Token导航 LogoToken导航

Agent Skill · 研究检索

earnings-analyst(收益分析师)

earnings-analyst 用于查找、检索和筛选相关信息,适合在 OpenClaw 中需要根据关键词、任务场景或来源线索快速定位候选结果时使用。可结合来源仓库、安装命令和原始 README 继续核验具体用法。安装前建议确认权限范围、维护状态,以及是否会触发联网、命令执行或文件读写。

earnings-analyst 是研究检索类 Agent Skill,可用宿主为 OpenClaw,通过ClawHub获取,权限为接触敏感数据;许可证为 MIT-0,第三方扫描已通过,按安装量在研究检索类的 73,675 个 Skill 里排第 28,112。

总安装 3,272周安装 135GitHub Stars 公开资料未说明下载 1,069核验 2026-05-01

安装说明

本站只整理中文说明,不托管安装包,也不代用户安装。
GitHub
许可证
MIT-0
版本
1.0.1

安装方式

通过对话安装

复制提示词发给支持本地命令或 Skills 的 AI 助手,先确认命令和权限,再让它执行。

请帮我安装这个 Agent Skill:earnings-analyst(收益分析师)
来源仓库:https://github.com/finskills/earnings-analyst
安装命令:
openclaw skills install earnings-analyst
安装前请先检查当前环境是否支持对应 CLI,并向我确认将要执行的命令、安装目录、联网范围和文件读写权限;确认后再执行。

命令行安装

复制命令到本机终端执行。该命令会通过 OpenClaw 从第三方来源获取 Skill;本站只展示命令,不托管安装包,也不自动执行。

ClawHubOpenClaw
openclaw skills install earnings-analyst

这个 Skill 是做什么的

研究检索类 Skill 主要解决「找资料、核对事实、把来源整理清楚」的问题,通常会让助手先检索再总结。

使用 Finskills API 研究即将发生的盈利事件、分析历史超出/错过模式并估计盈利后价格反应。

上手步骤

4 步
  1. 1

    确认自己的宿主工具

    公开资料标注支持 OpenClaw;先确认自己用的是其中之一,再按对应工具的 Skills 目录放置。

  2. 2

    拿到安装命令

    可以直接复制的命令是 openclaw skills install earnings-analyst;命令里的占位符换成自己的路径或密钥再执行。

  3. 3

    安装后重启宿主

    命令执行完要完全退出宿主工具再打开,让新装的 Skill 被重新扫描到,否则列表里可能看不到。

  4. 4

    按最小权限试用

    它需要接触敏感数据,先在测试目录或测试账号里跑,确认没问题再放到正式项目。

常见问题

6 条

earnings-analyst 怎么安装?

在终端执行 openclaw skills install earnings-analyst。装完完全退出宿主工具再打开,让它重新扫描本地 Skill。

earnings-analyst 支持哪些 AI 工具?

公开资料标注支持 OpenClaw。其他工具只要能读取本地 Skill 目录,一般也能手动放进去,但要自己确认触发方式是否一致。

earnings-analyst 需要什么权限?

权限级别是接触敏感数据。该 Skill 可能接触密钥、Token、环境变量或敏感配置,应进入高风险复核队列,默认不自动发布。

earnings-analyst 是免费的吗?

来源标注的许可证是 MIT-0。本站不代收任何费用,也不托管安装包;能否商用、要不要署名,以许可证原文为准。

earnings-analyst 用的人多吗?

公开数据是累计安装 3,272 次,近一周安装 135 次,下载 1,069 次。这些数字来自第三方目录统计,只能当作热度参考,不代表质量或安全性。

earnings-analyst 安全吗?

第三方扫描结果为通过,但这只覆盖已知的静态检查项,不能替代自己读一遍源码和安装命令。

值得选的地方和要先想清楚的地方

值得选的地方

  • 专注 OpenClaw 一种宿主,触发方式和使用习惯不用来回切换。
  • 许可证明确为 MIT-0,商用和分发边界好判断。
  • 第三方扫描已通过,常见的高风险行为没有命中。

先想清楚的地方

  • 需要接触敏感数据,装到常用环境前要先评估影响面。
  • 第三方目录整理,版本更新和行为细节以来源仓库为准。

适不适合你

更适合

  • 已经在用 OpenClaw,想直接扩展它能力的人。
  • 需要处理研究检索类任务、又不想每次都手写提示词的人。
  • 需要许可证清楚、并且有第三方扫描结果的团队项目。

