用 Codex 或 Claude 帮你安装 复制这段 Prompt,粘贴到 Codex、Claude 或其他助手里,让它检查 Skill 页面并帮你完成安装。
直接命令不会经过审查 Prompt;运行前请先检查来源。
npx skills add https://github.com/ginlix-ai/LangAlpha --skill earnings-preview命令会保持在同一行。复制前请横向滚动并检查完整内容。
想先保存到本地?可下载 SkillsMP 当前能够提供的文件。
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| name | earnings-preview |
| description | Pre-earnings analysis: consensus estimates, key metrics to watch, bull/base/bear scenarios |
| license | Derived from anthropics/financial-services-plugins (Apache-2.0). Modified for langalpha. |
description: Build pre-earnings analysis with estimate models, scenario frameworks, and key metrics to watch. Use before a company reports quarterly earnings to prepare positioning notes, set up bull/bear scenarios, and identify what will move the stock. Triggers on "earnings preview", "what to watch for [company] earnings", "pre-earnings", "earnings setup", or "preview Q[X] for [company]".
get_company_overview tool — includes earnings history (actual vs estimate), analyst consensus, price targets, rating distributionget_daily_prices tool for recent price history and to identify the earnings date windowget_sec_filing tool — auto-attaches earnings call transcript for 10-K/10-Q filings (review prior quarter for guidance or commentary)WebSearch / WebFetch for recent news and sentiment heading into earningsBuild a "what to watch" framework specific to the company:
Financial Metrics:
Operational Metrics (sector-specific):
Build 3 scenarios with stock price implications:
| Scenario | Revenue | EPS | Key Driver | Stock Reaction |
|---|---|---|---|---|
| Bull | ||||
| Base | ||||
| Bear |
For each scenario:
Identify the 3-5 things that will determine the stock's reaction:
Save all deliverables to $WORK_DIR/work/{task}/. One-page earnings preview with:
get_company_overview for historical actual vs estimate data$WORK_DIR/work/{task}/Search X (Twitter) posts, pull user profiles, fetch specific tweets, and read reply threads for sentiment, news, and event research. Triggers on 'X', 'Twitter', 'tweets about', 'sentiment on', 'what are people saying about', 'historical tweets', or any request to read public X content.
Web scraping: scrape_page / scrape_pages MCP tools for fetching pages as markdown, HTML, or text (fast HTTP, browser rendering, anti-bot stealth), plus the direct Scrapling Python API for selectors, sessions, and spiders
Orchestrate parallel subagent pipelines from a JavaScript workflow script — fan out work across many items (tickers, filings, findings) then synthesize, or run a saved workflow by name. Unlocks the RunWorkflow tool.
基于 SOC 职业分类