401。
| errcode | 含义 | 处理建议 |
|---|---|---|
| 200 | 成功 | 正常解析业务字段 |
| 401 | 认证失败 | 检查请求头 Authorization 是否正确携带 API Key;API Key 申请方式请参考上述调用规范下的认证方式。 |
| 其他非200值 | 业务异常 | 参考 errmsg 字段获取具体错误原因 |
错误响应示例:
{
"errcode": 401,
"errmsg": "authorized error"
}curl 示例
curl -X POST https://tool-gateway.linkfox.com/ruiguan/detectionPatentDesign \
-H "Authorization: $LINKFOXAGENT_API_KEY" \
-H "Content-Type: application/json" \
-d '{
"imageUrl": "https://example.com/product.jpg",
"queryMode": "hybrid",
"topNumber": 50,
"regions": "US",
"enableRadar": true
}'多地区检索示例
curl -X POST https://tool-gateway.linkfox.com/ruiguan/detectionPatentDesign \
-H "Authorization: $LINKFOXAGENT_API_KEY" \
-H "Content-Type: application/json" \
-d '{
"imageUrl": "https://example.com/product.jpg",
"queryMode": "physical",
"topNumber": 100,
"regions": "US,EU,CN",
"productTitle": "便携式无线充电支架",
"productDescription": "一款可折叠的智能手机无线充电支架",
"patentStatus": "1",
"enableRadar": true
}'---
Feedback API
This endpoint is separate from the tool API above. Do not mix the two base URLs.
- POST
https://skill-api.linkfox.com/api/v1/public/feedback - Content-Type:
application/json
{
"skillName": "linkfox-xxx-xxx",
"sentiment": "POSITIVE",
"category": "OTHER",
"content": "Results were accurate, user was satisfied."
}Field rules:
skillName: Use this skill'snamefrom the YAML frontmattersentiment: Choose ONE —POSITIVE(praise),NEUTRAL(suggestion without emotion),NEGATIVE(complaint or error)category: Choose ONE —BUG(malfunction or wrong data),COMPLAINT(user dissatisfaction),SUGGESTION(improvement idea),OTHERcontent: Include what the user said or intended, what actually happened, and why it is a problem or praise
#!/usr/bin/env python3
"""
Skill response I/O helper — wraps any main script to persist large API
responses to disk, then offers a `read` subcommand to extract specific fields
from those persisted files. Generic, business-agnostic.
This script is bundled into each skill's scripts/ directory by tools/response_io/sync.py.
The agent must pass --script <path> to identify which main script to execute.
Usage:
python scripts/response_io.py run --script <PATH> --out-dir <DIR> '<json_params>' [--label NAME] [--timeout SEC]
python scripts/response_io.py read <file> (--path "<JMESPath>" | --fields "f1,f2,...") [--limit N] [--offset M] [--format json|jsonl|csv|table]
"""
from __future__ import annotations
import sys
if sys.version_info < (3, 10):
sys.exit(
"Error: Python 3.10+ required (current: "
f"{sys.version_info.major}.{sys.version_info.minor}). "
"Please upgrade Python."
)
import argparse
import csv
import io
import json
import os
import re
import secrets
import subprocess
from datetime import datetime
from pathlib import Path
from typing import Any
# Force UTF-8 stdout/stderr so non-ASCII chars in previews and API responses
# print correctly on Windows (default cp936 / gbk).
for stream in (sys.stdout, sys.stderr):
try:
stream.reconfigure(encoding="utf-8") # type: ignore[attr-defined]
except (AttributeError, OSError):
pass
try:
import jmespath # type: ignore
HAS_JMESPATH = True
except ImportError:
HAS_JMESPATH = False
MAX_STRING_LEN = 120
MAX_DEPTH = 3
SAMPLE_KEY_CAP = 15
RAW_TEXT_PEEK = 500
DEFAULT_TIMEOUT_SEC = 300
# ---------------------------------------------------------------------------
# Shared helpers
# ---------------------------------------------------------------------------
def _err(msg: str, code: int = 1) -> None:
print(msg, file=sys.stderr)
sys.exit(code)
def _resolve_script(script_arg: str) -> Path:
p = Path(script_arg).expanduser()
if not p.is_absolute():
# Resolve relative to the current working directory the agent invoked from.
p = (Path.cwd() / p).resolve()
else:
p = p.resolve()
if not p.is_file():
_err(f"--script path not found: {p}")
return p
def _resolve_skill_name(main_script: Path) -> str:
"""Best-effort skill name extraction for filename prefixing.
main_script lives at <skill_dir>/scripts/<name>.py — return <skill_dir>'s
folder name. Fall back to the script's stem if structure differs.
