Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx skills add mphinance/alpha-skills --skill pead-screenergit clone --depth 1 https://github.com/mphinance/alpha-skillsWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/mphinance/alpha-skills/pead-screener)<a href="https://agentmods.dev/skills/mphinance/alpha-skills/pead-screener"><img src="https://agentmods.dev/badge/skills/mphinance/alpha-skills/pead-screener/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/mphinance/alpha-skills/pead-screener"><img src="https://agentmods.dev/badge/skills/mphinance/alpha-skills/pead-screener.svg" alt="Reviewed on agentmods" width="80" height="20"></a>What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00098 | $0.00851 |
| Opus 5.5 | $0.00039 | $0.00340 |
| Sonnet 5.5 | $0.00020 | $0.00170 |
| Haiku 4.5 | $0.00010 | $0.00085 |
Grade A, and why
pead-screener scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 1mo ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
This is a copy
86% identical to pead-screener — 12 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.
How it starts
The opening of the file, as written. The whole thing — 89 lines — stays where its author put it; the contents beside it link to each section on GitHub.
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)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)
What ships with it
14 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
- README.md 3.4 KB
- references/entry_exit_rules.md 3.8 KB
- references/pead_strategy.md 5.3 KB
- scripts/calculators/__init__.py 28 B runs code
- scripts/calculators/breakout_calculator.py 3.0 KB runs code
- scripts/calculators/liquidity_calculator.py 2.5 KB runs code
- scripts/calculators/risk_reward_calculator.py 2.3 KB runs code
- scripts/calculators/weekly_candle_calculator.py 10 KB runs code
- scripts/fmp_client.py 13 KB runs code
- scripts/report_generator.py 9.8 KB runs code
- scripts/scorer.py 3.6 KB runs code
- scripts/screen_pead.py 22 KB runs code
- scripts/tests/conftest.py 181 B runs code
- scripts/tests/test_pead_screener.py 49 KB runs code
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 1mo ago First seen · 89 lines · 98 tokens per session scan A 918b6293ced4
pead-screener is a skill published in the GitHub repository mphinance/alpha-skills (28 stars, last pushed 10d ago), licensed MIT. It adds 98 tokens to every session and 851 once invoked, about $0.0004 per session on Opus 5.5. A static security scan graded it A with 0 findings. It is 86% identical to pead-screener, differing in 12 lines, and is treated as a copy.
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