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Scalping strategy

Skill 0xgetz/xi-agent-skills/trading-skills/scalping-strategy

Skills and connected MCP server documentation exported from my agent.

Install
npx -y skills add 0xgetz/xi-agent-skills --skill scalping-strategy

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What its author says it does

Copied from the file, not written here

Analyze markets using Scalping Strategy (scalping). Capture small frequent moves with tight risk control. Activate when the user asks to analyze, interpret, or build signals based on Scalping Strategy or scalping.

SKILL.md

1.8 KB, 341 tokens by cl100k_base, as published. Nobody here has run it

Scalping Strategy

Overview

Scalping Strategy (scalping) — Capture small frequent moves with tight risk control.

When to use this skill

Use when the user asks to:

  • Analyze or interpret Scalping Strategy on a chart or dataset
  • Build buy/sell signals or alerts based on scalping
  • Combine Scalping Strategy with other indicators for confirmation

How it works

Capture small frequent moves with tight risk control. Apply it on OHLCV data (open, high, low, close, volume) for any timeframe. Always confirm with price structure, trend context, and at least one independent indicator before acting.

Reading the signals

  • Bullish bias: signal aligns with higher highs/higher lows and rising volume.
  • Bearish bias: signal aligns with lower highs/lower lows and rising volume.
  • No-trade: conflicting context or low volatility/volume.

Worked example (Python)

import pandas as pd
# df has columns: open, high, low, close, volume (datetime index)
# Compute the indicator, then generate signals
# (use pandas/numpy or ta libraries; validate on out-of-sample data)

Risk management

  • Define stop-loss from structure or ATR before entry.
  • Size positions by fixed-fractional risk (e.g. 0.5–1% per trade).
  • Never rely on a single indicator; require confluence.

Common pitfalls

  • Over-optimizing parameters to past data (curve fitting).
  • Ignoring the higher-timeframe trend.
  • Acting on signals during low liquidity.

Educational analysis only. Not financial advice.

Gives 0 of the 12 instructions most roadmap strategy skills give in 341 tokens

Counted across 591 of the 672 authors here whose files we hold, read 2026-08-07

  • read product marketing context before asking questionsin 21 of 591, across 10 files
  • base price on perceived value, not costin 15 of 591, across 4 files
  • compact after finalizing a planin 14 of 591, across 9 files
  • differentiate tiers using features, limits, or supportin 14 of 591, across 3 files
  • use Van Westendorp to find acceptable price rangein 13 of 591, across 2 files
  • use MaxDiff to identify highly valued featuresin 13 of 591, across 2 files
  • map topics to buyer journey stagesin 12 of 591, across 6 files
  • Extract domain capabilities and classify subdomainsin 11 of 591, across 1 file
  • Define bounded contexts around consistency and ownershipin 11 of 591, across 1 file
  • Establish a ubiquitous language glossary and anti-termsin 11 of 591, across 1 file
  • Capture context boundaries in ADRs before implementationin 11 of 591, across 1 file
  • Open the strategic design template if neededin 11 of 591, across 1 file

Said here and by no other author read

  • Apply strategy on OHLCV data
  • Confirm with price structure before acting
  • Confirm with trend context before acting
  • Use at least one independent indicator for confirmation
  • Require signal alignment with higher highs and higher lows
  • Size positions by fixed-fractional risk

Grouped from the skills themselves: near-identical wordings counted once, and counted by distinct author, so one author publishing three of these counts once. Length counted with cl100k_base; the agent that loads this file may tokenize it differently.

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