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krystofbe

rope-mcp-server

by krystofbe

extract_method

Extracts a selected code region into a new method to enhance code modularity and maintainability in Python projects.

Instructions

Extract a code region as a new method.

Args: project_path: Root directory of the Python project file_path: File path relative to project_path start_line: Start line (1-based) start_col: Start column (0-based) end_line: End line (1-based) end_col: End column (0-based) new_name: Name for the extracted method

Returns: JSON with success status and list of changed files

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
project_pathYes
file_pathYes
start_lineYes
start_colYes
end_lineYes
end_colYes
new_nameYes

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes
Behavior2/5

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

No annotations are provided, so the description carries full burden. It only states that the tool returns JSON with success status and changed files, but omits important traits like whether the selection is replaced with a method call, or effects on imports.

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

Conciseness5/5

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

The description is concise and well-structured with an Args list and Returns section. No redundant sentences; every line adds value.

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?

The tool has an output schema, so return description is sufficient. However, the description lacks behavioral context (e.g., side effects on original code) and fails to differentiate usage from sibling refactoring tools, making it only partially complete.

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

Parameters4/5

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

Input schema has 0% description coverage, but the description explains each parameter (e.g., 'Start line (1-based)', 'Root directory of the Python project'). This adds meaning beyond the bare schema types, though some details (e.g., line inclusivity) could be clearer.

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 clearly states 'Extract a code region as a new method', which is a specific verb and resource. It distinguishes well from siblings like rename_symbol or move_symbol, which are different refactoring operations.

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

Usage Guidelines2/5

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

No guidance is provided on when to use this tool versus alternatives (e.g., inline_variable, convert_module_to_init). There is no mention of prerequisites such as the file being open or the region being valid for extraction.

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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