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Saoud Rizwan
2024-07-31 12:46:32 -04:00
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@@ -44,9 +44,9 @@ Developers tend to name directories, files, classes, functions, and other compon
Claude Dev leverages the fact that large language models are fundamentally built on natural language processing, and by focusing on these named elements we provide the LLM with a structural understanding of the codebase that aligns closely with how developers conceptualize and organize their code. By effectively extracting the "language" of the codebase, we enable the LLM to grasp structure and intent without wasting context on implementation details. Claude Dev leverages the fact that large language models are fundamentally built on natural language processing, and by focusing on these named elements we provide the LLM with a structural understanding of the codebase that aligns closely with how developers conceptualize and organize their code. By effectively extracting the "language" of the codebase, we enable the LLM to grasp structure and intent without wasting context on implementation details.
1. **File Structure**: Claude first uses the `list_files_recursive` tool to get a complete picture of the project's file structure. This provides insights into the organization of the codebase, helping Claude understand the project's architecture and identify key areas of interest. 1. **File Structure**: Claude first uses the `list_files_recursive` tool to get a complete picture of the project's file structure. It turns out Claude 3.5 Sonnet is _really_ good at inferring what it needs to process further just from these file names alone.
2. **High-Level Code Overview**: Claude may then use the `view_source_code_definitions_top_level` tool on specific directories of interest. This tool uses [tree-sitter](https://github.com/tree-sitter/tree-sitter) to parse source code with custom tag queries that extract names of classes, functions, methods, and other definitions. `view_source_code_definitions_top_level` works by first scanning your project directory, identifying source code files that tree-sitter can parse (currently supports `python`, `javascript`, `typescript`, `ruby`, `go`, `java`, `php`, `rust`, `c`, `c++`, `c#`, and `swift`), and then parsing each file into an abstract syntax tree and applies a language-specific query to extract definition names (you can see the exact query used for each language in `src/analyze-project/queries`). The results are formatted into a concise & readable output that Claude can easily interpret to quickly understand the code's structure and purpose. 2. **High-Level Code Overview**: Claude may then use the `view_source_code_definitions_top_level` tool on specific directories of interest. This tool uses [tree-sitter](https://github.com/tree-sitter/tree-sitter) to parse source code with custom tag queries that extract names of classes, functions, methods, and other definitions. `view_source_code_definitions_top_level` works by first identifying source code files that tree-sitter can parse (currently supports `python`, `javascript`, `typescript`, `ruby`, `go`, `java`, `php`, `rust`, `c`, `c++`, `c#`, `swift`), then parsing each file into an abstract syntax tree, and finally applying a language-specific query to extract definition names (you can see the exact query used for each language in `src/parse-source-code/queries`). The results are formatted into a concise & readable output that Claude can easily interpret to quickly understand the code's structure and purpose.
3. **Read Relevant Files**: With the insights gained from the project file structure and high-level code overview, Claude can then use the `read_file` tool to examine specific files that are most relevant to the task at hand. 3. **Read Relevant Files**: With the insights gained from the project file structure and high-level code overview, Claude can then use the `read_file` tool to examine specific files that are most relevant to the task at hand.