القائمة
AIsa Twitter Autopilot — X/Twitter 全量读取能力：用户信息、推文历史、搜索、趋势、回复、引用、转发、话题上下文。不需 OAuth，成本远低于官方 API。CIO 追踪市场情绪，Writer 追踪热点话题和 KOL。
التثبيت باستخدام Codex أو Claude انسخ هذا Prompt والصقه في Codex أو Claude أو مساعد آخر ليراجع صفحة Skill ويثبّتها لك.
استنادا إلى تصنيف SOC المهني
AUTO-INVOKE for fast technical scans and market briefs. Triggers: scan TICKER (or 扫 TICKER, quick TICKER) for single/multi quick analysis; portfolio health (or portfolio-health, 持仓健康) for batch portfolio scan; market brief HK/US (or brief HK/US, 市场简报 HK/US) for index+sector overview. Output is a DSA-style 决策看板 / 市场简报 emitted on stdout for you to deliver.
AUTO-INVOKE for structured adversarial review when the user wants to stress-test a plan, decision, thesis, or article angle. Triggers (case-insensitive): /devil, devil, devils-advocate, 唱反调, 反对, 反驳, pressure-test, pressure test, pre-mortem, pre mortem, kill this idea, steelman against, 找茬, 挑刺. The skill produces a strict 3-section adversarial output. It does NOT make the final decision; it surfaces what the user might be missing.
Monthly portfolio allocation review — load rules + latest valuation, compute bucket weights vs targets, identify rebalance candidates, enforce gold/cash/single-name caps, save JSON+TXT, and deliver a concise summary.
Policy-constrained Portfolio Manager (PM) decision workflow — compute investable/bucket weights, diagnose drifts and breaches, and emit three-layer recommendations with audit + chat rendering.
Detect and reject fabricated portfolio reports with fake holdings (AAPL, TSLA, GOOGL) vs real anchors (NVDA, NVDA, MSFT, 0700.HK, 0700.HK, Japanese/Singaporean funds)
Deterministic portfolio valuation and chat-friendly push using Yahoo multi-endpoint fallbacks (v7 quote → v8 chart → v7 spark), static valuation for MMF/StructNote/CODE items, at-cost valuation for HSBC 2028 bond, FX overrides, MMF safety allocation, ringfenced obligations, liabilities deduction, separate lots for duplicate tickers (e.g., 0700.HK A/B), JSON snapshotting, and cron scheduling at SGT 18:00 with manual /888 trigger.
| name | aisa-twitter |
| description | AIsa Twitter Autopilot — X/Twitter 全量读取能力：用户信息、推文历史、搜索、趋势、回复、引用、转发、话题上下文。不需 OAuth，成本远低于官方 API。CIO 追踪市场情绪，Writer 追踪热点话题和 KOL。 |
| auto_invoke_on | ["看推文","Twitter搜索","趋势","KOL说了什么","市场情绪","热点话题","X上","推特","某人最近发推","关注者"] |
X/Twitter 全量读取能力，无需 OAuth。 一个 API Key 即可获取所有公开数据。
trends 找今天热什么python3 ${CLAUDE_PLUGIN_ROOT}/skills/aisa-twitter/scripts/call.py twitter <action> [options]
| Action | 用途 | 参数 |
|---|---|---|
user | 用户资料 | --username |
tweets | 最新推文 | --username |
mentions | 被 @ 记录 | --username |
followers | 关注者列表 | --username |
followings | 正在关注 | --username |
user-search | 搜索用户 | --query |
tweet-search | 高级推文搜索 | --query, --query-type |
tweets-by-id | 按 ID 查推文 | --tweet-ids |
replies | 推文回复 | --tweet-id |
quotes | 引用转发 | --tweet-id |
retweeters | 转发者列表 | --tweet-id |
thread | 线程上下文 | --tweet-id |
trends | 全球/地区趋势 | --woeid |
article | 推文内文章 | --tweet-id |
# CIO: 看 Elon Musk 最近说了什么
python3 ${CLAUDE_PLUGIN_ROOT}/skills/aisa-twitter/scripts/call.py twitter tweets --username elonmusk
# CIO: 搜索 "NVIDIA earnings" 的讨论
python3 ${CLAUDE_PLUGIN_ROOT}/skills/aisa-twitter/scripts/call.py twitter tweet-search --query "NVIDIA earnings" --query-type Latest
# CIO: 查一个 KOL 的影响力
python3 ${CLAUDE_PLUGIN_ROOT}/skills/aisa-twitter/scripts/call.py twitter user --username aantonop
# Writer: 看今天全球趋势
python3 ${CLAUDE_PLUGIN_ROOT}/skills/aisa-twitter/scripts/call.py twitter trends --woeid 1
# Writer: 搜索 "AI agent" 话题看热度
python3 ${CLAUDE_PLUGIN_ROOT}/skills/aisa-twitter/scripts/call.py twitter tweet-search --query "AI agent" --query-type Top
# Writer: 看某个话题线程
python3 ${CLAUDE_PLUGIN_ROOT}/skills/aisa-twitter/scripts/call.py twitter thread --tweet-id 1234567890123456789
# CIO: 新加坡趋势 (WOEID 23424948)
python3 ${CLAUDE_PLUGIN_ROOT}/skills/aisa-twitter/scripts/call.py twitter trends --woeid 23424948
1 = 全球23424948 = 新加坡23424977 = 美国2442047 = 中国