"""
try:
if main_script.parent.name == "scripts":
return main_script.parents[1].name
except IndexError:
pass
return main_script.stem
def _sanitize_label(label: str) -> str:
"""Allow only safe filename chars in --label to prevent path traversal."""
cleaned = re.sub(r"[^\w\-]", "_", label)
return cleaned[:64] # cap length
def _truncate_string(s: str) -> str:
if len(s) <= MAX_STRING_LEN:
return s
return s[:MAX_STRING_LEN] + f"...(truncated, total {len(s)} chars)"
def _truncate_value(value: Any, depth: int = 0) -> Any:
"""Recursively truncate strings, deep nesting, and large arrays for preview."""
if depth >= MAX_DEPTH:
if isinstance(value, dict):
return f"<truncated nested object, keys: {list(value.keys())[:10]}>"
if isinstance(value, list):
return f"<truncated nested array, length: {len(value)}>"
if isinstance(value, str):
return _truncate_string(value)
return value
if isinstance(value, str):
return _truncate_string(value)
if isinstance(value, dict):
out = {k: _truncate_value(v, depth + 1) for k, v in value.items()}
return out
if isinstance(value, list):
if not value:
return []
truncated = [_truncate_value(value[0], depth + 1)]
if len(value) > 1:
# Note total length on the parent — keep the array type-homogeneous
# so downstream consumers can iterate without special-casing strings.
truncated.append({"_omitted_items": len(value) - 1})
return truncated
return value
def _shape_of(value: Any, top: bool = False) -> Any:
"""Lightweight schema description for the preview block."""
if isinstance(value, dict):
keys = list(value.keys())
out: dict[str, Any] = {"type": "object", "top_keys" if top else "keys": keys}
if top:
for k in keys[:8]:
out[k] = _shape_of(value[k])
return out
if isinstance(value, list):
out = {"type": "array", "length": len(value)}
if value and isinstance(value[0], dict):
out["item_keys"] = list(value[0].keys())
elif value:
out["item_type"] = type(value[0]).__name__
return out
return {"type": type(value).__name__}
def _build_sample(value: Any) -> Any:
"""First-record sample with explicit truncation marker."""
if isinstance(value, list):
if not value:
return {"_truncated_record": True, "_note": "array is empty"}
first = value[0]
if isinstance(first, dict):
sample = {"_truncated_record": True, "_note": f"first of {len(value)} items"}
sample.update(_truncate_value(first, depth=1))
return sample
return {"_truncated_record": True, "_note": f"first of {len(value)} items", "value": _truncate_value(first, depth=1)}
if isinstance(value, dict):
sample = {"_truncated_record": True, "_note": "top-level object (truncated)"}
sample.update(_truncate_value(value, depth=1))
return sample
return {"_truncated_record": True, "value": _truncate_value(value, depth=1)}
def _shrink_preview(preview: dict) -> dict:
"""Cap the sample's value fields when it has many keys.
`shape.*.item_keys` is the single source of truth for the full key list
(always complete, no truncation). The sample only ever shows up to
SAMPLE_KEY_CAP fields with their concrete values, since the agent only
needs a feel for value shapes — for the full menu of available fields,
they read `shape`.
