team-shinchan:deepsearch

Name: team-shinchan:deepsearch
Availability: InStock
Author: Seokan

Locate files, symbols, and documentation across a codebase with two-stage search.

8|2|Updated Feb 3, 2026

Search Tags:#codebase #search #repository #developer-tools #dependency-tracking #code-exploration #deepsearch

Ready to run

npx skills add https://github.com/seokan-jeong/team-shinchan --skill team-shinchan-deepsearch

💬 Prompt for ChatGPT / Claude Chat▼

Please help me install this Agent Skill.
Skill: team-shinchan:deepsearch
Source: https://github.com/seokan-jeong/team-shinchan/tree/main/skills/deepsearch
Command: npx skills add https://github.com/seokan-jeong/team-shinchan --skill team-shinchan-deepsearch

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

Rapidly locate code, documentation, and related artifacts across a large repository to answer "find" and "where is" queries without manual file-by-file inspection.

Core Features & Use Cases

Two-stage searching: Performs a fast filename/keyword scan followed by an optional deep content analysis when initial results are insufficient.
Context-aware results: Returns file paths, surrounding code context, and related documentation or dependency traces to help developers act on findings.
Use Case: Quickly find all implementations and references of an API, configuration key, or component across the codebase and surface associated docs and dependencies.

Quick Start

Use the deepsearch skill to find all occurrences of "database connection" across the repository and return matching file paths with surrounding code context.

Frequently Asked Questions about team-shinchan:deepsearch

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

FAQPage Schema

How do I search a large codebase to find all references to a specific API or configuration key?▼

You can search a large codebase by running a fast filename and keyword scan to locate API or configuration key references, followed by a deep content analysis to return file paths with surrounding code context.

What is the best way to trace dependencies and find related documentation within a repository?▼

Tracing dependencies and finding documentation uses a two-stage exploration process that matches file patterns first, then analyzes file contents and dependency relationships to surface related docs and traces.

Can I locate specific symbols and files across a large repository without manual inspection?▼

Yes, you can locate symbols and files across a large repository without manual inspection by orchestrating a lightweight fast search that identifies matching paths and an optional deep agent for content analysis.

How does deep codebase exploration work for answering where is or find queries?▼

Deep codebase exploration answers find queries by first performing a rapid filename and keyword scan, then optionally deploying a deep agent to analyze surrounding code context, documentation, and dependency relationships.

Does deep codebase search work for large repositories with complex dependency tracking?▼

Yes, deep codebase search works for large repositories by applying fast pattern matching to quickly locate files and a deeper content analysis to trace dependency relationships and surface associated documentation.

When should I use a two-stage code search instead of a standard keyword scan?▼

Use a two-stage code search when initial keyword scan results are insufficient, triggering the optional deep agent to perform deeper content analysis and trace dependency relationships for context-aware results.