SKILL.md
AI News Digest
Workflow (required)
强制要求:在生成 AI 新闻汇总/简报前,必须先运行脚本获取最新数据。不要凭记忆或直接编写新闻摘要。若脚本失败,先重试一次;仍失败再使用 web.run 作为兜底,并在结果中标注“数据来源与时间窗口”。
- 必须抓取最新新闻
默认抓取过去 24 小时;如果用户指定“本周”“过去 72 小时”“今天”等范围,调整 --since。Use a task-local output path such as ./ai-news.json, ./ai-news.md, or a file under a temporary working directory. From the skill directory, run:
python3 scripts/fetch_ai_news.py --since 24h --limit 0 --max-per-source 0 --format json --output ./ai-news.json
Or generate Markdown directly (mandatory alternative):
python3 scripts/fetch_ai_news.py --since 24h --limit 0 --max-per-source 0 --format md --output ./ai-news.md
1b) 需要时补充 X + 非 RSS 站点
- Use
web.run.searchquery with references/xwatchlist.json and references/nonrsssources.json.
- Keep only items within the same time window (e.g. past 72 hours), and prefer links to the canonical announcement/blog/paper.
1c) 需要时补充 GitHub “热门上榜项目” + 社区热度/反馈
Run:
python3 scripts/fetch_github_ai_trending.py --since daily --limit 0 --format md --output ./github-ai.md
Notes:
- This uses GitHub Trending (HTML) for the “up榜热门” list, then enriches repos via GitHub API for heat/feedback signals.
- Set
GITHUBTOKEN (or GHTOKEN) to avoid low rate limits.
- Feedback signals include: open PRs, open/closed issues in the past N days, “good first issue/help wanted”, and top discussed issues.
- If you only need “hot list”, run faster with
--no-feedback (and/or --no-profile).
- 生成中文汇总(必须)
- Output in Chinese unless the user asked for English.
- Always include specific dates (e.g. “2026-02-04”) for “today / latest / yesterday”.
- For each item: 发生了什么 + 为什么重要 + link(必要时 2 links).
- If items conflict across sources, mention uncertainty and cite multiple links.
- End with a Chinese wrap-up section: “趋势与建议” (3–7 bullets). For 24h digests, title it “24小时趋势与建议”.
- If the user wants only certain outlets/topics
- Edit
references/sources.json (add/remove feeds, or toggle "enabled": true/false), then re-run the script.
- Use filters when you only need a subset:
- Keywords: --keywords agent,benchmark,open-source - Source tags: --include-tags vendor,research / --exclude-tags community
Output templates
Short digest (default)
- Title:
AI News Digest — <DATE RANGE>
- Sections (optional): Product/Company, Research, Policy/Safety, Market/Business
- 8–15 bullets total, each with 1 link (2 links if needed)
- If there are many items within 24h, cluster by theme and summarize each cluster; do not drop items silently.
Long digest
- Add 1–2 sentence summaries per item, grouped by section
- Include a “Notable trends” section at the end (3–5 bullets)
Notes
- Prefer RSS/Atom feeds over scraping HTML for reliability.
- If a target site has no public feed, use
web.run (search + open) as a fallback and still include dated links.
- For non-RSS “known sites”, use
references/nonrsssources.json query templates with web.run.search_query.
- For X (Twitter) news, prefer
web.run search (no scraping): use references/x_watchlist.json handles + templates, and set a clear time window (e.g. past 72 hours).
- For GitHub trending, prefer
scripts/fetchgithubai_trending.py (no scraping beyond the Trending listing page).
- If a feed is down, retry once, then skip and report which sources failed.
- Do not claim anything is “latest” without a date/time window (e.g. “past 72 hours”).
X (Twitter) quick recipe (web.run)
Use web.run.search_query with recency (days) and queries like:
site:x.com/OpenAI (announce OR released OR launch OR model OR paper)
site:x.com (OpenAI OR AnthropicAI OR GoogleDeepMind OR MistralAI OR xai) (released OR launch OR model)
Then: extract only posts that link to an official announcement/blog/paper, and include both the X link and the canonical source link when possible.