Skip to main content
Glama

extract_constant

Extracts a selected expression into a static final constant. Returns text edits to apply the constant declaration and replacement.

Instructions

Extract an expression into a static final constant at class level.

Returns the text edits needed to extract the expression. The caller should apply these edits to perform the extraction.

USAGE: Select expression by providing start and end positions OUTPUT: Constant declaration and replacement edits

IMPORTANT: Uses ZERO-BASED coordinates.

Requires load_project to be called first.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
endLineYesZero-based end line of expression
startColumnYesZero-based start column of expression
filePathYesPath to source file
endColumnYesZero-based end column of expression
constantNameYesName for the constant (should be UPPER_SNAKE_CASE)
startLineYesZero-based start line of expression
Behavior4/5

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

With no annotations, the description carries full burden. It explains the tool returns text edits (non-destructive) and that caller applies them. Also clarifies zero-based coordinate system and prerequisite, providing good behavioral insight.

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?

Extremely concise: 4 short sentences plus structured USAGE/OUTPUT/IMPORTANT sections. Every sentence adds value with no redundancy. Front-loaded main purpose.

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

Completeness4/5

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

Given no output schema, the description adequately explains return value (text edits) and prerequisite. For a refactoring tool, this is sufficiently complete to guide an agent.

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

Parameters3/5

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

Schema coverage is 100%, so the schema already documents parameters. Description reinforces zero-based coordinates but doesn't add significant meaning beyond what schema provides. Baseline score of 3 is appropriate.

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 an expression into a static final constant at class level,' which is a specific verb-resource combination. It distinguishes itself from sibling tools like extract_variable and extract_method by targeting constants.

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?

Provides explicit usage instructions: select expression by positions, zero-based coordinates, and prerequisite 'Requires load_project to be called first.' Lacks explicit alternatives or when-not-to-use, but context is clear for a refactoring tool.

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

Install Server

Other Tools

Latest Blog Posts

MCP directory API

We provide all the information about MCP servers via our MCP API.

curl -X GET 'https://glama.ai/api/mcp/v1/servers/pzalutski-pixel/javalens-mcp'

If you have feedback or need assistance with the MCP directory API, please join our Discord server