Skills Plugins MCP Prompt Model 博客 我的中心
内容创作 #data #api #ai

airbnb-listing-detail

Fetches complete Airbnb listing details for a given numeric listing ID via the internal GraphQL API, returning title, room type, description, amenities, photos, coordinates, city, house rules, highlights, ratings, review count, bedroom configuration, and property overview. Use when user mentions Airbnb listing details, Airbnb property info, Airbnb room details, get Airbnb listing data, Airbnb amenities list, Airbnb house rules, Airbnb property description, Airbnb detail page scraper, Airbnb rooms detail, Airbnb property page data, Airbnb listing info, fetch Airbnb room details, pull Airbnb listing.

DeepseekModel 官方收录技能 质量 优秀 · 90 v1.0.0

获取

https://deepseekmodel.com/api/download.php?id=browser-act-skills-solutions-ecommerce-airbnb-listing-detail-skill-md&format=skill
下载 .skill 标准格式,含 system_prompt 与 model_config,导入任意 Agent 框架即可使用
.skill 文件中 system_prompt 字段的实际内容。
name airbnb-listing-detail description Fetches complete Airbnb listing details for a given numeric listing ID via the internal GraphQL API, returning title, room type, description, amenities, photos, coordinates, city, house rules, highlights, ratings, review count, bedroom configuration, and property overview. Use when user mentions Airbnb listing details, Airbnb property info, Airbnb room details, get Airbnb listing data, Airbnb amenities list, Airbnb house rules, Airbnb property description, Airbnb detail page scraper, Airbnb rooms detail, Airbnb property page data, Airbnb listing info, fetch Airbnb room details, pull Airbnb listing. Airbnb — Listing Detail Listing ID → full property detail via internal GraphQL API (no login required) Language All process output to user (progress updates, process notifications) follows the user's language. Objective Fetch comprehensive listing data for an Airbnb property using the internal StaysPdpSections GraphQL API. Prerequisites Browser is open (any page). The API call is made via fetch() in the browser context — no specific page navigation required. No login required — the API endpoint is publicly accessible Pre-execution Checks 1. Tool Readiness If browser-act has been confirmed available in the current session → skip this step. Invoke browser-act via Skill tool to load usage. If installation or configuration issues arise, follow its guidance to resolve then retry. Capability Components This Skill's operational boundary = what the user can manually do in their browser. It only reads data already displayed to the user on the page, never bypassing authentication or access controls. JS code is encapsulated in Python files under the scripts/ directory, invoked via eval "$(python scripts/xxx.py {params})" . $(...) is bash syntax; it is recommended to use the bash tool for execution. API: fetch listing detail eval "$(python scripts/listing-detail.py '{listing_id}')" Parameters: listing_id : numeric Airbnb listing ID (e.g., 5476930 ). Extract from listing URL: airbnb.com/rooms/{listing_id} --checkin : check-in date in YYYY-MM-DD format, default: none (price info unavailable without dates) --checkout : check-out date in YYYY-MM-DD format, default: none --adults : number of adult guests, default: 1 --locale : response locale, default: en --currency : price currency code, default: USD Output example: { "id" : "5476930" , "url" : "https://www.airbnb.com/rooms/5476930" , "title" : "Bright Studio in Notting Hill" , "room_type" : "ENTIRE_HOME" , "description" : "<p>Welcome to this charming studio...</p>" , "photos" : [ "https://a0.muscache.com/im/pictures/...jpeg" ] , "lat" : 51.5101 , "lng" : -0.1949 , "city" : "London, England, United Kingdom" , "amenities" : [ { "name" : "Kitchen" , "available" : true } , { "name" : "Wifi" , "available" : true } ] , "house_rules" : [ "Check-in after 3:00 PM" , "Checkout before 11:00 AM" , "1 guest maximum" ] , "highlights" : [ { "title" : "Self check-in" , "subtitle" : "Check yourself in with the keypad." } ] , "rating_overall" : 4.85 , "review_count" : 142 , "ratings" : [ { "category" : "CLEANLINESS" , "value" : "4.9" } , { "category" : "LOCATION" , "value" : "4.8" } ] , "bedrooms" : [ { "title" : "Bedroom 1" , "subtitle" : "1 king bed" } ] } Error handling: If error: true is returned with HTTP 4xx, verify the listing ID is valid by visiting https://www.airbnb.com/rooms/{listing_id} in the browser. If No data in response is returned, the listing may have been removed or the API schema may have changed — check the raw field for details. Pagination Not applicable — each call returns complete detail for one listing. Success Criteria title is not null AND amenities.length >= 1 AND photos.length >= 1 Known Limitations rating_overall and review_count are null for new listings with no reviews bedrooms array may be empty for studio or hotel-style rooms Host personal details (bio, profile photo, response rate) are not available from this endpoint — they return as deferred sentinel sections Price per night is not included in the response without --checkin and --checkout dates Calling this endpoint too rapidly may trigger rate limiting; add 1-2 second delays between batch requests Execution Efficiency Batch orchestration : Write a bash script to loop through listing IDs serially with a 1-second delay between calls Test before batch execution : After writing a batch script, test with 1-2 listing IDs to verify output before running full batch Error resumption : Save results per listing ID; resume from the breakpoint on failure Experience Notes Path: {working-directory}/browser-act-skill-forge-memories/airbnb-scraper-airbnb-listing-detail.memory.md Before execution : If the file exists, read it first — it records unexpected situations encountered during past executions (e.g., a strategy has become ineffective); adjust strategy order accordingly. After execution : If an unexpected situation is encountered (strategy became ineffective, page redesigned, anti-scraping upgraded, better path discovered), append a line: {YYYY-MM-DD}: {what happened} → {conclusion} Normal execution does not write to the file. Do not record what listing IDs were fetched or how many results were returned — those are task outputs, not experience.
Agent 识别该技能的关键词,点击任意一个即可复制。

该技能未提供触发词。

下载的 .skill 包内含以下字段。
字段 说明
format格式标识(skill/v1)
skill_id技能唯一 ID
name技能名称
version版本号
description技能描述
category所属分类(数组)
trigger_words触发词列表
tags标签列表
source来源标识
source_url来源链接(本页地址)
exported_at导出时间(每次下载生成)
system_prompt系统提示词正文
model_config模型参数:provider / model / temperature / max_tokens / top_p
examples示例
install_guide各平台导入说明(Coze / Dify / Claude / 自定义框架)
同一份技能可按不同平台格式导出。
.skill 标准格式,含 system_prompt 与 model_config,导入任意 Agent 框架即可使用 下载
.skillpro 增强格式,额外含脚本 / 工具 / 依赖 / 钩子占位 下载
.json 纯 JSON 导出,只含 system_prompt 与模型参数 下载
Coze 带 frontmatter 的 Markdown,Coze 平台导入用 下载
Dify Dify DSL,创建应用后直接导入 下载

每日精选 Skill 推荐,免费送到你邮箱

输入邮箱,每天接收一个精选 AI Agent 技能推荐。完全免费,持续更新。

提交后我们会发送一封确认邮件,点击邮件里的链接才会开始收信。

完全免费,取消任意时间。我们不会发送垃圾邮件。