mt5-log-reader

terrylica/mql5-crossover

Reads MetaTrader 5 log files to validate indicator execution, unit tests, and compilation errors. Use when user mentions Experts pane, MT5 logs, errors, or asks "did it work".

0 stars

0 forks

2 views

View on GitHub Add to Favorites

Installation

Option 1: Use slash command in Claude Code

/install-skill https://github.com/terrylica/mql5-crossover/tree/main/.claude/skills/mt5-log-reader

Option 2: Clone to skills directory

# Global (all projects)

git clone https://github.com/terrylica/mql5-crossover/tree/main/.claude/skills/mt5-log-reader ~/.claude/skills/mql5-crossover

# Project-specific

git clone https://github.com/terrylica/mql5-crossover/tree/main/.claude/skills/mt5-log-reader .claude/skills/mql5-crossover

Add MCP server to .cursor/mcp.json:

{
  "mcpServers": {
    "skillz": {
      "command": "npx",
      "args": ["-y", "skillz-mcp", "https://github.com/terrylica/mql5-crossover/tree/main/.claude/skills/mt5-log-reader"]
    }
  }
}

Restart Cursor after adding the configuration.

Option 1: Use Gemini CLI command

gemini extensions install https://github.com/terrylica/mql5-crossover/tree/main/.claude/skills/mt5-log-reader

Option 2: Clone to extensions directory

git clone https://github.com/terrylica/mql5-crossover/tree/main/.claude/skills/mt5-log-reader ~/.gemini/extensions/mql5-crossover

Related Skills

skill-writer

Guide users through creating Agent Skills for Claude Code. Use when the user wants to create, write, author, or design a new Skill, or needs help with SKILL.md files, frontmatter, or skill structure.

docstring

Write docstrings for PyTorch functions and methods following PyTorch conventions. Use when writing or updating docstrings in PyTorch code.

Convert PyTorch AT_DISPATCH macros to AT_DISPATCH_V2 format in ATen C++ code. Use when porting AT_DISPATCH_ALL_TYPES_AND*, AT_DISPATCH_FLOATING_TYPES*, or other dispatch macros to the new v2 API. For ATen kernel files, CUDA kernels, and native operator implementations.

add-uint-support

Add unsigned integer (uint) type support to PyTorch operators by updating AT_DISPATCH macros. Use when adding support for uint16, uint32, uint64 types to operators, kernels, or when user mentions enabling unsigned types, barebones unsigned types, or uint support.