stockbee-exhaustion-hammer-screener
Screen US stocks for Stockbee-style selling-exhaustion hammer setups using prior momentum, pullback depth, undercut/reclaim, long lower-wick geometry, close-location, volume confirmation, quality/liquidity gates, and risk-distance scoring. Use when the user asks for Stockbee, Pradeep Bonde, exhaustion setup, selling exhaustion, hammer reversal, undercut reclaim, near-close reversal candidates, or pullback entries in high-quality funds-owned stocks.
npx skills add BaggaT236/AI-Trading-Skills --skill stockbee-exhaustion-hammer-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.
# Stockbee Exhaustion Hammer Screener Screen US equities for Stockbee-style selling-exhaustion hammer candidates. The skill is a candidate-generation and setup-quality workflow, not a signal service or an auto-execution system. ## When to Use - User asks for Stockbee / Pradeep Bonde style exhaustion setup screening - User wants near-close hammer / long lower-wick reversal candidates - User wants to scan strong, liquid stocks that pulled back and may be seeing selling exhaustion - User wants undercut/reclaim candidates before the close or after the close - User provides a symbol list, universe file, or historical / provisional OHLCV JSON for screening - User wants candidate outputs to feed into `technical-analyst`, `position-sizer`, `trader-memory-core`, or `stockbee-setup-fluency-trainer` ## Prerequisites - FMP API key for live universe and historical OHLCV screening: ```bash export FMP_API_KEY=your_api_key_here ``` - Optional no-API path: provide `--prices-json` containing daily OHLCV bars by symbol. For the intended near-close use case, the latest bar should be a provisional current-day bar captured near the close. - Optional `--profiles-json` can add quality metadata such as `ma
- When to Use
- Prerequisites
- Workflow
- Step 1: Choose Input Mode
- Step 2: Run the Screening Pass
- Step 3: Review Output
- Step 4: Send Survivors to Trade Planning
- Output
- Resources
export FMP_API_KEY=your_api_key_here python3 skills/stockbee-exhaustion-hammer-screener/scripts/screen_exhaustion_hammer.py \
What does the stockbee-exhaustion-hammer-screener skill do?
Screen US stocks for Stockbee-style selling-exhaustion hammer setups using prior momentum, pullback depth, undercut/reclaim, long lower-wick geometry, close-location, volume confirmation, quality/liquidity gates, and risk-distance scoring. Use when the user asks for Stockbee, Pradeep Bonde, exhaustion setup, selling exhaustion, hammer reversal, undercut reclaim, near-close reversal candidates, or pullback entries in high-quality funds-owned stocks.
How do I install it?
Run `npx skills add BaggaT236/AI-Trading-Skills --skill stockbee-exhaustion-hammer-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.