Install
$ agentstack add skill-xonevn-ai-xone-trading-skills-pead-screener ✓ scanned · ✓ verified, works with Claude Code, Cursor, and more.
Security review
✓ PassedNo issues found. Passed automated security review. · v0.1.0 How review works →
- ✓ Prompt-injection patterns
- ✓ Secret / credential exfiltration
- ✓ Dangerous shell & filesystem operations
- ✓ Untrusted network calls
- ✓ Known-malicious package signatures
What it can access
- ✓ Network access No
- ✓ Filesystem access No
- ✓ Shell / process execution No
- ✓ Environment & secrets No
- ✓ Dynamic code execution No
From automated source analysis of v0.1.0. “Used” means the capability is present in the source — more access means more to trust, not that it’s unsafe.
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Reliability & compatibility
Declared compatibility
Compatibility is declared by the source manifest. End-to-end runtime verification is coming, see below.
We're building live execution health for every listing: tool-call success rate, median latency, uptime, and last-checked timestamps, measured, not self-reported. It isn't live yet, so we don't show numbers we can't stand behind.
How agent discovery & health will work →About
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_KEYenvironment 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):
# 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/
Step 2: Review Results
- Read the generated JSON and Markdown reports
- Load
references/pead_strategy.mdfor PEAD theory and pattern context - Load
references/entry_exit_rules.mdfor trade management rules
Step 3: Present Analysis
For each candidate, present:
- Stage classification (MONITORING, SIGNAL_READY, BREAKOUT, EXPIRED)
- Weekly candle pattern details (red candle location, breakout status)
- Composite score and rating
- Trade setup: entry, stop-loss, target, risk/reward ratio
- Liquidity metrics (ADV20, average volume)
Step 4: Provide Actionable Guidance
Based on stages and ratings:
- BREAKOUT + Strong Setup (85+): High-conviction PEAD trade, full position size
- BREAKOUT + Good Setup (70-84): Solid PEAD setup, standard position size
- SIGNAL_READY: Red candle formed, set alert for breakout above red candle high
- MONITORING: Post-earnings, no red candle yet, add to watchlist
- EXPIRED: Beyond monitoring window, remove from watchlist
Output
pead_screener_YYYY-MM-DD_HHMMSS.json- Structured results with stage classificationpead_screener_YYYY-MM-DD_HHMMSS.md- Human-readable report grouped by stage
Resources
references/pead_strategy.md- PEAD theory and weekly candle approachreferences/entry_exit_rules.md- Entry, exit, and position sizing rules
Source & license
This open-source skill is cataloged on AgentStack and links to its original source — we do not rehost the code.
- Author: xonevn-ai
- Source: xonevn-ai/xone-trading-skills
- License: MIT
- Homepage: https://xone.vn
Install and usage instructions live in the source repository linked above.
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Versions
- v0.1.0 Imported from the upstream source.