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 besoeasy/open-skills --skill trading-indicators-from-price-datagit clone --depth 1 https://github.com/besoeasy/open-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/besoeasy/open-skills/trading-indicators-from-price-data)<a href="https://agentmods.dev/skills/besoeasy/open-skills/trading-indicators-from-price-data"><img src="https://agentmods.dev/badge/skills/besoeasy/open-skills/trading-indicators-from-price-data/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/besoeasy/open-skills/trading-indicators-from-price-data"><img src="https://agentmods.dev/badge/skills/besoeasy/open-skills/trading-indicators-from-price-data.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector pass
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 | $0.00024 | $0.00512 |
| Opus 5 | $0.00012 | $0.00256 |
| Sonnet 5 | $0.00005 | $0.00102 |
| Haiku 4.5 | $0.00002 | $0.00051 |
Grade A, and why
trading-indicators-from-price-data 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.
What it actually says
Trading Indicators from Price Data (20 common indicators)
Calculate 20 widely used trading indicators from OHLCV candles (open, high, low, close, volume) using Python.
This skill is useful for:
- signal generation
- strategy backtesting
- feature engineering for ML models
- market condition dashboards
Requirements
Install dependencies:
pip install pandas pandas-ta
Input data must include these columns:
openhighlowclosevolume
20 indicators included
- RSI (14)
- MACD line (12,26)
- MACD signal (9)
- MACD histogram
- SMA (20)
- SMA (50)
- EMA (20)
- EMA (50)
- WMA (20)
- Bollinger upper band (20,2)
- Bollinger middle band (20,2)
- Bollinger lower band (20,2)
- Stochastic %K (14,3,3)
- Stochastic %D (14,3,3)
- ATR (14)
- ADX (14)
- CCI (20)
- OBV
- MFI (14)
- ROC (12)
Notes
- Indicators need warmup candles (first rows can be
NaN). - For stable output, use at least 200 candles.
- If you run this on minute candles, indicators are intraday; on daily candles, they are swing/position oriented.
Agent prompt
You have a trading-indicators skill.
When given OHLCV price data, calculate the following 20 indicators:
RSI(14), MACD line/signal/histogram (12,26,9), SMA(20), SMA(50), EMA(20), EMA(50), WMA(20),
Bollinger upper/middle/lower (20,2), Stoch %K/%D (14,3,3), ATR(14), ADX(14), CCI(20), OBV, MFI(14), ROC(12).
Return a table with the latest value of each indicator and include the last 50 rows when requested.
If data is insufficient, ask for more candles.
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 · 72 lines · 24 tokens per session scan A 39e548438e33
trading-indicators-from-price-data is a skill published in the GitHub repository besoeasy/open-skills (132 stars, last pushed 7d ago), licensed MIT. It adds 24 tokens to every session and 512 once invoked, about $0.0001 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.
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