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 BaggaT236/AI-Trading-Skills --skill stockbee-momentum-burst-screenergit clone --depth 1 https://github.com/BaggaT236/AI-Trading-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/baggat236/ai-trading-skills/stockbee-momentum-burst-screener)<a href="https://agentmods.dev/skills/baggat236/ai-trading-skills/stockbee-momentum-burst-screener"><img src="https://agentmods.dev/badge/skills/baggat236/ai-trading-skills/stockbee-momentum-burst-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/baggat236/ai-trading-skills/stockbee-momentum-burst-screener"><img src="https://agentmods.dev/badge/skills/baggat236/ai-trading-skills/stockbee-momentum-burst-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 | $0.00097 | $0.00988 |
| Opus 5 | $0.00048 | $0.00494 |
| Sonnet 5 | $0.00019 | $0.00198 |
| Haiku 4.5 | $0.00010 | $0.00099 |
Grade A, and why
stockbee-momentum-burst-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 12d 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
100% identical to stockbee-momentum-burst-screener — 0 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 — 104 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Stockbee Momentum Burst Screener
Screen US equities for Stockbee-style short-term Momentum Burst 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 Momentum Burst screening
- User wants 4% breakout, dollar breakout, or range expansion candidates
- User asks for short-term 3-5 day swing momentum setups
- User wants to review whether a daily breakout has A/B/C setup quality
- User provides a symbol list, universe file, or historical OHLCV JSON for screening
- User wants candidate outputs to feed into
technical-analyst,position-sizer, ortrader-memory-core
Prerequisites
- FMP API key for live universe and historical OHLCV screening:
export FMP_API_KEY=your_api_key_here - Optional no-API path: provide
--prices-jsoncontaining daily OHLCV bars by symbol. - 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
python3 skills/stockbee-momentum-burst-screener/scripts/screen_momentum_burst.py \
--fmp-universe \
--max-symbols 300 \
--output-dir reports/
Mode B: Explicit symbols
python3 skills/stockbee-momentum-burst-screener/scripts/screen_momentum_burst.py \
--symbols NVDA SMCI PLTR TSLA \
--output-dir reports/
Mode C: Offline OHLCV JSON
python3 skills/stockbee-momentum-burst-screener/scripts/screen_momentum_burst.py \
--prices-json data/daily_ohlcv.json \
--output-dir reports/
Step 2: Run the Screening Pass
The script detects these trigger families:
- 4% Breakout:
close / previous_close >= 1.04, volume above previous day, and volume above the liquidity floor - Dollar Breakout:
close - open >= 0.90, volume above the liquidity floor - Range Expansion: current daily range exceeds the prior three daily ranges while the prior day was not already extended
What ships with it
5 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.
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.
- 12d ago First seen · 104 lines · 97 tokens per session scan A cfa25c366847
stockbee-momentum-burst-screener is a skill published in the GitHub repository BaggaT236/AI-Trading-Skills (121 stars, last pushed 9d ago), licensed MIT. It adds 97 tokens to every session and 988 once invoked, about $0.0005 per session on Opus 5. A static security scan graded it A with 0 findings. It is 100% identical to stockbee-momentum-burst-screener, differing in 0 lines, and is treated as a copy.
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