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Backend Logic Expert

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caomeiyouren·vlatest·backend·MIT

Analyzes and optimizes complex backend code logic, identifying inefficiencies and suggesting improvements for enhanced performance.

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This skill no longer installs under the name backend-logic-expert. SKILL.md is marked internal, so the skills CLI hides it.

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What we know about this skill

Publisher

caomeiyouren

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Install target

Live repository

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Automated safety checks

scanned

This skill passed all 6 checks. We read its files at one commit and looked for the things that make a skill dangerous to run — not for whether it works.

  • Declares what it does: passed

    SKILL.md parses and declares a name and a description.

    SKILL.md exists, its frontmatter parses, and it declares a name and a description.

  • No undeclared network calls: passed

    Makes no network calls.

    Every host the skill dials — from its scripts, its config endpoints or the commands it tells the agent to run — is either well-known package and API infrastructure or declared in its own frontmatter. Links in documentation are not counted.

  • No obfuscated payloads: passed

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  • No credential access: passed

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  • Pinned to a commit: passed

    Scanned caomeiyouren/momei at 02346816ce.

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Commit
02346816ce
Manifest
.github/skills/backend-logic-expert/SKILL.md
Scanned
1 file, 29 lines
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About this skill

What it does

This skill allows AI agents to reason about and generate complex backend logic. It can translate natural language instructions into code snippets, debug existing code, and optimize performance based on specified constraints. The agent is capable of handling various programming languages and frameworks commonly used in backend development.

When to use it

  • Automating API endpoint creation: Generate the necessary code for a new REST API endpoint given a description of its functionality and data requirements.
  • Debugging existing server-side applications: Identify and fix errors within an existing codebase, providing explanations for the changes made.
  • Optimizing database queries: Analyze slow SQL queries and suggest improvements to enhance performance.
  • Implementing business logic in microservices: Translate complex business rules into executable code for a microservice architecture.

Key capabilities

  • Code generation (multiple languages)
  • Debugging assistance
  • Performance optimization
  • API endpoint creation

Example prompts

  • "Write a Python function to calculate the average of a list of numbers."
  • "Debug this Java code snippet and explain the error: [code]"
  • "Optimize this SQL query for faster execution: [query]"
  • “Create a Node.js endpoint that accepts a POST request with JSON data and saves it to a MongoDB database.”

Tips & gotchas

The skill's effectiveness depends on providing clear and specific instructions. While it supports multiple languages, familiarity with the target language’s syntax will improve results.