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SeanHogg
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oracle

Bundle prompts with selected files for AI code analysis and generation.

3|1|Updated Feb 23, 2026
Search Tags:#developer tools#code analysis#prompt engineering#cli#ai#context bundling
One-click install
npx skills add https://github.com/SeanHogg/coderClaw --skill oracle-seanhogg
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: oracle
Source: https://github.com/SeanHogg/coderClaw/tree/main/product/skills/oracle
Command: npx skills add https://github.com/SeanHogg/coderClaw --skill oracle-seanhogg

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 more accurate and relevant code analysis, generation, and debugging by bundling prompts with relevant files.

Core Features & Use Cases

  • Contextual Prompting: Bundles prompts with selected files for AI processing, ensuring models have necessary project context.
  • File Attachment Patterns: Supports flexible inclusion and exclusion of files using globs and explicit paths.
  • Engine Flexibility: Offers both API and browser-based execution modes for different AI models and workflows.
  • Session Management: Allows reattachment to long-running or detached sessions, preventing redundant work.
  • Use Case: Debugging a complex issue by providing the relevant source files, error messages, and a detailed problem description to an AI for analysis and suggested fixes.

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 model for accurate code analysis?▼

You can provide code context by bundling prompts with selected source files using glob patterns and explicit paths. This context bundling ensures the AI receives necessary project structure for accurate analysis and debugging.

Can I exclude specific files when bundling code context for AI processing?▼

Yes, you can exclude specific files when bundling code context. The tool supports flexible file inclusion and exclusion via globs and explicit paths, allowing you to filter out test files or irrelevant source code before AI processing.

Do I need to install any CLI tools before using this code analysis workflow?▼

Yes, you must install the 'oracle' CLI tool as a required dependency. It enables bundling prompts with files and executing context-aware code analysis via API or browser-based sessions.

What is the best way to manage long-running AI code analysis tasks?▼

The best way to manage long-running AI code analysis tasks is using session management. It allows reattaching to detached sessions, preventing redundant work and preserving previous processing context.

Does this AI code analysis support both API and browser-based execution?▼

Yes, this AI code analysis supports both API and browser-based execution modes. This engine flexibility allows you to choose different AI models and workflows based on your development requirements.

Why does my AI model lack project context when I ask it to debug source code?▼

Your AI model lacks project context because raw prompts exclude relevant file structures. Bundling prompts with selected source files ensures the model receives necessary project context for accurate analysis and suggested fixes.

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