"""
sample = preview.get("sample")
if isinstance(sample, dict):
meta_keys = {"_truncated_record", "_note"}
data_keys = [k for k in sample.keys() if k not in meta_keys]
if len(data_keys) > SAMPLE_KEY_CAP:
kept = data_keys[:SAMPLE_KEY_CAP]
new_sample = {k: v for k, v in sample.items() if k in meta_keys or k in kept}
base_note = sample.get("_note", "")
extra = (
f"showing first {SAMPLE_KEY_CAP} of {len(data_keys)} fields "
f"(see `shape` for the complete key list)"
)
new_sample["_note"] = f"{base_note}; {extra}" if base_note else extra
preview["sample"] = new_sample
return preview
# ---------------------------------------------------------------------------
# `run` subcommand
# ---------------------------------------------------------------------------
def cmd_run(args: argparse.Namespace) -> int:
main_script = _resolve_script(args.script)
skill_name = _resolve_skill_name(main_script)
out_dir = Path(args.out_dir).expanduser().resolve()
try:
out_dir.mkdir(parents=True, exist_ok=True)
except OSError as e:
_err(f"Failed to create --out-dir {out_dir}: {e}")
if not os.access(out_dir, os.W_OK):
_err(f"--out-dir is not writable: {out_dir}")
timestamp = datetime.now().strftime("%Y%m%d_%H%M%S")
rand = secrets.token_hex(3)
safe_label = _sanitize_label(args.label) if args.label else ""
label_part = f"__{safe_label}" if safe_label else ""
out_file = out_dir / f"{skill_name}__{timestamp}_{rand}{label_part}.json"
# Force the child process to emit UTF-8 regardless of the host console
# encoding (Windows defaults to cp936 / gbk and would otherwise corrupt
# non-ASCII bytes when we read them back).
child_env = os.environ.copy()
child_env["PYTHONIOENCODING"] = "utf-8"
timed_out = False
try:
proc = subprocess.run(
[sys.executable, str(main_script), args.params],
capture_output=True,
text=True,
encoding="utf-8",
errors="replace",
env=child_env,
timeout=args.timeout,
)
stdout_text = proc.stdout or ""
stderr_text = proc.stderr or ""
returncode = proc.returncode
except subprocess.TimeoutExpired as e:
timed_out = True
stdout_text = (e.stdout.decode("utf-8", errors="replace") if isinstance(e.stdout, bytes) else (e.stdout or "")) or ""
stderr_text = (e.stderr.decode("utf-8", errors="replace") if isinstance(e.stderr, bytes) else (e.stderr or "")) or ""
returncode = 124 # convention for timeout
# Always write the captured stdout to disk, even if not JSON.
try:
out_file.write_text(stdout_text, encoding="utf-8")
except OSError as e:
_err(f"Failed to write output file {out_file}: {e}")
if stderr_text:
sys.stderr.write(stderr_text)
# Try to parse the captured stdout as JSON for the preview.
try:
parsed = json.loads(stdout_text) if stdout_text.strip() else None
format_kind = "json"
except json.JSONDecodeError:
parsed = None
format_kind = "raw_text"
preview: dict[str, Any] = {
"_preview": {
"is_preview": True,
"warning": (
"PREVIEW ONLY — NOT FULL DATA. The full response is saved to `file`. "
"Use `python scripts/response_io.py read <file> --fields '...'` to extract "
"specific fields, or `--path '<JMESPath>'` for complex projections."
),
},
}
# Surface failures prominently so agents don't mistake a stub preview for success.
if returncode != 0 or timed_out:
stderr_snippet = stderr_text[-500:] if stderr_text else ""
preview["_error"] = {
"exit_code": returncode,
"timed_out": timed_out,
"stderr_snippet": stderr_snippet,
"hint": "The wrapped script failed or timed out. The output file may be empty or partial.",
}
preview.update({
"file": str(out_file),
"size_bytes": out_file.stat().st_size,
"skill": skill_name,
"exit_code": returncode,
"format": format_kind,
"label": safe_label or None,
"next_steps_hint": (
"use: python scripts/response_io.py read <file> --fields '...' | --path '...'"
),
})
if format_kind == "json":
preview["shape"] = _shape_of(parsed, top=True)
preview["sample"] = _build_sample(parsed)
else:
peek = stdout_text[:RAW_TEXT_PEEK]
preview["raw_text_peek"] = peek
preview["raw_text_total_chars"] = len(stdout_text)
preview["sample"] = {
"_truncated_record": True,
"_note": f"stdout was not valid JSON; first {RAW_TEXT_PEEK} chars shown above in raw_text_peek",
}
preview = _shrink_preview(preview)
print(json.dumps(preview, ensure_ascii=False, indent=2))
return returncode
# ---------------------------------------------------------------------------
# `read` subcommand
# ---------------------------------------------------------------------------
def _load_json(path: Path) -> Any:
try:
text = path.read_text(encoding="utf-8")
except OSError as e:
_err(f"Failed to read file {path}: {e}")
try:
return json.loads(text)
except json.JSONDecodeError as e:
_err(f"File is not valid JSON: {path}\n{e}")
def _basic_dot_path(data: Any, path: str) -> Any:
"""Pure-stdlib dot-path resolver. No [*] support — callers fall back here only when jmespath is unavailable AND the path has no [*]."""
