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oracle

Guide oracle CLI usage for bundling project context into AI prompts.

Updated Mar 10, 2026
Search Tags:#developer tools#prompt engineering#cli#ai#llm#code context
One-click install
npx skills add https://github.com/lemonlqf/openclaw-rtsp --skill oracle-lemonlqf
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: oracle
Source: https://github.com/lemonlqf/openclaw-rtsp/tree/main/skills/oracle
Command: npx skills add https://github.com/lemonlqf/openclaw-rtsp --skill oracle-lemonlqf

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes references (resource) components.

What problem does it solve?

This Skill provides guidance on effectively using the oracle command-line interface for bundling prompts with files to get context-aware answers from AI models, streamlining development workflows.

Core Features & Use Cases

  • Contextual AI Interaction: Integrates project context (code files, documentation) directly into AI prompts for more accurate and relevant responses.
  • Workflow Optimization: Offers best practices for prompt engineering, file selection, engine usage (API vs. browser), and session management to maximize efficiency and minimize token costs.
  • Use Case: A developer needs to refactor a specific module in a large codebase. They can use oracle to include the relevant source files and configuration, ask the AI for a refactoring plan, and receive code suggestions directly related to their project.

Quick Start

Use the oracle CLI 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 bundle project source files with AI prompts for context-aware code suggestions?▼

Bundling project source files with AI prompts involves using a CLI tool to integrate code context directly into model queries for accurate code suggestions. The oracle CLI specifically streamlines this by combining prompts and files to generate project-aware responses.

What is the best way to include project context when asking an AI model to refactor a module?▼

The best way to include project context for refactoring is to pass relevant source files directly into the AI prompt. Using the oracle CLI, developers can bundle specific code files and configurations, ensuring the AI provides a refactoring plan directly related to the project.

How can I preview token count for specific files before sending a prompt to an AI model?▼

To preview token count for specific files before sending an AI prompt, use the oracle CLI to estimate token usage for targeted directories. By previewing token counts for tasks like analyzing the src directory while excluding test files, you can minimize token costs.

Does the oracle CLI work with both API and browser-based model execution?▼

Yes, the oracle CLI works with both API and browser-based model execution. Engine selection between API and browser execution is a core feature, requiring the oracle binary to be installed and configured for your chosen method to optimize development workflows.

What are the limitations or safety considerations when integrating code context into AI prompts?▼

Limitations and safety considerations when integrating code context into AI prompts include managing session configurations and selecting appropriate files to avoid exposing sensitive data. The oracle CLI provides best practices for these safety precautions to protect development tasks.

Do I need to install any binary before using oracle to manage AI prompt sessions?▼

Yes, you need to install the oracle binary before using it to manage AI prompt sessions. The binary must be installed and properly configured for either API or browser-based model execution to successfully integrate project context into your AI interactions.

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