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Codeql Database Building

Listed
aleister1102·vlatest·database

Helps with database, building as part of working with databases and data persistence workflows.

Install on your platform

This skill no longer installs under the name codeql-database-building. aleister1102/skills is deleted or private, so it cannot be installed from.

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Repository install instructions

What we know about this skill

Publisher

aleister1102

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.

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Automated safety checks

scanned

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Not scanned. repository not found or private Source recorded as aleister1102/skills.
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About this skill

What it does

This skill allows an AI agent to build a CodeQL database from source code. A CodeQL database is a representation of the codebase that can be queried using the CodeQL language, enabling static analysis and vulnerability detection. This facilitates identifying potential security flaws and enforcing coding standards within projects.

When to use it

  • Security Audits: When you need to perform a comprehensive security audit on a software project to identify vulnerabilities.
  • Code Quality Checks: To automatically enforce coding standards and best practices across a codebase.
  • Vulnerability Research: For researchers analyzing codebases to discover new vulnerabilities or patterns of malicious behavior.
  • Compliance Enforcement: To ensure adherence to specific security regulations by identifying non-compliant code patterns.

Key capabilities

  • Database creation from source code
  • Support for various programming languages (implied)
  • Static analysis enablement through CodeQL queries

Example prompts

  • "Build a CodeQL database for this repository: [repository URL]"
  • "Create a CodeQL database from the following Java code: [code snippet]"
  • "Generate a CodeQL database and save it as 'my_project.db'."

Tips & gotchas

The agent will require access to the source code being analyzed, either through direct file input or a repository URL. Building a CodeQL database can be computationally intensive and may take significant time depending on the size of the codebase.