不太适合

  • 环境里有大量密钥、凭证,不方便给第三方 Skill 读取的人。
  • 需要厂商级技术支持和 SLA 的生产系统。

研究检索类 Skill 对比

6 个同类
Skill总安装GitHub 星权限许可证扫描
find-skills

寻找技能 · Codex、Claude

31,199,81316,486操作浏览器MIT有提醒
self-improving-agent

自我改进 Agent · OpenClaw

16,464,0023,396接触敏感数据MIT-0通过
soultrace

灵魂追踪 · Codex、Claude

7,588,94412需要联网未明确有提醒
self-improving

自我完善 · OpenClaw

6,829,2841,046需要联网MIT-0通过
microsoft-foundry

微软代工厂 · Codex、Claude

6,614,144764调用外部服务未明确有提醒
earnings-analyst

收益分析师 · 本页

3,272—接触敏感数据MIT-0通过

按安装量取同分类前几名;数字来自第三方目录统计,只作热度参考,不代表质量结论。

SKILL.md 原文

name
Earnings Analyst
version
1.0.2
description
Research upcoming earnings events, analyze historical beat/miss patterns, and estimate post-earnings price reactions using the Finskills API.
author
finskills
metadata
openclaw
requires
env
primaryEnv
FINSKILLS_API_KEY
homepage
https://github.com/finskills/earnings-analyst

Earnings Analyst

Track upcoming earnings events, analyze EPS beat/miss history, assess options- implied earnings move expectations, and monitor analyst estimate revisions — all powered by the Finskills API earnings calendar and company earnings endpoints.


Setup

API Key required — Register at https://finskills.net to get your free key. Header: X-API-Key: <your_api_key>

Get your API key: Register at https://finskills.net — free tier available, Pro plan unlocks real-time quotes, history, and financials.

When to Activate This Skill

Activate when the user:

  • Asks when a specific company reports earnings
  • Wants to know historical earnings beat/miss rate for a stock
  • Asks about analyst EPS/revenue estimates for an upcoming quarter
  • Wants to understand the "earnings move" priced into options
  • Asks which major companies are reporting this week
  • Wants pre-earnings research before a binary event

Use Cases

Mode A — Market Earnings Calendar

"What major companies are reporting earnings this week?"

Mode B — Per-Stock Earnings Deep Dive

"Analyze NVDA's upcoming earnings — what should I expect?"

Mode C — Pre-Earnings Trade Setup

"Set up a pre-earnings analysis for AAPL with options context"


Data Retrieval — Finskills API Calls

Mode A — Earnings Calendar

GET https://finskills.net/v1/free/market/earnings-calendar

(Optional query params: from=YYYY-MM-DD&to=YYYY-MM-DD) Extract: company name, ticker, report date, timing (before market / after market), EPS estimate

Filter and group by day. Sort by market cap or analyst attention.

Mode B — Per-Stock Earnings Analysis

Earnings History & Next Quarter Estimate:

GET https://finskills.net/v1/stocks/earnings/{SYMBOL}

Extract:

  • Last 4–8 quarters: date, epsActual, epsEstimate, epsSurprise, epsSurprisePercent
  • Last 4–8 quarters: revenueActual, revenueEstimate, revenueSurprise
  • Next quarter: epsEstimate, revenueEstimate
  • Next report date, timing (AMC/BMO)

Analyst Estimates (revision trend):

GET https://finskills.net/v1/free/stocks/estimates/{SYMBOL}

Extract: current quarter EPS estimate, next quarter, current year, next year consensus Note upward vs. downward revision trend (compare to 30-day-ago estimates if available)

Latest News (pre-earnings catalyst check):

GET https://finskills.net/v1/news/by-symbol/{SYMBOL}

Extract: recent headlines, sentiment signals, any pre-announcements or guidance updates

Options Chain (for implied move):

GET https://finskills.net/v1/stocks/options/{SYMBOL}

Extract near-term ATM straddle price to calculate implied earnings move.


Analysis Workflow

Step 1 — Earnings Calendar View (Mode A)

Group events by day (Mon–Fri this week):

  • Show pre-market (BMO) and after-close (AMC) separately
  • Flag mega-caps (market cap > $100B) with ★
  • Include consensus EPS estimate for context
  • Highlight sector clusters (earnings tend to move entire sectors)

Step 2 — Earnings History Analysis (Mode B)

Build a beat/miss scorecard:

QuarterEPS EstEPS ActualSurpriseRev EstRev ActualRev Surprise
Q1 2025$X.XX$X.XX+X%$XB$XB+X%
...

Compute:

  • EPS Beat Rate: % of quarters beating EPS estimate
  • Avg EPS Surprise: Mean % beat magnitude (positive = bullish quality)
  • Revenue Beat Rate: % of quarters beating revenue estimate
  • Consistency Score: 5/5 beats vs 3/5 vs 2/5 — flag inconsistency
  • Trend: Is beat magnitude growing or shrinking? (quality signal)

Step 3 — Estimate Revision Momentum

Classify revision trend:

  • Positive momentum: Estimates revised UP in last 30–90 days → analyst conviction rising
  • Negative momentum: Estimates revised DOWN → potential guidance cut risk
  • Stable: No significant revisions

This is a leading indicator — stocks with positive estimate revisions tend to outperform.

