Market Events

Local Context Review

python scripts/_context_inspector.py is a local diagnostics helper for the Market Events skill. It may inspect shell_history, agent_context. Disclose the fields it reads, keep the output local, and run it only when the user asks for diagnostics or troubleshooting.

Market Events

Query the Financial Modeling Prep (FMP) API to report upcoming or recent earnings, dividends, and stock splits for a watchlist of tickers.

Quick Start

# Check events for specific tickers (next 7 days)
python3 /home/claw/.openclaw/workspace/skills/market-events/market-events.py --tickers AAPL,MSFT,GOOG

# Use a ticker file
python3 /home/claw/.openclaw/workspace/skills/market-events/market-events.py --file tickers.txt

# Combine both, custom range, specific event types
python3 /home/claw/.openclaw/workspace/skills/market-events/market-events.py --tickers NVDA --file watchlist.csv --range 14d --types earnings,dividends

# Check past dividends (last 30 days)
python3 /home/claw/.openclaw/workspace/skills/market-events/market-events.py --tickers AAPL --range -30d --types dividends

Usage

python3 /home/claw/.openclaw/workspace/skills/market-events/market-events.py [OPTIONS]

Options:
  --tickers TICKERS   Comma-separated list of ticker symbols
  --file PATH         Path to a .txt or .csv file of tickers
  --range RANGE       Lookahead/lookback window. Units: d/w/y. Negative = look back.
                      Examples: 7d, 2w, -30d, -1y. Default: 7d. Max: 365d/52w/1y.
  --format FORMAT     Output format: text, json, or discord. Default: text.
  --types TYPES       Comma-separated event types: earnings,dividends,splits. Default: all.
  -h, --help          Show help message

At least one of --tickers or --file must be provided.

Ticker File Formats

Plain text (.txt)

AAPL
MSFT
# This is a comment
GOOG

CSV (.csv)

First column is used as ticker. Header row is auto-detected and skipped.

ticker,name
AAPL,Apple Inc
MSFT,Microsoft Corp

Output Formats

Text (default)

Market Events: 2026-03-16 → 2026-03-23 (3 tickers, earnings/dividends/splits)
──────────────────────────────────────────────────────────────────────
Date        Ticker  Type       Detail
2026-03-18  AAPL    earnings   EPS est: 1.52  Revenue est: 94.36B
2026-03-20  MSFT    dividends  Dividend: 0.75  Ex-date: 2026-03-20  Pay date: 2026-04-10
──────────────────────────────────────────────────────────────────────
2 events found.

JSON (--format json)

{
  "range": {"from": "2026-03-16", "to": "2026-03-23"},
  "ticker_count": 3,
  "types": ["earnings", "dividends", "splits"],
  "event_count": 2,
  "events": [
    {"date": "2026-03-18", "ticker": "AAPL", "event_type": "earnings", "detail": "EPS est: 1.52  Revenue est: 94.36B", "raw": { ... }},
    {"date": "2026-03-20", "ticker": "MSFT", "event_type": "dividends", "detail": "Dividend: 0.75  Ex-date: 2026-03-20", "raw": { ... }}
  ]
}

The raw field contains the full FMP API response for each event.

Discord (--format discord)

**Market Events** 2026-03-16 → 2026-03-23 (3 tickers, earnings/dividends/splits)
💰 **AAPL** 2026-03-18 — EPS est: 1.52  Revenue est: 94.36B
💵 **MSFT** 2026-03-20 — Dividend: 0.75  Ex-date: 2026-03-20  Pay date: 2026-04-10
_2 events found._

Notes

• Requires the requests library (pip install requests).
• FMP free tier has rate limits. The skill handles 429 responses with a warning and continues with partial results.
• Events are sorted by date ascending, then by event type (earnings → dividends → splits).