pead-screener
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.
npx skills add BaggaT236/AI-Trading-Skills --skill pead-screener --agent claude-code
Same command for any agent — swap --agent for codex, cursor, copilot.
Weekly change comes from our own snapshots, not the repository page — it measures attention, not adoption.
# PEAD Screener - Post-Earnings Announcement Drift 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. ## When to Use - User asks for PEAD screening or post-earnings drift analysis - User wants to find earnings gap-up stocks with follow-through potential - User requests red candle breakout patterns after earnings - User asks for weekly earnings momentum setups - User provides earnings-trade-analyzer JSON output for further screening ## Prerequisites - FMP API key (set `FMP_API_KEY` environment variable or pass `--api-key`) ```bash export FMP_API_KEY=your_api_key_here ``` - Free tier (250 calls/day) is sufficient for default screening - For Mode B: earnings-trade-analyzer JSON output file with schema_version "1.0" ## Workflow ### Step 1: Prepare and Execute Screening Run the PEAD screener script in one of two modes: **Mode A (FMP earnings calendar):** ```bash # 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 \ -
- When to Use
- Prerequisites
- Workflow
- Step 1: Prepare and Execute Screening
- Step 2: Review Results
- Step 3: Present Analysis
- Step 4: Provide Actionable Guidance
- Output
- Resources
export FMP_API_KEY=your_api_key_here python3 skills/pead-screener/scripts/screen_pead.py --output-dir reports/ Custom parameters python3 skills/pead-screener/scripts/screen_pead.py \ From earnings-trade-analyzer output
What does the pead-screener skill do?
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.
How do I install it?
Run `npx skills add BaggaT236/AI-Trading-Skills --skill pead-screener --agent claude-code` — it drops the skill into your project so the agent can pick it up. Swap the --agent value for codex, cursor or copilot if you use one of those.
Where does this skill come from?
From BaggaT236/AI-Trading-Skills, a repository with 118 stars. We read it straight from the repository tree rather than a submitted listing, so what you see here is what is actually published.
Is a popular skill a good skill?
Not necessarily. Stars measure attention, not adoption — a repository can trend for a week and be abandoned. That is why we show the weekly change from our own snapshots next to the total, instead of a single flattering number.