
Linkfox 1688 Search By Image
- 177 installs
- 64 repo stars
- Updated August 3, 2026
- linkfox-ai/linkfox-skills
Helps with ai & agent building tasks.
About
linkfox-1688-search-by-image is a Claude Code skill for ai & agent building. It helps solo builders move faster with AI-assisted development.
- linkfox-1688-search-by-image
- AI & Agent Building
- AI-coding skill
Linkfox 1688 Search By Image by the numbers
- 177 all-time installs (skills.sh)
- +46 installs in the week ending Aug 2, 2026 (Skillselion tracking)
- Ranked #3,076 of 16,546 AI & Agent Building skills by installs in the Skillselion catalog
- Data as of Aug 4, 2026 (Skillselion catalog sync)
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| Installs | 177 |
|---|---|
| repo stars | ★ 64 |
| Last updated | August 3, 2026 |
| Repository | linkfox-ai/linkfox-skills ↗ |
What it does
Helps with ai & agent building tasks.
Files
1688 Image-Based Product Search
This skill performs visual product searches on the 1688 platform using an image URL, helping cross-border sellers find visually similar supplier products for sourcing.
Core Concepts
1688 Image Search uses visual recognition to find products with similar appearance on the 1688 wholesale marketplace. It returns supplier product data including title, price, minimum order quantity, monthly sales, repurchase rate, trade score, and seller identity badges.
Data Fields
| Field | Description |
|---|---|
| offerId | Product ID on 1688 |
| title | Product title |
| imageUrl | Product main image |
| price | Wholesale price (CNY) |
| consignPrice | Dropship price (CNY) |
| salesQuantity | Monthly sales volume |
| estimatedSalesAmount | Estimated monthly revenue |
| quantityBegin | Minimum order quantity |
| repurchaseRate | Repurchase rate |
| tradeScore | Product trade score |
| compositeServiceScore | Composite service experience score |
| sellerIdentities | Seller identity (超级工厂/实力商家/诚信通会员) |
| offerIdentities | Product badge (严选) |
| sendGoodsAddressText | Shipping origin |
| deliveryTime | Delivery time (24/48 hours) |
| isOnePsale | Supports dropshipping (是/否) |
| isJxhy | Premium sourcing (是/否) |
| hasPromotion | Has promotion (是/否) |
| isPatentProduct | Patent product (是/否) |
Parameter Guide
Image Rules: 1. Only png, jpg, jpeg formats are supported. webp, gif, and other formats are NOT supported. 2. Base64 string must be pure encoded content WITHOUT the data:image/jpeg;base64, prefix. 3. Image source — one of imageUrl, imageBase64, or imageId must be provided (at least one required).
| Parameter | Required | Default | Description |
|---|---|---|---|
| imageUrl | Conditional | - | Public image URL (max 1000 chars). Only png/jpg/jpeg formats supported |
| imageBase64 | Conditional | - | Pure Base64 encoded image string, without data:image/...;base64, prefix. Only png/jpg/jpeg supported |
| imageId | Conditional | - | 1688 image ID from previous search result (speeds up pagination) |
| page | No | 1 | Page number, starting from 1 |
| pageSize | No | 20 | Results per page (1-50) |
| priceStart | No | - | Min price filter (CNY) |
| priceEnd | No | - | Max price filter (CNY) |
| filter | No | - | Filter conditions, comma-separated (see supported filters below) |
| sort | No | {"monthSold":"desc"} | Sort as JSON: {field: direction} (see supported sort fields below) |
| keyword | No | - | Keyword to further filter results |
| productCollectionId | No | - | Product collection ID (see supported IDs below) |
Supported Filters
Multiple filters can be combined with commas (e.g. 1688Selection,totalEpScoreLv1,qrr0).
| Filter Value | Description |
|---|---|
| 1688Selection | 1688严选 |
| certifiedFactory | 认证工厂 |
| totalEpScoreLv1 | 综合体验分5星 |
| totalEpScoreLv2 | 综合体验分4星 |
| totalEpScoreLv3 | 综合体验分3星 |
| totalEpScoreLv4 | 综合体验分2星 |
| qrr0 | 无品质退款 |
| qrr1 | 品质退款率<1% |
| qrr5 | 品质退款率<5% |
| qrr10 | 品质退款率<10% |
| shipInToday | 当日发货 |
| shipIn24Hours | 24小时发货 |
| shipIn48Hours | 48小时发货 |
| noReason7DReturn | 7天无理由退货 |
| isOnePsale | 一件代发 |
| isOnePsaleFreePost | 一件代发包邮 |
| new7 | 7天内新品 |
| new30 | 30天内新品 |
| isQqyx | 全球严选 |
| JPFL | 日本专线 |
| USFL | 美国专线 |
| KRFL | 韩国专线 |
| VNFL | 越南专线 |
| SAFL | 沙特专线 |
| RUFL | 俄罗斯专线 |
| KZFL | 哈萨克斯坦专线 |
| HKFL | 香港专线 |
| MOFL | 澳门专线 |
| TWFL | 台湾专线 |
Supported Sort Fields
| Field | Direction | Description |
|---|---|---|
| price | asc/desc | Price ascending/descending |
| monthSold | asc/desc | Monthly sales ascending/descending |
| rePurchaseRate | asc/desc | Repurchase rate ascending/descending |
Sort format example: {"price":"asc"} for price low to high.
