AI Product Launch Monitor

面向 AI 产品发布跟踪的命令行流水线：抓取 AI/科技 RSS 源并按发布信号过滤去重，用 Brave 搜索 API 或 DuckDuckGo 补充信息，Playwright 无头 Chromium 截图，再按关键词、搜索结果数、截图与时效打分分类排序，输出 Markdown 报告与结构化 JSON。

terrycarter1985

热度 16.09

最近更新 2026-08-01 07:25:14

分类：数据依赖：代码执行 / 联网浏览搜索 / 读写文件 / 第三方 API应用场景：研究 / 报告撰写 / 市场分析 / 数据处理 ...

安装技能

复制下面的话术发给你的 Agent，它会通过 secure-skills 检索并安装该技能。

执行命令安装此 skill： npx secure-skills-cli add ai-product-launch-monitor

Metadata

name: ai-product-launch-monitor
description: One-command AI product launch monitoring pipeline. Use when the user wants to track, discover, or analyze new AI product launches, releases, or announcements. Runs four stages automatically - RSS feed monitoring, web search enrichment, page screenshots, and trend analysis/scoring. Outputs a markdown report and structured JSON. Triggers on phrases like monitor AI product launches, track AI releases, AI launch report, what new AI products launched, product hunt AI monitoring, AI news roundup.

AI Product Launch Monitor

End-to-end pipeline that collects AI product launches from RSS feeds, enriches them with web search, captures screenshots, and scores trends — all in one command.

Quick Start

python3 scripts/monitor.py --output ./output -v

This runs all four stages and produces output/report.md + output/launches.json.

Pipeline Stages

Stage	What it does
1. RSS monitoring	Fetches AI/tech RSS feeds, filters for launch signals, dedupes
2. Product search	Enriches each launch with web search results (Brave API or DDG fallback)
3. Screenshots	Headless Chromium screenshots of each product page via Playwright
4. Trend analysis	Categorizes, scores, and ranks launches; generates report

Usage

# Default run (3-day lookback, all stages)
python3 scripts/monitor.py --output ./output

# Custom lookback window
python3 scripts/monitor.py --days 7 --output ./weekly

# Use a config file
python3 scripts/monitor.py --config assets/default-config.json --output ./output

# Override feeds
python3 scripts/monitor.py --feeds https://example.com/feed.xml https://other.com/rss

# Skip screenshots (faster, no browser needed)
python3 scripts/monitor.py --no-screenshots --output ./quick

# Verbose mode
python3 scripts/monitor.py -v --output ./output

Configuration

Copy assets/default-config.json and customize:

{
  "feeds": ["https://..."],
  "query_terms": ["AI product launch"],
  "days": 3
}

Environment Variables

BRAVE_API_KEY — set to use Brave Search API (better results). Without it, falls back to DuckDuckGo HTML scraping.

Output

report.md — human-readable trend report with category breakdown, top launches, and full entry list
launches.json — structured data for downstream automation
screenshots/*.png — page screenshots (named by URL hash)

Dependencies

Python 3.10+
feedparser, requests, beautifulsoup4 (auto-installed)
playwright + Chromium (for screenshots; skip with --no-screenshots)

Install Playwright browsers:

python3 -m playwright install chromium

How Scoring Works

Each launch gets a trend score (0–100+):

+30 — strong launch keyword in title/summary
+5 per search result (max 25) — external corroboration
+10 — screenshot captured (page was reachable)
Recency bonus — newer launches score higher (up to +35)

Categories: LLM/Foundation Models, Image/Video Gen, Agent/Automation, Developer Tools, Enterprise/B2B, Consumer/App, Healthcare/Science, Other.

Agent Integration

When using this skill in an agent workflow:

Run the script with --output pointing to a temp or workspace directory
Read report.md for a summary to present to the user
Parse launches.json for structured data (e.g., filtering by category or score threshold)
Screenshots can be attached or referenced in responses