stockbee-exhaustion-hammer-screener

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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.

3installs

Sourcetradermonty/claude-trading-skills

Added on2026-08-20

NPX Install

npx skill4agent add tradermonty/claude-trading-skills stockbee-exhaustion-hammer-screener

SKILL.md Content

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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

marketCap

,

mutualFundHolders

,

institutionalHolders

, or

institutionalOwnershipPct

.

Run only after the market-regime workflow allows new swing risk, or mark output as manual-review-only.

Workflow

Step 1: Choose Input Mode

Use one of three modes:

Mode A: FMP universe scan

bash

python3 skills/stockbee-exhaustion-hammer-screener/scripts/screen_exhaustion_hammer.py \
  --fmp-universe \
  --max-symbols 300 \
  --market-gate allowed \
  --output-dir reports/

Mode B: Explicit symbols

bash

python3 skills/stockbee-exhaustion-hammer-screener/scripts/screen_exhaustion_hammer.py \
  --symbols APP ENPH NVDA TSLA \
  --market-gate allowed \
  --output-dir reports/

Mode C: Offline / near-close OHLCV JSON

bash

python3 skills/stockbee-exhaustion-hammer-screener/scripts/screen_exhaustion_hammer.py \
  --prices-json data/near_close_daily_ohlcv.json \
  --profiles-json data/quality_profiles.json \
  --market-gate allowed \
  --output-dir reports/

For a best-effort FMP near-close run, use quote override. This costs one additional quote call per symbol and depends on provider freshness:

bash

python3 skills/stockbee-exhaustion-hammer-screener/scripts/screen_exhaustion_hammer.py \
  --fmp-universe \
  --use-quote-latest \
  --max-api-calls 700 \
  --market-gate allowed \
  --output-dir reports/

Step 2: Run the Screening Pass

The script detects these setup families:

Selling exhaustion hammer: long lower wick, small body, strong close-location, and recovery from the day low
Undercut/reclaim hammer: current low undercuts the prior short-term low and the near-close price reclaims that level
Prior momentum pullback: recent high formed within the configured lookback, followed by a controlled pullback rather than a long-term downtrend
High-quality / liquid context: price, volume, 20-day average dollar volume, market-cap metadata, and optional holder metadata

It then scores setup quality using:

Quality / liquidity
Prior momentum
Pullback and selling-exhaustion context
Hammer candle geometry
Risk distance to the day low plus buffer
Market gate alignment

Step 3: Review Output

Read the generated JSON and Markdown reports. For each candidate, present:

Trigger type and all matched tags
Pullback depth from recent high and days since that high
Undercut/reclaim status and short-term prior low
Hammer geometry: lower wick, body, upper wick, close location, recovery from low
Volume ratios, average dollar volume, and quality metadata
Entry reference, stop reference, and risk percentage to stop
Setup score, rating, state, and reject reasons
Suggested downstream action

Step 4: Send Survivors to Trade Planning

Use the output conservatively:

A / A- candidates: validate chart manually, check earnings/news risk, then send to
```
position-sizer
```
B candidates: manual review or next-day hammer-high confirmation
Watch candidates: keep on watchlist / model book; wait for follow-through or tighter risk
Rejected candidates: retain for post-analysis, not for execution

Output

```
stockbee_exhaustion_hammer_YYYY-MM-DD_HHMMSS.json
```
- Structured candidate list, metadata, thresholds, score components, and rejects

stockbee_exhaustion_hammer_YYYY-MM-DD_HHMMSS.md

- Human-readable report grouped by rating/state

Resources

```
references/exhaustion_hammer_methodology.md
```
- Stockbee-style method summary and implementation boundaries
```
references/scoring_system.md
```
- Component weights, state thresholds, and failure filters
```
references/near_close_operations.md
```
- Near-close operational checklist and scheduling notes

stockbee-exhaustion-hammer-screener

NPX Install

Tags

SKILL.md Content

Stockbee Exhaustion Hammer Screener

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