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trace_feature_implementation

Map all code involved in a feature from UI to data layer to understand its components, trace dependencies, and locate affected files before modifications.

Instructions

Map all code involved in implementing a specific feature from UI to data layer.

Use this tool when you need to:

  • Understand all components involved in a feature before modifying it

  • Map feature implementation across multiple layers (UI, business logic, data)

  • Find all related code that might be affected by feature changes

  • Understand how a feature is structured and organized

Perfect for feature modification, debugging feature issues, or understanding complex feature implementations that span multiple modules.

Args: repo_path: Repository path (absolute) working_directory: Working directory (absolute path) feature_keywords: List of keywords that identify the feature (e.g., ["login", "authenticate"]) file_categories: Dictionary mapping category names to path patterns for file organization. Format: {"category_name": ["pattern1", "pattern2", ...]}

    Example:
    {
        "ui_frontend": ["view", "template", "component", "ui", "frontend"],
        "api_controllers": ["api", "controller", "endpoint", "route"],
        "business_logic": ["service", "business", "logic", "core"],
        "data_models": ["model", "entity", "schema", "db"],
        "utilities": ["util", "helper", "common"],
        "tests": ["test", "spec"],
        "config": ["config", "setting", "env"]
    }
    
    Files are categorized by checking if any pattern appears in the file path.
    Use descriptive category names that match your project structure.
include_tests: Whether to include test files in the analysis
include_config: Whether to include configuration files
trace_depth: How deep to trace dependencies

Returns: Complete feature implementation map with all involved components by layer

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
repo_pathYes
trace_depthNo
include_testsNo
include_configNo
file_categoriesYes
feature_keywordsYes
working_directoryYes
Behavior3/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

With no annotations, the description carries the full burden. It explains file categorization behavior ('Files are categorized by checking if any pattern appears in the file path') and the overall mapping intent. However, it does not disclose whether the tool is read-only (no modifications), how trace_depth affects behavior, or what happens when no files match, leaving behavioral gaps.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is structured with a clear intro, usage bullets, and an organized Args section with an example. It is longer than average but appropriate for 7 parameters including a nested object. Minor redundancy: 'Perfect for feature modification...' overlaps with the earlier bullet list, but overall every section earns its place.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness3/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a tool with 7 parameters, no annotations, and no output schema, the description covers purpose, usage, and parameters well. The 'Returns' section is minimal ('Complete feature implementation map with all involved components by layer') and does not describe output structure, how trace_depth influences results, or edge cases. Completeness is adequate but not exhaustive.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters5/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 0%, so the description must fully explain parameters, and it does. Each argument has a meaningful explanation; file_categories includes a detailed format and example, and trace_depth/booleans are described. This compensates completely for the schema's lack of descriptions.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description opens with a specific verb and resource: 'Map all code involved in implementing a specific feature from UI to data layer.' It clearly defines the scope (feature implementation, multi-layer) and distinguishes itself from sibling tools like trace_data_flow or map_integration_points by focusing on feature implementation mapping.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines4/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description provides an explicit 'Use this tool when you need to' list covering four common scenarios, and adds 'Perfect for feature modification, debugging feature issues, or understanding complex feature implementations.' It lacks explicit when-not-to-use guidance or named alternatives, but the use cases are clear and actionable.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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