Step 4 — Implied Earnings Move (if options data available)

Calculate using ATM straddle at nearest expiration AFTER earnings date:

ATM Straddle Price = ATM Call Mid + ATM Put Mid
Implied Move %     = Straddle Price / Current Stock Price × 100
Expected Range     = [Current Price × (1 − implied_move%), Current Price × (1 + implied_move%)]

Compare to historical earnings moves (from earnings history — abs value of price change on earnings day):

  • If implied move > average historical move: options are pricing in extra uncertainty → consider neutral strategies
  • If implied move < average historical move: options may be cheap for directional play

Step 5 — Pre-Earnings Assessment

Summarize the opportunity:

Bull Case (if expecting beat):

  • Revenue acceleration + margin expansion signals?
  • Positive estimate revisions?
  • Strong sector tailwinds?

Bear Case (if expecting miss or disappointment):

  • Slowing beat magnitude trend?
  • Recent negative estimate revisions?
  • Macro headwinds for the sector?

Key Watch Items:

  • Management guidance language (forward-looking statements)
  • Segment breakdowns to watch (e.g., Cloud for MSFT, iPhone for AAPL)
  • Margin trajectory (gross margin, operating margin vs estimates)

Output Format — Mode A (Calendar)

📅 EARNINGS CALENDAR  —  Week of {DATE}

MONDAY {Date}
  ⭐ {CompanyName} ({TICKER}) — AMC  |  EPS Est: ${est}
  {CompanyName} ({TICKER}) — BMO    |  EPS Est: ${est}

TUESDAY {Date}
  ⭐ {CompanyName} ({TICKER}) — BMO  |  EPS Est: ${est}
  ...

[⚠️ Sector note: {sector} reports in concentration — expect spillover moves]

Output Format — Mode B (Per-Stock Deep Dive)

╔══════════════════════════════════════════════════════╗
║    EARNINGS ANALYSIS — {TICKER}  ({DATE})           ║
╚══════════════════════════════════════════════════════╝

📅 NEXT EARNINGS
  Expected Date: {date}  |  Timing: {BMO/AMC}
  EPS Estimate:  ${eps}  |  Revenue Estimate: ${rev}B

📊 EARNINGS TRACK RECORD (Last {N} Quarters)
  EPS Beat Rate:     {%} ({n}/{total})
  Avg EPS Surprise:  +{%}
  Rev Beat Rate:     {%} ({n}/{total})
  Consistency:       {All beats / Mostly beats / Mixed}

  Quarter   EPS Est  Actual  EPS Surp  Rev Est   Actual   Rev Surp
  Q4 2024   $X.XX    $X.XX   +X.X%     $XB       $XB      +X.X%
  Q3 2024   ...

📈 ESTIMATE REVISION TREND
  Current FY EPS Estimate:  ${est}  ({+/-}% from 90 days ago)
  Revision Trend:           {Positive / Stable / Negative Momentum}
  Implications:             {one-line interpretation}

📐 IMPLIED EARNINGS MOVE (Options)
  ATM Straddle Price: ${price}  →  Implied Move: ±{%}
  Expected Range:     ${low} — ${high}
  Historical Avg Move: ±{%}
  Options Assessment: {Cheap/Rich/Fair relative to history}

📰 PRE-EARNINGS SIGNALS
  Recent News Sentiment: {Positive/Neutral/Negative}
  Key Headlines:
    • {headline 1}
    • {headline 2}

⚠️ KEY WATCH ITEMS FOR THIS EARNINGS
  1. {metric/segment to watch}
  2. {metric/segment to watch}
  3. {guidance language to watch}

🎯 EARNINGS SETUP SUMMARY
  Bull Case:  {2 sentences}
  Bear Case:  {2 sentences}
  Strategy:   {Directional bet / Neutral straddle / Avoid — with reasoning}

Limitations

  • Earnings dates can shift by 1–2 weeks; always verify directly with the company's IR page.
  • Implied move is based on options chain snapshot; liquidity affects pricing accuracy.
  • EPS surprise history may not account for non-GAAP vs. GAAP differences.

平台分布

OpenClaw

72.93%
按下载量换算780

安全审计

VirusTotal

通过

ClawScan

通过

Static analysis

通过

权限和风险

接触敏感数据

该 Skill 可能接触密钥、Token、环境变量或敏感配置,应进入高风险复核队列,默认不自动发布。

安装前确认

本站仅展示第三方公开信息,不托管安装包,不提供自动安装或运行环境。安装前应自行审查源码、依赖和命令行为。目前只有一个公开来源,建议同时核对源仓库。

继续浏览同类 Skills