What are symbol summaries in this context?

Symbol summaries are LLM-generated documents for functions that explicitly describe parameters, return types, and side effects like database writes or external API calls.

Why does this skill forbid the use of grep?

It relies exclusively on claudemem v0.2.0, which uses vector search and LLM enrichment to find code based on meaning and behavior rather than simple, often noisy, text matches.

How does this improve code navigation?

By using the --use-case navigation flag, the skill prioritizes behavioral understanding (what a function does) over raw code chunks, making it easier to trace complex logic.

What is the Developer Detective skill?

It is a specialized Claude Code skill that uses semantic indexing to help developers understand implementation details and data flow in complex repositories.

Developer Detective

Name: Developer Detective
Author: MadAppGang

byMadAppGang

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177

开发者工具

Investigates complex codebases using semantic search and indexed memory to map data flows, side effects, and implementation details.

关于

Developer Detective is a high-performance Claude Code skill designed for deep codebase exploration and architectural analysis. By leveraging claudemem v0.2.0's indexed memory and LLM enrichment, it moves beyond simple text matching to understand the actual behavior and meaning of code symbols. It is purpose-built for tasks like tracing data flow across services, identifying function side effects, and mapping error handling paths, providing developers with structured implementation reports that clarify exactly how code works within a larger system.

主要功能

Automated data flow and call chain tracing
LLM-enriched symbol summaries for behavioral context
Efficient discovery of API endpoints and logical implementations
Detailed implementation reporting including side effects and error paths
Semantic search using claudemem v0.2.0 vector embeddings
177 GitHub stars

使用场景

Onboarding to a large, unfamiliar legacy codebase to understand core logic
Tracing data movement from an API endpoint through services to the database
Auditing a system for side effects or identifying specific error handling patterns

关于

主要功能

Automated data flow and call chain tracing
LLM-enriched symbol summaries for behavioral context
Efficient discovery of API endpoints and logical implementations
Detailed implementation reporting including side effects and error paths
Semantic search using claudemem v0.2.0 vector embeddings
177 GitHub stars

使用场景

Onboarding to a large, unfamiliar legacy codebase to understand core logic
Tracing data movement from an API endpoint through services to the database
Auditing a system for side effects or identifying specific error handling patterns