oracle

Bundle repository files and prompts into a context payload for AI models.

6|Updated Mar 13, 2026
One-click install
npx skills add https://github.com/me2Doc/friendlyclaw --skill oracle-me2doc
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: oracle
Source: https://github.com/me2Doc/friendlyclaw/tree/main/body/skills/oracle
Command: npx skills add https://github.com/me2Doc/friendlyclaw --skill oracle-me2doc

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill requires @steipete/oracle.

What problem does it solve?

This skill solves the context-window limitation by intelligently bundling your prompt and relevant repository files into a single, high-signal payload for advanced AI models.

Core Features & Use Cases

  • Context Bundling: Automatically aggregates code, documentation, and configuration files while respecting .gitignore rules.
  • Session Management: Supports long-running, asynchronous analysis sessions that can be detached and reattached.
  • Use Case: When debugging a complex system issue, use this skill to bundle your entrypoints, configuration files, and error logs into a single request for a deep-dive analysis by a high-reasoning model.

Quick Start

Use the oracle skill to analyze the current directory with a prompt asking for a summary of the project architecture.

Frequently Asked Questions about oracle

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

FAQPage Schema
How do I bundle repository context for AI code analysis?

To bundle repository context for AI code analysis, this skill aggregates your code, documentation, and configuration files with a prompt into a single high-signal payload. It respects .gitignore rules and estimates tokens to prepare a context-rich request for external AI models.

How does context bundling help with debugging complex system issues?

Context bundling helps debugging by packaging entrypoints, configuration files, and error logs together. Sending this aggregated payload to a high-reasoning AI model enables a deep-dive architectural review without losing critical file relationships.

Do I need the oracle CLI binary to analyze my repository?

Yes, you need the oracle CLI binary installed and appropriate environment configuration. This CLI interfaces with browser or API-based AI engines to process the bundled repository files and user prompts for external analysis.

Can I detach and reattach long-running code analysis sessions?

Yes, you can detach and reattach long-running asynchronous analysis sessions. This session management capability allows you to start a complex code review and check back on the AI processing results later.

What is the best way to overcome AI context window limitations for a large repository?

The best way to overcome context window limitations is intelligently bundling relevant repository files with your prompt. This method manages file selection and token estimation to ensure only high-signal context is sent to the AI model.