Supported Product Collection IDs
| ID | Usage |
|---|---|
| 262105288 | 跨境货盘 |
| 262105286 | 跨境货盘 |
| 262105253 | 跨境货盘 |
| 262105281 | 跨境货盘 |
| 262105280 | 跨境货盘 |
| 262105277 | 跨境货盘 |
| 262105276 | 跨境货盘 |
| 262105274 | 跨境货盘 |
| 262105269 | 跨境货盘 |
| 262185282 | 跨境货盘 |
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/alibaba1688_image_search.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, 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 imageUrl parameter.
Usage Examples
1. Basic image search
在1688搜索与图片相似的商品,图片地址为 https://m.media-amazon.com/images/I/719mRAn2VrL._AC_SL1500_.jpg2. Search with filters
在1688搜索与图片相似的商品,图片地址为 https://m.media-amazon.com/images/I/719mRAn2VrL._AC_SL1500_.jpg,查询第1页,筛选1688严选,并按价格从高到低排序3. Search with sorting
在1688搜索与图片相似的商品,图片地址为 https://example.com/product.jpg,按价格从高到低排序4. Paginated search
在1688搜索与图片相似的商品,图片地址为 https://example.com/product.jpg,查询第2页,每页50条5. Price range filter
在1688搜索与图片相似的商品,图片地址为 https://example.com/product.jpg,价格区间10-100元Display Rules
1. Present data clearly: Show results in a structured table with key columns: product image, title, price, dropship price, monthly sales, minimum order quantity, repurchase rate, and seller identity 2. Image display: When the response includes imageUrl for products, display them inline for visual comparison 3. Price display: Always show price in CNY (¥) format 4. Seller badges: Display seller identity badges (超级工厂/实力商家/诚信通会员) and product badges (严选) prominently 5. Result count: Always inform the user of total results and current page/total pages 6. Pagination hint: When more pages are available, suggest the user can request the next page 7. Filter/sort limitation: If the user requests a sort or filter not in the supported list, do NOT attempt any workaround. Inform the user of the supported options 8. No secondary processing: Results are real-time and not stored in a database, so secondary SQL/data processing is not available
Important Limitations
1. Data real-time nature: Results are live searches, not stored in any database. Cannot use _dataQuery_executeDynamicQuery for secondary processing. 2. Logic constraint: If the user requests sort or filter conditions not in the preset supported list, do NOT call any other tool or logic to compensate. 3. Image input: One of imageUrl, imageBase64, or imageId is required. For page > 1, prefer passing imageId from the first page result to speed up queries. 4. Image format: Only png, jpg, jpeg are supported. webp, gif, and other formats will be rejected. 5. Base64 format: The imageBase64 value must be the raw Base64 string only — do NOT include the data:image/jpeg;base64, prefix. 6. Page size: Maximum 50 results per page.
User Expression & Scenario Quick Reference
Applicable -- Visual product sourcing scenarios on 1688:
| User Says | Scenario |
|---|---|
| "1688以图搜图" / "用图片找1688货源" | Basic image search |
| "帮我在1688找这个图片的同款" | Find same-style products |
| "跨境找工厂,图片是..." | Cross-border supplier sourcing |
| "这个Amazon产品在1688有没有货源" | Reverse sourcing from Amazon image |
| "筛选1688严选的相似商品" | Filtered image search |
| "按月销量排序找相似货源" | Sorted image search |
| "查看第2页结果" | Pagination |
Not applicable -- Needs beyond 1688 image search:
- Text/keyword-based 1688 search (use 店雷达-1688选品库)
- 1688 product rankings/trending (use 店雷达-1688商品榜单)
- Amazon image search (use 亚马逊前端-以图搜图)
- Image generation or editing
- Product review analysis
- Price history or trend analysis
Boundary judgment: When users say "找货源" or "找同款", if they provide an image URL and the intent is to find visually similar products on 1688, this skill applies. If they want keyword-based search or ranking data on 1688, use the 店雷达 tools instead.
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/alibaba1688_image_search.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:alibaba1688_image_search.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, visit [LinkFox Skills](https://skill.linkfox.com/).
