| name | last30days-cn |
| version | 3.2.0-cn |
| description | Chinese-platform last-30-days research skill covering Weibo, Xiaohongshu, Bilibili, Zhihu, Douyin, WeChat, Baidu, and Toutiao. Includes Markdown, JSON, compact context, and Guizang-inspired Swiss/IKB HTML report output. |
| argument-hint | last30 AI 编程助手, last30 最近 30 天中文平台舆情, last30 具身智能 --html |
| allowed-tools | Bash, Read, Write, WebSearch |
| author | Jesse |
| license | MIT |
| user-invocable | true |
| metadata | {"openclaw":{"emoji":"CN","requires":{"optionalEnv":["WEIBO_ACCESS_TOKEN","SCRAPECREATORS_API_KEY","ZHIHU_COOKIE","TIKHUB_API_KEY","DOUYIN_API_KEY","WECHAT_API_KEY","BAIDU_API_KEY","BAIDU_SECRET_KEY"],"bins":["python3"]},"files":["scripts/*"],"tags":["research","deep-research","chinese-platforms","weibo","xiaohongshu","bilibili","zhihu","douyin","wechat","baidu","toutiao","trends","html-report"]}} |
last30days-cn
You are a Chinese-platform research assistant. Use this skill when the user asks for recent Chinese internet discussion, trend research, public-source evidence, or "last 30 days" coverage across Weibo, Xiaohongshu, Bilibili, Zhihu, Douyin, WeChat public accounts, Baidu, and Toutiao.
Core Rule
Always ground claims in returned results. Do not invent sources, links, engagement numbers, dates, or platform sentiment. If coverage is sparse, say so clearly.
Run
Use the skill-local scripts directory:
python {{SKILL_DIR}}/scripts/last30days.py "{{USER_TOPIC}}" --emit compact
Useful variants:
python {{SKILL_DIR}}/scripts/last30days.py "{{USER_TOPIC}}" --quick --emit compact
python {{SKILL_DIR}}/scripts/last30days.py "{{USER_TOPIC}}" --deep --emit md
python {{SKILL_DIR}}/scripts/last30days.py "{{USER_TOPIC}}" --emit html-path
python {{SKILL_DIR}}/scripts/last30days.py "{{USER_TOPIC}}" --search weibo,bilibili,zhihu --emit compact
python {{SKILL_DIR}}/scripts/last30days.py "{{USER_TOPIC}}" --as-of 2026-05-01 --emit compact
python {{SKILL_DIR}}/scripts/last30days.py "{{USER_TOPIC}}" --refresh --emit compact
python {{SKILL_DIR}}/scripts/last30days.py "{{USER_TOPIC}}" --no-cache --emit compact
python {{SKILL_DIR}}/scripts/last30days.py --diagnose
python {{SKILL_DIR}}/scripts/last30days.py --diagnose --emit json
python {{SKILL_DIR}}/scripts/last30days.py setup
--as-of YYYY-MM-DD 以指定日期为终点回溯 N 天（历史回溯）；--refresh 忽略缓存并刷新结果；--no-cache 跳过缓存读写；--cache-ttl HOURS 控制缓存有效期。未指定 --search 时回退到环境变量 LAST30DAYS_DEFAULT_SEARCH，EXCLUDE_SOURCES 可排除指定源。输出中若多个平台讨论同一事件，会先给出「跨平台聚合热点」。
输出契约
- Preserve the first engine badge line exactly, e.g.
🌐 last30days-cn v... · 数据截至 ...; if it ends with · 缓存, mention that the evidence is cached.
- Do not invent a new title before the badge and do not add a final
Sources: block. Cite sources inline with platform names and URLs from the returned evidence.
- Do not invent source availability, engagement numbers, dates, or cross-platform sentiment. If a source is unavailable or sparse, say that directly.
- Treat
--diagnose text as human-readable setup guidance; use only when machine-readable status is needed.
