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Gamma Common Errors

Listed
jeremylongshore·vlatest·ai-ml·MIT

Identifies and suggests corrections for frequently made mistakes in writing, improving clarity and reducing avoidable errors.

Repository

Install on your platform

Showing Claude Code. One command installs this skill into any of the agents below.

  1. 1

    Run this in your project

    terminal
    $ npx skills add jeremylongshore/tons-of-skills-marketplace --skill gamma-common-errors -a claude-code

  2. Uses the open-source skills CLI and needs Node.js. Add -g to install it for your user instead of this project.

What we know about this skill

Publisher

jeremylongshore

Taken from the source listing. We haven't verified who controls this account.

Install target

Live repository

Not pinned. Installing fetches whatever the repository holds at the time you run the command.

Nobody has reviewed this code. TrustedSkills indexes and links skills; it does not audit, run or scan them. A skill runs with whatever access you give your agent — read the source before you install it.

Automated safety checks

scanned

We could not read this skill's source, so none of the checks below were run.

Not scanned. none of the 396 skills in the repository match this slug — it was most likely renamed or removed upstream after the registry indexed it Source recorded as jeremylongshore/claude-code-plugins-plus-skills.
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About this skill

What it does

This skill identifies and flags common errors in code generated by AI agents. It helps users understand why their agent might be producing unexpected or incorrect results, pinpointing issues like off-by-one errors, incorrect variable usage, and logical flaws. The skill aims to improve the reliability of AI-generated code through error detection and explanation.

When to use it

  • Debugging AI-generated code: Use this when you're seeing unexpected behavior or bugs in code produced by an AI agent.
  • Understanding AI reasoning: If your agent is consistently making a specific type of mistake, this skill can help diagnose the underlying issue.
  • Improving prompt engineering: By understanding common error patterns, you can refine your prompts to guide the AI towards more accurate solutions.
  • Educational purposes: Learn about typical programming errors and how an AI might make them.

Key capabilities

  • Error identification
  • Explanation of potential causes
  • Detection of off-by-one errors
  • Identification of incorrect variable usage
  • Logical flaw detection

Example prompts

  • "Analyze this code for common errors: [code snippet]"
  • "Why is my AI agent consistently producing this error in its code? [code snippet]"
  • "Explain the likely cause of these bugs found in the following code: [code snippet]"

Tips & gotchas

This skill requires a clear and complete code snippet as input. The quality of the analysis depends on the clarity and completeness of the provided code.