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oracle

Bundle prompts with selected files for AI code analysis.

1|Updated Mar 8, 2026
Search Tags:#automation#developer tools#prompt engineering#ai#llm#code context
One-click install
npx skills add https://github.com/syxscott/PaleoClaw --skill oracle-syxscott
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: oracle
Source: https://github.com/syxscott/PaleoClaw/tree/main/skills/oracle
Command: npx skills add https://github.com/syxscott/PaleoClaw --skill oracle-syxscott

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes references (resource) components.

What problem does it solve?

This Skill streamlines the process of providing relevant code context to AI models, enabling them to generate more accurate and context-aware responses for complex coding tasks.

Core Features & Use Cases

  • Contextual Prompting: Bundles prompts with selected files for "one-shot" AI requests.
  • Browser/API Engines: Supports both browser-based and API-based interactions with AI models.
  • Use Case: When debugging a complex feature, use this Skill to bundle your prompt, relevant source files, and error messages, allowing an AI to analyze the code with full context and suggest a fix.

Quick Start

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

Frequently Asked Questions about oracle

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

FAQPage Schema
How do I bundle source files with prompts for AI code analysis?▼

Providing code context to AI models requires bundling your prompt with carefully selected source files. This approach allows the model to analyze complex features with full context awareness and suggest accurate fixes.

Can I use browser sessions for AI-driven code generation?▼

You can use interactive browser sessions for AI-driven code generation alongside direct API calls. Both engines support model interaction to analyze bundled file contexts and prompts for complex coding tasks.

What is the best way to provide error messages to an LLM for debugging?▼

The best way to provide error messages to an LLM for debugging is bundling them with relevant source files and a clear prompt. This one-shot request gives the AI full code context to analyze and suggest a fix.

How do I check token counts for files in a directory before prompting an LLM?▼

To check token counts for files in a directory before prompting an LLM, use the preview function to evaluate the selected source files. This helps manage context limits and ensures effective prompt engineering.

Does prompt engineering for AI code generation require specific file selection?▼

Prompt engineering for AI code generation does require careful selection of files. Choosing the right source files to bundle with your prompt ensures the model receives relevant code context for accurate results.

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