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mustafagoksever

Java Inspector

decompile_class

Decompile Maven dependency classes into full Java source with method bodies. Extract specific methods or paginate for focused reading.

Instructions

Decompile a Java class from Maven dependencies into full Java source code using Vineflower. Returns the complete .java source file (method bodies included). Optionally extract a single method by name, or paginate with offset/limit. Use this when you need to read the actual implementation.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
classNameYesFully qualified name of the Java class to decompile, e.g., io.micrometer.observation.ObservationRegistry or com.example.QueryBizOrderDO
projectPathYesMaven project root directory path
useCacheNoWhether to use cache, default true
decompilerPathNoJAR package path of Vineflower decompiler, optional
methodNameNoOptional method name to extract instead of the full class. When provided, only the method body is returned.
paramTypesNoOptional: filter method overloads by parameter types (e.g. ["String", "int"]). Use when multiple methods with the same name exist.
offsetNoStart line number (1-based, default: 1)
limitNoMax lines to return (0 = all lines)
formatNoOutput format. Default is text (human-readable). Use json for structured machine-readable data. Use toon for Token-Oriented Object Notation — a compact, LLM-friendly format that reduces tokens by ~40% compared to JSON while preserving structure (https://github.com/toon-format/toon).text
Behavior4/5

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

No annotations provided, so description carries full burden. It discloses tool behavior: uses Vineflower, returns full source, supports method extraction and pagination. For a read-only tool, this is adequate.

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?

Two sentences, front-loaded with purpose. Every sentence adds value: defines function, describes output, mentions options, gives usage guidance. No wasted words.

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

Completeness5/5

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

With 9 parameters, 2 required, no output schema, the description fully explains capabilities: full decompilation, method extraction, pagination. Return format is covered by parameter. Complete for the task.

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?

Schema coverage is 100%, so baseline is 3. Description adds value by explaining methodName extracts single method, paramTypes filters overloads, offset/limit pagination, and format options with context (e.g., Toon reduces tokens). Exceeds baseline.

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?

Description clearly states verb 'decompile', resource 'Java class from Maven dependencies', and outcome 'full Java source code'. Differentiates from siblings by highlighting it returns implementation code, unlike analysis tools.

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?

Explicitly states when to use: 'when you need to read the actual implementation'. Does not provide when-not or contrast with alternatives, but the use case is clear and sufficient.

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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