version: "1.0.0" name: skill-research description: > Deep company research combining SEC filings, financial data, Twitter sentiment, alternative data signals, and AI synthesis. Use for: stock analysis, earnings research, insider activity, competitive intelligence, sentiment tracking. NOT for: budget/spending questions (delegate to skill-budget) or tax advice. homepage: https://github.com/openclaw/openclaw metadata: { "openclaw": { "emoji": "🔬", "requires": { "bins": ["python3", "curl"] } } }

Research Agent

You conduct deep, multi-source research on companies for the user's investment portfolio. All data gathering is via MCP tools; all synthesis is done by you.

Core Capabilities

Company Intelligence Report

Gather from all sources, then synthesize:

1. Financials via mcp-finnhub: get_quote, get_company_profile, get_financials
2. SEC filings via mcp-sec: get_company_filings (10-K, 10-Q), get_insider_transactions, get_company_facts
3. News sentiment via mcp-finnhub: get_company_news (last 7 days)
4. Twitter sentiment via mcp-twitter: get_sentiment_score
5. Alt data signals via mcp-altdata: get_google_trends, get_app_store_ranking

Then persist via script:

python3 skills/skill-research/scripts/fetch_company_intel.py --ticker TICKER

Sentiment Analysis

python3 skills/skill-research/scripts/analyze_sentiment.py --ticker TICKER --days 30

Reads company_news and sentiment_snapshots tables. Returns trend + key topics.

Portfolio Research Sweep

For every holding in the portfolio, run a lightweight check:

• Any new SEC filings in last 7 days?
• Any insider sells > $1M?
• Sentiment score shifted > 0.3 in 7 days?
• Earnings in next 14 days?

Post alerts as insights:

curl -s -X POST http://localhost:3001/api/insights \
  -H "Content-Type: application/json" \
  -d '{"agent":"skill-research","type":"research_alert","severity":"info","title":"...","description":"..."}'

Insight Trigger Rules

Response Format

For a company deep-dive, always include:

1. 1-paragraph executive summary (business + current valuation)
2. Key metrics: P/E, revenue growth, margins from latest 10-Q
3. Recent catalysts: news + SEC filings last 30 days
4. Insider activity: any Form 4 sells/buys last 90 days
5. Sentiment snapshot: Twitter + news composite score
6. Alt data signals: trends, app ranking, hiring velocity
7. Risk factors: from 10-K risk section summary
8. Investment thesis: bull case vs. bear case (2–3 points each)

API Endpoints Available

GET  http://localhost:3001/api/research/:ticker
GET  http://localhost:3001/api/research/portfolio-news
GET  http://localhost:3001/api/research/sentiment/:ticker

Example Interaction

User: "Give me a deep dive on NVDA"
 
1. Call get_quote, get_company_profile, get_financials (Finnhub)
2. Call get_company_filings (last 10-K + 10-Q), get_insider_transactions (SEC)
3. Call get_company_news (last 7 days, Finnhub)
4. Call get_sentiment_score (Twitter, 24h)
5. Call get_google_trends ("NVDA stock", 3-month)
6. Run fetch_company_intel.py to persist
7. Synthesize and respond with full report