More Real-World Scenarios: Financial Data Analysis Assistant

Use case: You need to watch market movements, read research reports, and track news every day, but the volume of information is overwhelming — easy to end up "reading a lot without any input for decisions." This guide corresponds to the README scenario "Financial Data Analysis."

This is not investment advice. It's about building a "collect → filter → summarize → alert" research pipeline where every conclusion has a source and a timestamp.

1. What This Guide Helps You Do

• Automatically collect market data, news, and announcements and group them into comparable themes
• Output a daily digest with sources and timestamps for easy review
• Automatically push alerts on abnormal movements, flagging "trigger condition + related assets"
• Persist daily reports to Feishu for easy daily reference

2. Copy This Prompt to Claw First

Please help me build a "Financial Data Analysis Assistant":
1) The tracked asset pool is: ________ (example: NVDA, TSLA, 3 new energy companies)
2) Collect market data + news + major announcements daily, and output one structured daily report: Market Overview, Key Assets, Key Events, Risk Warnings, Tomorrow's Watch List
3) Immediately push an alert when price movement, volume, or announcement keywords exceed a threshold; conclusions must include source links + collection time
4) All output in English; append "For research assistance only, does not constitute investment advice" at the end

3. Which Skills You Need

A quick look at what each skill does:

• skill-vetter Link: https://llmbase.ai/openclaw/skill-vetter/ Purpose: Security check before installation.
• tavily-search Link: https://termo.ai/skills/liang-tavily-search Purpose: Fetch news, announcements, and external information.
• summarize Link: https://termo.ai/skills/summarize Purpose: Compress research reports and news digests.
• feishu-send-message Link: https://playbooks.com/skills/openclaw/skills/feishu-send-message Purpose: Push daily reports and abnormal alerts.

Install with:

clawhub install skill-vetter
clawhub install tavily-search
clawhub install summarize
clawhub install feishu-send-message

For market data, you may find alpha-vantage-type skills, but their slugs are still changing. It's recommended to write a "quote fetch skill" or connect directly to your own API; do not treat unconfirmed slugs as stable public skills.

4. What You'll See Once It's Running

[Market Overview]
Nasdaq up 1.8%, semiconductor sector with elevated volume, data filed under "Chips + AI" theme

[Key Assets]
NVDA +4.2% (high volume, AI inference chip logic); TSLA -2.4% (regulatory keyword triggered alert)

[Risk Warnings]
TSLA regulatory news still developing; recommend close monitoring of volume and announcement keywords

[Tomorrow's Watch List]
Continue monitoring NVDA analyst day progress + watch for new regulatory keywords

All of the above includes source links and collection timestamps, so you can paste them directly into your research log.

5. How to Set It Up Step by Step

1. Start by selecting 10–20 core assets/themes; set price change and volume thresholds for each
2. Define the daily report template (Market Overview, Key Assets, Key Events, Risk Warnings, Tomorrow's Watch List)
3. Use tavily-search for news and announcement retrieval; use summarize for research report compression
4. Set up anomaly detection rules (e.g., intraday movement exceeding 5%, volume doubling, or banned keyword appearances)
5. Attach source links + collection time to every conclusion, and push the daily digest or alert via feishu-send-message

6. If No Existing Skill Fits, Have Claw Build One

If you can't find a stable market data skill, don't worry — just send Claw this message:

Please help me generate a minimal viable market data fetch skill. The first version only needs to do 3 things: pull prices for core assets, check whether thresholds are triggered, and output a daily report draft with sources and timestamps.

Let it sketch out the first version's approach, then consider building it into this skeleton:

market-watch/
├── SKILL.md
└── scripts/
    └── quote.py

SKILL.md describes that the skill is responsible for fetching market data, evaluating thresholds, and generating summaries. The first version of scripts/quote.py does three things only: 1) fetch prices for core assets; 2) check whether thresholds are triggered; 3) output a daily report draft with sources and timestamps.

7. Further Optimization

• Deduplicate and merge results from multiple data sources to avoid pushing the same event twice
• Add a "theme overview" view that bundles related assets and supports splitting by sector/strategy
• Include an "action recommendation" column in alerts, such as "needs manual review / keep watching / position size warning"

8. Frequently Asked Questions

Q1: Values differ across data sources. What do I do? A: Define a "primary data source"; use others only for cross-validation. Label the "data source" field in the summary.

Q2: Too many alerts to keep up with. What do I do? A: Add a cooldown period, tier alerts by priority, or only alert when the anomaly score exceeds 80.

Q3: Summaries are too generic and hard to act on. What do I do? A: Force the template to include a "tomorrow's watch points" + "trigger condition" section — conclusions are only actionable if they tell you what to watch for.