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ask-expert

Generate expert consultation documents with extracted code snippets, diffs, and architectural context under a 125 KB limit.

2|Updated Nov 13, 2025
Search Tags:#documentation#technical writing#architecture review#code extraction#git diff#expert consultation#token limits
One-click install
npx skills add https://github.com/propstreet/claude-powerpack --skill ask-expert
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: ask-expert
Source: https://github.com/propstreet/claude-powerpack/tree/main/skills/ask-expert
Command: npx skills add https://github.com/propstreet/claude-powerpack --skill ask-expert

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes scripts (resource) and references (resource) components.

What problem does it solve?

Preparing detailed technical documents for external experts, especially with code snippets, is time-consuming and often exceeds LLM token limits. Manually extracting relevant code, ensuring context, and tracking size is a tedious process that this Skill fully automates.

Core Features & Use Cases

  • Automated Code Extraction: Extracts full files, specific line ranges, or Git diffs, automatically formatting them into markdown code blocks for clarity.
  • Real-time Size Tracking: Monitors the document size against a 125KB limit, providing warnings and stopping extraction to prevent token overflow, ensuring your document fits within expert consultation constraints.
  • Structured Document Generation: Guides the creation of comprehensive consultation documents with clear sections for problem context, architecture overview, and specific questions for experts.
  • Use Case: A team needs an external architect to review a critical refactor. Instead of manually copying and pasting code and worrying about token limits, they use this Skill to automatically gather all relevant code, diffs, and architectural context into a single, size-optimized document, ready for expert review.

Quick Start

Create an expert consultation document for our authentication refactor.

Frequently Asked Questions about ask-expert

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

FAQPage Schema
How do I prepare code and diffs for external expert review without hitting token limits?▼

Automated code extraction gathers full files, line ranges, and git diffs into a structured document with real-time size tracking against a 125KB limit, ensuring your consultation materials fit within LLM constraints while preserving architectural context.

Can I extract specific line ranges and git diffs automatically into a single document?▼

Yes, the Skill extracts full files, specific line ranges, or git diffs with language-aware syntax highlighting, formats them into markdown code blocks, and consolidates them into a sectionized document ready for expert analysis.

What's the best way to organize technical documentation for architecture reviews?▼

Structure consultation documents with clear sections for problem context, architecture overview, and specific expert questions, automatically gathering relevant code snippets and diffs while monitoring document size to stay within the 125KB constraint.

Does this work with batch processing of multiple files and code sections?▼

Yes, batch processing extracts multiple files and sections with configurable extraction plans, organizing them into sectionized output with real-time size tracking to prevent token overflow during expert consultation preparation.

What happens when my document approaches the 125KB size limit?▼

The Skill provides real-time warnings as you approach the 125KB limit and stops extraction to prevent overflow, ensuring your expert consultation document remains within technical constraints while preserving the most critical code and context.

Can I use this for bug investigations and API design reviews?▼

Yes, the Skill handles bug investigations, API reviews, and architecture assessments by automatically extracting relevant code snippets, diffs, and architectural context into structured documents optimized for expert analysis and feedback.

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