Documentation Search Skill

Search Vrooli documentation with globbing, grep, and relevance ranking.

54|7|Updated Sep 19, 2021
One-click install
npx skills add https://github.com/Vrooli/Vrooli --skill documentation-search-skill
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: Documentation Search Skill
Source: https://github.com/Vrooli/Vrooli/tree/main/scenarios/prompt-manager/store/skills/packs/core/documentation-search
Command: npx skills add https://github.com/Vrooli/Vrooli --skill documentation-search-skill

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

Helps you rapidly locate the most relevant Vrooli documentation files by interpreting natural language queries and surveying the repository.

Core Features & Use Cases

  • Deep context parsing to translate user intent into file patterns and keywords.
  • Globbing and targeted grep to surface promising files plus relevance scoring and reference follow-up.
  • Use Case: When trying to understand how to extend Vrooli services, ask for the relevant architecture guides and receive ranked summaries from the docs.

Quick Start

Ask the Documentation Search Skill to review the Vrooli docs for guidance on extending the CLI workflow.

Frequently Asked Questions about Documentation Search Skill

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

FAQPage Schema
How do I search internal developer documentation using natural language queries?

You can search internal developer documentation by asking natural language questions, which the tool translates into file patterns and keywords using deep context parsing to locate relevant content.

What is the best way to find Vrooli architecture guides for extending services?

The best way to find Vrooli architecture guides is to query the documentation search tool, which applies globbing and targeted grep scanning to surface and rank the most relevant files.

Does the documentation search return raw text or structured JSON output?

The documentation search returns structured JSON output, providing ranked summaries and relevant content references rather than raw text or unformatted data.

Can I use this for API research and reference lookups within a local repository?

Yes, you can use this for API research and internal developer reference lookups, as it surveys the local repository using relevance ranking heuristics to prioritize the most useful files.

How does relevance ranking work when scanning repository documentation?

Relevance ranking works by applying heuristics to prioritize promising files found during globbing and grep scanning, then performing reference follow-up to ensure accurate contextual results.

What are the limitations of using globbing and grep for documentation searches?

The limitation of using globbing and grep is that searches depend on pattern matching and keyword relevance heuristics, which may struggle with highly ambiguous queries or unindexed binary content.