1688-以图搜图 API 参考
调用规范
- 请求地址:
https://tool-gateway.linkfox.com/alibaba1688/imageSearch - 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) - User-Agent:
LinkFox-Skill/1.0 - 超时:60s
请求参数
POST Body(JSON):
| 参数 | 类型 | 必填 | 默认值 | 说明 |
|---|---|---|---|---|
| imageUrl | string | 条件必填 | - | 图片URL地址,请确保图片URL有效且可公开访问。最大长度:1000。仅支持 png/jpg/jpeg 格式,不支持 webp/gif 等。imageUrl/imageBase64/imageId 三选一必填 |
| imageBase64 | string | 条件必填 | - | 图片 Base64 编码字符串,为纯编码内容,不包含 data:image/jpeg;base64, 前缀。仅支持 png/jpg/jpeg 格式(imageUrl为空时使用) |
| imageId | string | 条件必填 | - | 图片ID(1688图片ID),以图搜图查询结果中也会返回,建议当分页 page>1 查询时带 imageId,加快响应速度 |
| page | int | 否 | 1 | 页码,从1开始 |
| pageSize | int | 否 | 20 | 每页返回的商品数量,最大不超过50 |
| priceStart | string | 否 | - | 价格筛选起始值(人民币),如 10 |
| priceEnd | string | 否 | - | 价格筛选结束值(人民币),如 100 |
| filter | string | 否 | - | 过滤条件,多个条件用逗号分隔。有效值见下方「支持的过滤条件」 |
| sort | string | 否 | {"monthSold":"desc"} | 排序条件,JSON格式 {排序字段: 排序方式}。有效字段:price、rePurchaseRate、monthSold;方式:asc/desc |
| keyword | string | 否 | - | 关键词,在结果中搜索 |
| productCollectionId | string | 否 | - | 货盘ID,单选。有效值见下方「支持的货盘ID」 |
支持的过滤条件
多个条件用逗号分隔,如 1688Selection,totalEpScoreLv1,qrr0。
| 值 | 说明 |
|---|---|
| 1688Selection | 1688严选 |
| certifiedFactory | 认证工厂 |
| totalEpScoreLv1 | 综合体验分5星 |
| totalEpScoreLv2 | 综合体验分4星 |
| totalEpScoreLv3 | 综合体验分3星 |
| totalEpScoreLv4 | 综合体验分2星 |
| qrr0 | 无品质退款 |
| qrr1 | 品质退款率<1% |
| qrr5 | 品质退款率<5% |
| qrr10 | 品质退款率<10% |
| shipInToday | 当日发货 |
| shipIn24Hours | 24小时发货 |
| shipIn48Hours | 48小时发货 |
| noReason7DReturn | 7天无理由退货 |
| isOnePsale | 一件代发 |
| isOnePsaleFreePost | 一件代发包邮 |
| new7 | 7天内新品 |
| new30 | 30天内新品 |
| isQqyx | 全球严选 |
| JPFL | 日本专线 |
| USFL | 美国专线 |
| KRFL | 韩国专线 |
| VNFL | 越南专线 |
| SAFL | 沙特专线 |
| RUFL | 俄罗斯专线 |
| KZFL | 哈萨克斯坦专线 |
| HKFL | 香港专线 |
| MOFL | 澳门专线 |
| TWFL | 台湾专线 |
支持的排序字段
| 字段 | 说明 |
|---|---|
| price | 价格 |
| monthSold | 月销量 |
| rePurchaseRate | 复购率 |
排序方式:asc(升序)、desc(降序)。格式示例:{"price":"asc"}
支持的货盘ID
| ID | 说明 |
|---|---|
| 262105288 | 跨境货盘 |
| 262105286 | 跨境货盘 |
| 262105253 | 跨境货盘 |
| 262105281 | 跨境货盘 |
| 262105280 | 跨境货盘 |
| 262105277 | 跨境货盘 |
| 262105276 | 跨境货盘 |
| 262105274 | 跨境货盘 |
| 262105269 | 跨境货盘 |
| 262185282 | 跨境货盘 |
响应结构
| 字段 | 类型 | 说明 |
|---|---|---|
| imageId | string | 上传后的图片ID(分页查询时回传可加速) |
| total | integer | 本页商品数量 |
| totalPage | integer | 总页数 |
| sourceType | string | 来源类型(固定值 "1688") |
| type | string | 渲染样式(固定值 "productWorkbenches") |
| columns | array | 渲染列定义 |
| costToken | integer | 消耗 token |
| products | array | 商品列表(详见下方商品字段) |
商品字段
| 字段 | 类型 | 说明 |
|---|---|---|
| offerId | string | 商品ID |
| asin | string | 商品编号(同 offerId) |
| imageUrl | string | 商品图片 |
| title | string | 商品标题 |
| price | number | 批发价(元) |
| consignPrice | number | 一件代发价(元) |
| salesQuantity | integer | 月销售件数 |
| estimatedSalesAmount | number | 预估销售额 |
| asinUrl | string | 商品链接 |
| isOnePsale | string | 是否一件代发(是/否) |
| isJxhy | string | 是否精选货源(是/否) |
| sellerIdentities | string | 商家身份(超级工厂/实力商家/诚信通会员) |
| offerIdentities | string | 商品标(严选) |
| repurchaseRate | string | 复购率 |
| tradeScore | string | 商品交易评分 |
| compositeServiceScore | string | 综合服务体验分 |
| sendGoodsAddressText | string | 发货地 |
| deliveryTime | string | 发货时间(24/48小时) |
| quantityBegin | integer | 起批量 |
| hasPromotion | string | 是否有营销活动(是/否) |
| promotionType | string | 营销类型 |
| isPatentProduct | string | 是否专利商品(是/否) |
