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 Bhala-Srinivash/nse-trading-skills --skill multi-timeframe-analysisgit clone --depth 1 https://github.com/Bhala-Srinivash/nse-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/bhala-srinivash/nse-trading-skills/multi-timeframe-analysis)<a href="https://agentmods.dev/skills/bhala-srinivash/nse-trading-skills/multi-timeframe-analysis"><img src="https://agentmods.dev/badge/skills/bhala-srinivash/nse-trading-skills/multi-timeframe-analysis/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/bhala-srinivash/nse-trading-skills/multi-timeframe-analysis"><img src="https://agentmods.dev/badge/skills/bhala-srinivash/nse-trading-skills/multi-timeframe-analysis.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 | $0.00105 | $0.01022 |
| Opus 5 | $0.00053 | $0.00511 |
| Sonnet 5 | $0.00021 | $0.00204 |
| Haiku 4.5 | $0.00011 | $0.00102 |
Grade A, and why
multi-timeframe-analysis 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.
How it starts
The opening of the file, as written. The whole thing — 100 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Multi-Timeframe Analysis
Higher timeframes set the direction. Lower timeframes refine the entry. Never trade against the higher timeframe trend unless you have very strong reasons.
The 3-Screen Method
| Screen | Timeframe | Purpose | What to Look For |
|---|---|---|---|
| Screen 1 | Weekly | Trend bias | Primary trend, major S/R, 200-week MA |
| Screen 2 | Daily | Setup | Pattern formation, indicator signals, entry zone |
| Screen 3 | 4H / 1H | Entry timing | Precise entry price, tight stop placement |
How to use it:
- Weekly decides direction — only take trades in the weekly trend's direction
- Daily identifies the setup — pullback to support in uptrend, rally to resistance in downtrend
- Hourly/4H times the entry — wait for the lower TF to confirm reversal in your direction
Prerequisites
No dependencies required. Framework applies to any timeframe data. Enhanced with Groww MCP (multi-interval candles) or yfinance (pip install yfinance) for weekly/monthly history.
Fetching Multi-TF Data
When data tools are available:
Weekly: fetch_historical_candle_data with interval=1w
Daily: fetch_historical_candle_data with interval=1d
Hourly: fetch_historical_candle_data with interval=1h (limited to ~30 days)
For weekly indicators via yfinance: yf.download("SYMBOL.NS", period="2y", interval="1wk")
Screen 1: Weekly Analysis
Check these on the weekly chart:
- Trend: Series of higher highs/lows (up) or lower highs/lows (down)?
- Position vs MAs: Price relative to 20W and 50W SMA
- RSI(14) weekly: Above 50 = bullish bias, below 50 = bearish bias
- Major S/R: Horizontal levels with multiple weekly touches
- Volume trend: Rising into the trend direction = healthy
Weekly verdict: Bullish / Bearish / Neutral — this sets your trading bias.
Screen 2: Daily Analysis
With the weekly bias established:
- Look for setups that align: Pullbacks to buy in uptrend, rallies to sell in downtrend
- Pattern identification: Flags, wedges, double bottoms/tops, breakouts
- Indicator signals: RSI, MACD, Bollinger on daily
- Volume: Confirmation of the setup (declining volume on pullback = healthy)
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 · 100 lines · 105 tokens per session scan A 3585024fa2e4
multi-timeframe-analysis is a skill published in the GitHub repository Bhala-Srinivash/nse-trading-skills (37 stars, last pushed 6mo ago), licensed MIT. It adds 105 tokens to every session and 1,022 once invoked, about $0.0005 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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