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find_field_writes

Locates all write operations that modify a specific Java field to analyze data flow and state mutations in code.

Instructions

Find all write accesses (mutations) to a field.

USAGE: Position cursor on a field declaration or reference OUTPUT: List of locations where the field is modified

IMPORTANT: Uses ZERO-BASED coordinates.

Unlike find_references which returns all usages, this returns only locations where the field value is changed (assignments, increments, etc). Useful for data flow analysis and understanding state mutations.

Requires load_project to be called first.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
columnYesZero-based column number
lineYesZero-based line number
maxResultsNoMax write locations to return (default 100)
filePathYesPath to source file
Behavior4/5

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

With no annotations provided, the description carries the full burden of behavioral disclosure. It effectively describes the tool's behavior: it returns a list of write locations, uses zero-based coordinates, and requires a prior 'load_project' call. It could improve by mentioning output format details or error handling, but it covers key operational aspects well.

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 well-structured with clear sections (purpose, usage, output, important note, differentiation, and prerequisites). Each sentence adds value without redundancy, and it's front-loaded with the core functionality. The formatting enhances readability without unnecessary verbosity.

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 the tool's complexity (mutation analysis in code) and lack of annotations and output schema, the description does a good job of explaining purpose, usage, and behavior. It could be more complete by detailing the output format (e.g., structure of the list) or error cases, but it covers essential context for effective use.

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?

The schema description coverage is 100%, so the schema already documents all parameters (column, line, maxResults, filePath). The description adds minimal value beyond the schema by implying that parameters relate to cursor positioning and result limits, but doesn't provide additional syntax or format details. This meets the baseline for high schema coverage.

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 the specific action ('find all write accesses/mutations') and resource ('to a field'), distinguishing it from sibling tools like 'find_references' which returns all usages. It explicitly contrasts with 'find_references' to highlight its unique focus on mutations only.

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

Usage Guidelines5/5

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

The description provides explicit guidance on when to use this tool ('Position cursor on a field declaration or reference'), when not to use it (vs. 'find_references'), and prerequisites ('Requires load_project to be called first'). It also mentions its usefulness for 'data flow analysis and understanding state mutations'.

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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