cur = data
for part in path.split("."):
if isinstance(cur, dict):
cur = cur.get(part)
else:
return None
return cur
def _resolve_field(data: Any, expr: str) -> Any:
if HAS_JMESPATH:
return jmespath.search(expr, data)
if "[" in expr or "*" in expr:
_err(
f"jmespath is required for expression '{expr}'. "
f"Install with: pip install jmespath"
)
return _basic_dot_path(data, expr)
def _project_fields(data: Any, fields: list[str]) -> Any:
"""Run each field expr; if any returns a list, zip them into list-of-dicts."""
resolved: dict[str, Any] = {f: _resolve_field(data, f) for f in fields}
list_lengths = [len(v) for v in resolved.values() if isinstance(v, list)]
if not list_lengths:
return resolved
# All list values must be same length to zip cleanly.
if len(set(list_lengths)) > 1:
# Fallback: return the dict as-is so caller can inspect mismatches.
return resolved
n = list_lengths[0]
rows = []
for i in range(n):
row = {}
for f, v in resolved.items():
row[f] = v[i] if isinstance(v, list) else v
rows.append(row)
return rows
def _apply_slice(value: Any, limit: int | None, offset: int | None) -> Any:
if not isinstance(value, list):
return value
start = offset or 0
end = (start + limit) if limit is not None else None
return value[start:end]
def _format_output(value: Any, fmt: str) -> str:
if fmt == "json":
return json.dumps(value, ensure_ascii=False, indent=2)
if fmt == "jsonl":
if isinstance(value, list):
return "\n".join(json.dumps(item, ensure_ascii=False) for item in value)
return json.dumps(value, ensure_ascii=False)
if fmt in ("csv", "table"):
if not isinstance(value, list) or not value:
_err(f"--format {fmt} requires a non-empty list result")
if not all(isinstance(item, dict) for item in value):
_err(f"--format {fmt} requires list-of-objects, got list of {type(value[0]).__name__}")
keys: list[str] = []
for item in value:
for k in item.keys():
if k not in keys:
keys.append(k)
if fmt == "csv":
buf = io.StringIO()
writer = csv.DictWriter(buf, fieldnames=keys, extrasaction="ignore")
writer.writeheader()
for item in value:
writer.writerow({k: _stringify(item.get(k)) for k in keys})
return buf.getvalue().rstrip("\n")
# table: simple aligned columns
rows = [[_stringify(item.get(k)) for k in keys] for item in value]
widths = [len(k) for k in keys]
for row in rows:
for i, cell in enumerate(row):
widths[i] = max(widths[i], len(cell))
lines = [
" ".join(k.ljust(widths[i]) for i, k in enumerate(keys)),
" ".join("-" * widths[i] for i in range(len(keys))),
]
for row in rows:
lines.append(" ".join(row[i].ljust(widths[i]) for i in range(len(keys))))
return "\n".join(lines)
_err(f"Unknown --format: {fmt}")
return "" # unreachable
def _stringify(v: Any) -> str:
if v is None:
return ""
if isinstance(v, (dict, list)):
return json.dumps(v, ensure_ascii=False)
return str(v)
def cmd_read(args: argparse.Namespace) -> int:
if not args.path and not args.fields:
_err("read: either --path or --fields is required")
if args.path and args.fields:
_err("read: --path and --fields are mutually exclusive")
file_path = Path(args.file).expanduser().resolve()
data = _load_json(file_path)
if args.path:
result = _resolve_field(data, args.path)
else:
fields = [f.strip() for f in args.fields.split(",") if f.strip()]
if not fields:
_err("--fields parsed to empty list")
result = _project_fields(data, fields)
result = _apply_slice(result, args.limit, args.offset)
print(_format_output(result, args.format))
return 0
# ---------------------------------------------------------------------------
# CLI
# ---------------------------------------------------------------------------
def main() -> int:
parser = argparse.ArgumentParser(
prog="response_io.py",
description="Persist large skill API responses to disk and read fields on demand.",
)
sub = parser.add_subparsers(dest="cmd", required=True)
p_run = sub.add_parser(
"run",
help="Execute a main script and persist its stdout to a file; "
"print only a lightweight preview to stdout.",
)
p_run.add_argument("params", help="JSON params string passed verbatim to the main script (argv[1]).")
