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oracle

Bundles codebase files with prompts for AI-powered analysis and debugging.

5|Updated Feb 2, 2026
Search Tags:#developer tools#code analysis#debugging#prompt engineering#ai assistant#contextual ai
One-click install
npx skills add https://github.com/0xHoneyJar/loa-beauvoir --skill oracle-0xhoneyjar
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: oracle
Source: https://github.com/0xHoneyJar/loa-beauvoir/tree/main/skills/oracle
Command: npx skills add https://github.com/0xHoneyJar/loa-beauvoir --skill oracle-0xhoneyjar

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes references (resource) components.

What problem does it solve?

This Skill streamlines the process of providing code context to AI models, enabling them to understand and analyze your codebase more effectively, leading to better suggestions and faster debugging.

Core Features & Use Cases

  • Contextual Code Analysis: Bundles prompts with selected files to provide AI models with relevant code context for accurate responses.
  • Efficient Workflow: Supports both API and browser-based interactions, with session management for long-running tasks.
  • Use Case: When facing a complex bug, use Oracle to bundle your relevant source files and a detailed problem description, allowing an AI to analyze the code and suggest a fix with high accuracy.

Quick Start

Use the oracle skill to preview the token count for a task involving all files in the src directory, excluding test files.

Frequently Asked Questions about oracle

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I provide code context to an AI assistant for debugging?▼

To provide code context for debugging, bundle your relevant source files and a detailed problem description together. This allows the AI to analyze the codebase and suggest fixes with higher accuracy by understanding the surrounding context.

What is the best way to analyze code using AI without exceeding token limits?▼

Preview token usage before analyzing code with AI by running specific CLI commands to estimate the token count. This helps manage context limits by excluding unnecessary files like tests from the selected source directory.

Can I run AI code analysis directly in a browser instead of using an API?▼

Yes, you can run AI code analysis in browser mode. The tool supports both API and browser-based interactions, allowing you to choose your preferred engine for tasks like refactoring and code generation.

How does session management work for long-running AI code generation tasks?▼

Session management tracks long-running AI code generation tasks by maintaining state across interactions. This allows you to manage continuous prompts and file contexts without losing progress during extended debugging or refactoring sessions.

Does contextual AI code analysis work with specific file directories?▼

Yes, contextual AI code analysis works with specific file directories. You can target all files in a source directory and exclude specific files like tests to ensure the AI only receives relevant code context.

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