Use when generating a daily 24h AI / Agent / AIGC top-news briefing, publishing it as a Feishu/Lark native document, validating it, and optionally archiving it to Bitable.
Instalar com Codex ou Claude Copie este prompt, cole no Codex, Claude ou outro assistente e deixe que ele revise a página da skill e instale para você.
Um comando direto ignora o prompt de revisão. Verifique a origem antes de executá-lo.
Use when generating a daily 24h AI / Agent / AIGC top-news briefing, publishing it as a Feishu/Lark native document, validating it, and optionally archiving it to Bitable.
This skill runs a daily AI / Agent / AIGC morning briefing workflow.
It collects candidates from news aggregators and source-of-truth pages, filters for high-signal items, writes a Chinese 24h report, publishes it as a Feishu/Lark native document, fetches it back for validation, and optionally archives the result to Feishu Bitable.
Core rule: truth first, no quota-filling. If there are only a few important items, keep the report short.
When to Use
Use this skill when the task asks for any of these:
daily AI / Agent / AIGC top news
过去24小时 AI / Agent / AIGC 早报
cron-generated AI morning briefing
Feishu/Lark native document delivery
AI news archive into Feishu Bitable
recurring report that must include Agent, AIGC image/video, GitHub Trending, and a mandatory project check
Do not use this for:
broad weekly reports with a different time window
pure finance/news briefings unrelated to AI / Agent / AIGC
one-off research notes that do not need Feishu publishing or Bitable archival
Required Inputs
A cron prompt should be self-contained and include:
Task: Generate the past-24h AI / Agent / AIGC Top News briefing.
Timezone: Asia/Shanghai.
Delivery: create Feishu/Lark native doc, fetch-back validate, optionally archive to Feishu Bitable, send result to origin chat.
Archive base_token: <FEISHU_BITABLE_BASE_TOKEN>
Archive table_id: <FEISHU_BITABLE_TABLE_ID>
Bitable URL: https://www.feishu.cn/base/<FEISHU_BITABLE_BASE_TOKEN>?table=<FEISHU_BITABLE_TABLE_ID>
Required project check: <owner>/<repo>
If no Feishu folder token is supplied, create the document in the default Feishu location. Do not block.
Output Contract
Final answer must include:
已完成。
- 文档标题：...
- doc_url：...
- bitable_url：... # if archival is enabled
- record_id：... # if archival is enabled
- 摘要：
- ...
- ...
- ...
If archival fails but doc publishing succeeds, say so explicitly and include the doc URL plus a short error summary.
Phase 1 — Preflight
Always check live time and Feishu/Lark auth. Do not infer time mentally.
date -u '+UTC=%Y-%m-%d %H:%M:%S' && TZ=
lark-cli auth status
lark-cli auth scopes
'Asia/Shanghai'
date
'+CST=%Y-%m-%d %H:%M:%S %Z'
Minimum expected capabilities:
document create/import capability
document fetch/read capability
Bitable record read/write capability, if archival is enabled
If scope output is noisy, continue if the actual create/fetch/API calls work.
Phase 2 — Source Collection
Prefer a local news aggregator as the first pass. It gives candidates, not final truth.
Example commands, adapt paths to your local setup:
Also perform targeted checks against official/source-of-truth pages. At minimum check:
OpenAI models / image / video updates
Google Gemini / Imagen / Veo updates
Anthropic / Claude / coding-agent updates
Runway
Pika
Kling / 可灵
ByteDance / 即梦 / Seedance
Midjourney
Ideogram
Adobe Firefly
Stability AI
GitHub Trending Today for AI / Agent / AIGC / developer-tool / infra projects
Use web search/extract for current facts. If a page blocks extraction, combine search-result snippets, official docs/API pages, and one reputable secondary source.
Phase 3 — Mandatory Project Check
Always check the configured project separately. External popularity does not decide whether it appears.
If there is no material update, still mention that the check was performed in source notes or omit the section only if truly empty. Never skip the check.
Phase 4 — Selection Rules
Use this priority order:
official release / changelog / docs / API evidence
GitHub release / merged PR / commit evidence
reputable media report
HN / social discussion as secondary signal
GitHub Trending as trend signal only
Hard rules:
Do not write rumors as releases.
Do not convert GitHub Trending Today into “past 24h launched”. Say “今日趋势信号”.
HN Algolia is noisy. Treat it as discovery, not proof.
Verify important HN links using original objectID / hn_url; do not guess item IDs.
If official naming differs from media naming, state the official name clearly.
AIGC image/video must be checked daily, even if no item survives final selection.
Chinese only, unless product/repo/model names need English.
Every ## heading must have a blank line before it.
Every retained news item should explain: what happened / why it matters / practical workflow impact.
Avoid hype words and generic filler.
Links must point to the actual source when possible.
Phase 6 — Publish Feishu/Lark Native Doc
Prefer writing the report to a local temporary Markdown file, then pass the file content via Python/subprocess or safe argv. Avoid shell-embedded huge markdown.
Minimal create command:
lark-cli docs +create \
--as user \
--title 'AI / Agent / AIGC Top News 24h｜YYYY-MM-DD 08:00' \
--markdown '<content>'