p_run.add_argument("--script", required=True, help="Path to the main script to execute, e.g. scripts/my_api.py")
p_run.add_argument("--out-dir", required=True, help="Directory to write the response file into (created if missing).")
p_run.add_argument("--label", default=None, help="Optional filename suffix; sanitized to safe filename characters.")
p_run.add_argument("--timeout", type=int, default=DEFAULT_TIMEOUT_SEC, help=f"Subprocess timeout in seconds (default: {DEFAULT_TIMEOUT_SEC}).")
p_run.set_defaults(func=cmd_run)
p_read = sub.add_parser(
"read",
help="Extract specific fields from a previously persisted response file.",
)
p_read.add_argument("file", help="Path to the persisted JSON response file.")
g = p_read.add_mutually_exclusive_group()
g.add_argument("--path", default=None, help="JMESPath expression, e.g. 'data[*].{asin: asin, title: title}'.")
g.add_argument("--fields", default=None, help="Comma-separated field paths, e.g. 'data[*].asin,data[*].title'.")
p_read.add_argument("--limit", type=int, default=None, help="Take at most N items (when result is a list).")
p_read.add_argument("--offset", type=int, default=None, help="Skip the first M items (when result is a list).")
p_read.add_argument("--format", choices=["json", "jsonl", "csv", "table"], default="json", help="Output format (default: json).")
p_read.set_defaults(func=cmd_read)
args = parser.parse_args()
return args.func(args)
if __name__ == "__main__":
sys.exit(main())
#!/usr/bin/env python3
"""
Ruiguan Design Patent Detection - LinkFox Skill
Calls the ruiguan/detectionPatentDesign API endpoint to check product images
against global design patent databases.
Usage:
python ruiguan_detection_patent_design.py '{"imageUrl": "https://example.com/product.jpg", "queryMode": "hybrid", "topNumber": 50, "regions": "US"}'
"""
import json
import os
import sys
from urllib.request import urlopen, Request
from urllib.error import HTTPError, URLError
API_URL = "https://tool-gateway.linkfox.com/ruiguan/detectionPatentDesign"
# Required parameters that must be present in the request
REQUIRED_PARAMS = ["imageUrl", "queryMode", "topNumber"]
# Default values applied when optional parameters are not provided
DEFAULTS = {
"queryMode": "hybrid",
"topNumber": 100,
"regions": "US",
"patentStatus": "1",
"enableRadar": True,
}
def get_api_key():
"""Retrieve the API key from environment, with a friendly prompt if missing."""
key = os.environ.get("LINKFOXAGENT_API_KEY")
if not key:
print(
"API Key not configured. Please complete authorization first:\n"
"1. Visit https://skill.linkfox.com/linkfoxskills/guide.htm to obtain your Key\n"
"2. Set the environment variable: export LINKFOXAGENT_API_KEY=your-key-here",
file=sys.stderr,
)
sys.exit(1)
return key
def validate_params(params: dict):
"""Validate that all required parameters are present."""
missing = [p for p in REQUIRED_PARAMS if p not in params]
if missing:
print(
f"Missing required parameters: {', '.join(missing)}\n"
f"Required: imageUrl (product image URL), queryMode (physical/line/hybrid), topNumber (1-100)",
file=sys.stderr,
)
sys.exit(1)
# Validate topNumber range
top_number = params.get("topNumber", 100)
if not isinstance(top_number, int) or top_number < 1 or top_number > 100:
print("topNumber must be an integer between 1 and 100", file=sys.stderr)
sys.exit(1)
# Validate queryMode value
query_mode = params.get("queryMode", "hybrid")
if query_mode not in ("physical", "line", "hybrid"):
print(
f"Invalid queryMode: '{query_mode}'. Must be one of: physical, line, hybrid",
file=sys.stderr,
)
sys.exit(1)
def apply_defaults(params: dict) -> dict:
"""Apply default values for optional parameters that are not provided."""
