Screen post-earnings gap-up stocks for PEAD (Post-Earnings Announcement Drift) patterns. Analyzes weekly candle formation to detect red candle pullbacks and breakout signals. Supports two input modes - FMP earnings calendar (Mode A) or earnings-trade-analyzer JSON output (Mode B). Use when user asks about PEAD screening, post-earnings drift, earnings gap follow-through, red candle breakout patterns, or weekly earnings momentum setups.
80
100%
Does it follow best practices?
Run evals on this skill
Adds up to 20 points to the overall score
View guide
Passed
No findings from the security scan
Screen post-earnings gap-up stocks for PEAD (Post-Earnings Announcement Drift) patterns using weekly candle analysis to detect red candle pullbacks and breakout signals.
FMP_API_KEY environment variable or pass --api-key)
export FMP_API_KEY=your_api_key_hereRun the PEAD screener script in one of two modes:
Mode A (FMP earnings calendar):
# Default: last 14 days of earnings, 5-week monitoring window
python3 skills/pead-screener/scripts/screen_pead.py --output-dir reports/
# Custom parameters
python3 skills/pead-screener/scripts/screen_pead.py \
--lookback-days 21 \
--watch-weeks 6 \
--min-gap 5.0 \
--min-market-cap 1000000000 \
--output-dir reports/Mode B (earnings-trade-analyzer JSON input):
# From earnings-trade-analyzer output
python3 skills/pead-screener/scripts/screen_pead.py \
--candidates-json reports/earnings_trade_analyzer_YYYY-MM-DD_HHMMSS.json \
--min-grade B \
--output-dir reports/Scheduled US-equity routine pitfall: Prefer Mode B for pre-market / US-equity cron briefs after running earnings-trade-analyzer. Mode A can pull the global FMP earnings calendar, spend the API budget on non-US symbols, and return weak/non-actionable foreign listings before reaching the intended US watchlist. If Mode A is used anyway and the script reports budget trimming or non-US symbols, mark PEAD output as degraded and treat it as manual-review only rather than a clean candidate source.
references/pead_strategy.md for PEAD theory and pattern contextreferences/entry_exit_rules.md for trade management rulesFor each candidate, present:
Based on stages and ratings:
pead_screener_YYYY-MM-DD_HHMMSS.json - Structured results with stage classificationpead_screener_YYYY-MM-DD_HHMMSS.md - Human-readable report grouped by stagereferences/pead_strategy.md - PEAD theory and weekly candle approachreferences/entry_exit_rules.md - Entry, exit, and position sizing rules62a1635
If you maintain this skill, you can claim it as your own. Once claimed, you can manage eval scenarios, bundle related skills, attach documentation or rules, and ensure cross-agent compatibility.