stop-loss-strategies

stop-loss-strategies is a skill for Claude Code, Codex from Bhala-Srinivash/nse-trading-skills. It costs 98 tokens per session (953 once invoked), scanned A, original, MIT.

A guide for setting stop-loss levels on NSE and BSE equity trades. A stop-loss is an instruction to limit how much a trade can lose.

In plain words
What is it for?
Use it to choose structure-, ATR-, support/resistance-, or moving-average-based stops for Indian stock trades.
Why use it?
It helps turn chart levels and volatility into a defined exit point before entering a position.

Skill for Claude CodeCodex

Written for no agent in particular: nothing here depends on one.

Good fit Use it to choose structure-, ATR-, support/resistance-, or moving-average-based stops for Indian stock trades.

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Install with agentmods
npx agentmods add skills/bhala-srinivash/nse-trading-skills/stop-loss-strategies
Install

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.

Any agent
npx skills add Bhala-Srinivash/nse-trading-skills --skill stop-loss-strategies
Clone the repo
git clone --depth 1 https://github.com/Bhala-Srinivash/nse-trading-skills

Made for: Claude Code, Codex.

Wrote 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.

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README.md
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Per session 98 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 953 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe.
Origin original No closer match found in the catalogue.
Token cost

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.

ModelPer sessionOnce invoked
Fable 5.1 $0.00098 $0.00953
Opus 5 $0.00049 $0.00477
Sonnet 5 $0.00020 $0.00191
Haiku 4.5 $0.00010 $0.00095

Measured 12d ago against content hash 717ac26ad88a, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-12, from the pricing page.

Security

Grade A, and why

stop-loss-strategies 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.

stop-loss-strategies/SKILL.md · 94 lines

How it starts

The opening of the file, as written. The whole thing — 94 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Stop-Loss Strategies

A stop-loss is not optional. Every position needs one before entry. The purpose is to cap your maximum loss — not to predict where price will go.

Prerequisites

No dependencies required. Provide entry price and key levels manually. Enhanced with Groww MCP (candles, ATR, MAs) or yfinance (pip install yfinance).

Data Needed

  1. Entry price: Known or planned
  2. Recent candles: fetch_historical_candle_data (daily, last 60 days) or user-provided levels
  3. ATR(14): get_historical_technical_indicators from Groww, or calculate manually
  4. Key S/R levels: From technical-analysis skill or swing highs/lows
  5. Moving averages: SMA20, SMA50, SMA200

Stop Type Selection

Method Best For How to Calculate
Structure-based Swing trades, clear chart patterns Below recent swing low (long) or above swing high (short)
ATR-based Volatile stocks, no clear structure Entry - ATR(14) × 1.5 to 2.0
Support/Resistance Range-bound markets, clear levels Below key support level + buffer
Moving Average Trend-following trades Below SMA20 (aggressive) or SMA50 (conservative)

Structure-Based (Preferred)

Find the most recent swing low (for longs) that, if broken, would invalidate your trade thesis.

Stop = Recent swing low - buffer
Buffer = 0.5% for large-caps, 1% for mid/small-caps

ATR-Based

Adapts to the stock's natural volatility:

Stop (long) = Entry - ATR(14) × multiplier
Stop (short) = Entry + ATR(14) × multiplier

Multiplier: 1.5 (tight) to 2.0 (standard) to 2.5 (loose)

Support/Resistance-Based

Place stop just below a confirmed support level:

Stop = Support level × (1 - buffer%)
Buffer: 0.5% large-cap, 1.0% mid/small-cap

Only use levels with at least 2 historical touches.

Moving Average-Based

For trend-following positions:

Aggressive: Stop below SMA20 (for short-term trends)
Moderate: Stop below SMA50 (for medium-term trends)
Conservative: Stop below SMA200 (for long-term holds)

Best when MA is clearly sloping in your direction.

Read the full file on GitHub · 94 lines

Changes

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.

  1. 12d ago First seen · 94 lines · 98 tokens per session scan A 717ac26ad88a

Subscribe to this mod's changes

stop-loss-strategies is a skill published in the GitHub repository Bhala-Srinivash/nse-trading-skills (38 stars, last pushed 6mo ago), licensed MIT. It adds 98 tokens to every session and 953 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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