result = dict(params)
for key, default_value in DEFAULTS.items():
if key not in result:
result[key] = default_value
return result
def call_api(params: dict) -> dict:
"""Call the Ruiguan design patent detection API."""
api_key = get_api_key()
data = json.dumps(params).encode("utf-8")
req = Request(
API_URL,
data=data,
headers={
"Authorization": api_key,
"Content-Type": "application/json",
"User-Agent": "LinkFox-Skill/1.0",
},
method="POST",
)
try:
# Use a longer timeout since patent detection can be slow
with urlopen(req, timeout=120) as response:
return json.loads(response.read().decode("utf-8"))
except HTTPError as e:
body = e.read().decode("utf-8") if e.fp else ""
return {"error": f"HTTP {e.code}: {e.reason}", "details": body}
except URLError as e:
return {"error": f"Connection failed: {e.reason}"}
def summarize_results(result: dict):
"""Print a human-readable summary of high-risk patents."""
data = result.get("data", [])
total = result.get("total", 0)
print(f"\n--- Detection Summary ---")
print(f"Total patents found: {total}")
# Filter high-risk patents (similarity >= 0.7 or has TRO history)
high_risk = []
for patent in data:
similarity = float(patent.get("similarity", 0))
tro_case = patent.get("troCase", False)
tro_holder = patent.get("troHolder", False)
if similarity >= 0.7 or tro_case or tro_holder:
high_risk.append(patent)
if high_risk:
print(f"High-risk patents (similarity >= 0.7 or TRO history): {len(high_risk)}")
print()
for i, patent in enumerate(high_risk, 1):
print(f" [{i}] {patent.get('applicationNumber', 'N/A')}")
print(f" Title: {patent.get('patentProd', 'N/A')}")
print(f" Title (CN): {patent.get('patentProdCn', 'N/A')}")
print(f" Similarity: {patent.get('similarity', 'N/A')}")
print(f" TRO Case: {patent.get('troCase', False)}")
print(f" TRO Holder: {patent.get('troHolder', False)}")
radar = patent.get("radarResult", {})
if radar:
print(f" Radar - Suspected Infringement: {radar.get('same', 'N/A')}")
print(f" Radar - Explanation: {radar.get('exp', 'N/A')}")
print()
else:
print("No high-risk patents found (none with similarity >= 0.7 or TRO history).")
print("Note: This detection result is generated by LinkfoxAgent.")
print("It is recommended to consult a professional IP attorney for legal advice.")
def main():
if len(sys.argv) < 2:
print("Usage: ruiguan_detection_patent_design.py '<JSON parameters>'", file=sys.stderr)
print(
"Example: ruiguan_detection_patent_design.py "
"'{\"imageUrl\": \"https://example.com/product.jpg\", \"queryMode\": \"hybrid\", \"topNumber\": 50}'",
file=sys.stderr,
)
print(
"\nRequired parameters:\n"
" imageUrl - Product image URL\n"
" queryMode - Search mode: physical, line, or hybrid\n"
" topNumber - Number of results (1-100)\n"
"\nOptional parameters:\n"
" regions - Country codes, e.g., US,EU,CN (default: US)\n"
" productTitle - Product title\n"
" productDescription - Product description\n"
" patentStatus - 1 (active), 0 (expired), 1,0 (both) (default: 1)\n"
" enableRadar - Enable radar analysis (default: true)\n"
" topLoc - LOC codes, e.g., 06,07\n"
" sourceLanguage - Source language, e.g., zh-CN",
file=sys.stderr,
)
sys.exit(1)
try:
params = json.loads(sys.argv[1])
except json.JSONDecodeError as e:
print(f"Invalid parameter format: {e}", file=sys.stderr)
sys.exit(1)
# Validate required parameters
validate_params(params)
# Apply defaults for optional parameters
params = apply_defaults(params)
# Call the API
result = call_api(params)
# Print full JSON response
print(json.dumps(result, indent=2, ensure_ascii=False))
# If successful and contains data, print a summary
if "error" not in result and "data" in result:
summarize_results(result)
if __name__ == "__main__":
main()
#!/usr/bin/env python3
"""
Upload Local Image - LinkFox Skill
Uploads a local image file to LinkFox OSS and returns a publicly accessible URL.