| isSelect | string | 跨境select货盘标识 |
| currency | string | 币种(固定值 "¥") |
| sourceType | string | 来源类型(固定值 "1688") |
| sourceTool | string | 来源工具(固定值 "1688以图搜图") |
| dataType | string | 数据类型(固定值 "monthlyData") |
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
基础以图搜图
curl -X POST https://tool-gateway.linkfox.com/alibaba1688/imageSearch \
-H "Authorization: $LINKFOXAGENT_API_KEY" \
-H "Content-Type: application/json" \
-H "User-Agent: LinkFox-Skill/1.0" \
-d '{
"imageUrl": "https://m.media-amazon.com/images/I/719mRAn2VrL._AC_SL1500_.jpg",
"page": 1,
"pageSize": 20
}'带筛选和排序
curl -X POST https://tool-gateway.linkfox.com/alibaba1688/imageSearch \
-H "Authorization: $LINKFOXAGENT_API_KEY" \
-H "Content-Type: application/json" \
-H "User-Agent: LinkFox-Skill/1.0" \
-d '{
"imageUrl": "https://m.media-amazon.com/images/I/719mRAn2VrL._AC_SL1500_.jpg",
"page": 1,
"pageSize": 20,
"filter": "1688Selection,totalEpScoreLv1,qrr0",
"sort": "{\"price\":\"desc\"}"
}'分页查询(使用 imageId)
curl -X POST https://tool-gateway.linkfox.com/alibaba1688/imageSearch \
-H "Authorization: $LINKFOXAGENT_API_KEY" \
-H "Content-Type: application/json" \
-H "User-Agent: LinkFox-Skill/1.0" \
-d '{
"imageId": "abc123456",
"page": 2,
"pageSize": 20
}'价格区间筛选
curl -X POST https://tool-gateway.linkfox.com/alibaba1688/imageSearch \
-H "Authorization: $LINKFOXAGENT_API_KEY" \
-H "Content-Type: application/json" \
-H "User-Agent: LinkFox-Skill/1.0" \
-d '{
"imageUrl": "https://m.media-amazon.com/images/I/719mRAn2VrL._AC_SL1500_.jpg",
"page": 1,
"pageSize": 20,
"priceStart": "10",
"priceEnd": "100"
}'---
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-1688-search-by-image",
"sentiment": "POSITIVE",
"category": "OTHER",
"content": "Results were accurate, user was satisfied."
}Field rules:
skillName: Use this skill'snamefrom the YAML frontmatter (linkfox-1688-search-by-image)sentiment: 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
"""
1688 Image-Based Product Search - LinkFox Skill
Calls the alibaba1688/imageSearch API endpoint
Usage:
python alibaba1688_image_search.py '{"imageUrl": "https://example.com/image.jpg", "page": 1}'
"""
from __future__ import annotations
import json
import os
import sys
from urllib.request import urlopen, Request
from urllib.error import HTTPError, URLError
if sys.version_info < (3, 10):
sys.exit("Python 3.10+ is required. Current version: %s" % sys.version)
if sys.platform == "win32":
sys.stdout.reconfigure(encoding="utf-8")
sys.stderr.reconfigure(encoding="utf-8")
API_URL = "https://tool-gateway.linkfox.com/alibaba1688/imageSearch"
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 call_api(params: dict) -> dict:
"""Call the tool gateway 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:
with urlopen(req, timeout=60) 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 main():
if len(sys.argv) < 2:
print("Usage: alibaba1688_image_search.py '<JSON parameters>'", file=sys.stderr)
print(
'Example: alibaba1688_image_search.py \'{"imageUrl": "https://m.media-amazon.com/images/I/719mRAn2VrL._AC_SL1500_.jpg", "page": 1}\'',
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)
result = call_api(params)
print(json.dumps(result, indent=2, ensure_ascii=False))
if __name__ == "__main__":
main()
#!/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
"""
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()