Steps:
1. Request a presigned PUT URL from the LinkFox OSS gateway
2. Upload the local file to the presigned URL
3. Return the public URL (valid for 24 hours)
Usage:
python upload_image.py /path/to/local/image.png
"""
import json
import os
import sys
from urllib.request import urlopen, Request
from urllib.error import HTTPError, URLError
PRESIGN_URL = "https://tool-gateway.linkfox.com/oss/file/presignedPut"
CONTENT_TYPE_MAP = {
"jpg": "image/jpeg",
"jpeg": "image/jpeg",
"png": "image/png",
"gif": "image/gif",
"webp": "image/webp",
"heic": "image/heic",
}
def get_api_key():
"""Retrieve the API key from environment, with a friendly prompt if missing."""
key = os.environ.get("LINKFOXAGENT_API_KEY")
if not key:
print(
"API Key not configured. Please complete authorization first:\n"
"1. Visit https://skill.linkfox.com/linkfoxskills/guide.htm to obtain your Key\n"
"2. Set the environment variable: export LINKFOXAGENT_API_KEY=your-key-here",
file=sys.stderr,
)
sys.exit(1)
return key
def get_presigned_url(content_type: str, file_extension: str) -> str:
"""Request a presigned PUT URL from the OSS gateway."""
api_key = get_api_key()
data = json.dumps({
"contentType": content_type,
"fileExtension": file_extension,
}).encode("utf-8")
req = Request(
PRESIGN_URL,
data=data,
headers={
"Authorization": api_key,
"Content-Type": "application/json",
"User-Agent": "LinkFox-Skill/1.0",
},
method="POST",
)
try:
with urlopen(req, timeout=30) as response:
result = json.loads(response.read().decode("utf-8"))
except HTTPError as e:
body = e.read().decode("utf-8") if e.fp else ""
print(f"Failed to get presigned URL: HTTP {e.code}: {e.reason}\n{body}", file=sys.stderr)
sys.exit(1)
except URLError as e:
print(f"Connection failed: {e.reason}", file=sys.stderr)
sys.exit(1)
if result.get("errcode") != 200:
print(f"API error: {result.get('errmsg', 'unknown error')}", file=sys.stderr)
sys.exit(1)
return result["url"]
def upload_file(presigned_url: str, file_path: str, content_type: str):
"""Upload the local file to the presigned OSS URL via HTTP PUT."""
with open(file_path, "rb") as f:
file_data = f.read()
req = Request(
presigned_url,
data=file_data,
headers={
"Content-Type": content_type,
"x-oss-object-acl": "public-read",
},
method="PUT",
)
try:
with urlopen(req, timeout=120) as response:
if response.status not in (200, 201):
print(f"Upload failed with status: {response.status}", file=sys.stderr)
sys.exit(1)
except HTTPError as e:
body = e.read().decode("utf-8") if e.fp else ""
print(f"Upload failed: HTTP {e.code}: {e.reason}\n{body}", file=sys.stderr)
sys.exit(1)
except URLError as e:
print(f"Upload connection failed: {e.reason}", file=sys.stderr)
sys.exit(1)
def extract_public_url(presigned_url: str) -> str:
"""Extract the base public URL by stripping query parameters."""
return presigned_url.split("?")[0]
def main():
if len(sys.argv) < 2:
print(
"Usage: upload_image.py <local_image_path>\n"
"Example: upload_image.py /path/to/product.png",
file=sys.stderr,
)
sys.exit(1)
file_path = sys.argv[1]
if not os.path.isfile(file_path):
print(f"File not found: {file_path}", file=sys.stderr)
sys.exit(1)
extension = os.path.splitext(file_path)[1].lstrip(".").lower()
content_type = CONTENT_TYPE_MAP.get(extension)
if not content_type:
print(
f"Unsupported image format: .{extension}\n"
f"Supported formats: {', '.join(CONTENT_TYPE_MAP.keys())}",
file=sys.stderr,
)
sys.exit(1)
# Step 1: Get presigned URL
presigned_url = get_presigned_url(content_type, extension)
# Step 2: Upload file
upload_file(presigned_url, file_path, content_type)
# Step 3: Output public URL
public_url = extract_public_url(presigned_url)
print(json.dumps({"url": public_url}, indent=2, ensure_ascii=False))
if __name__ == "__main__":
main()