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extract_dll_classes

List class names in .NET DLLs via stream-based analysis, supporting very large files. Filter by search terms or cap class count to inspect game or mod assemblies.

Instructions

Extract class names from a .NET DLL using stream-based analysis. Works with very large files.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
file_pathYesPath to DLL file
max_classesNoMax classes to return (default 200)
search_termsNoFilter by these terms (case-insensitive)

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.4

TDQS

A3.5/5.0
Behavior3/5

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

With no annotations, the description carries the full burden, and it does disclose one real behavioral trait: stream-based analysis that tolerates very large files. It says nothing about error handling on non-.NET/invalid binaries, output ordering, or whether the scan is exhaustive or truncated, leaving meaningful behavioral gaps for a no-annotation tool.

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 short sentences, front-loaded with the action and resource, with the second sentence adding a distinct constraint. No filler or restatement of the name.

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?

There is no output schema and no annotations, so the description is the only source for behavior, yet it never states the return shape (e.g., flat list of fully-qualified names vs. nested), ordering, or failure mode on non-.NET files. It is adequate for a simple three-parameter read tool but leaves those gaps unfilled.

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 description coverage is 100%, so file_path, max_classes (default 200), and search_terms (case-insensitive filter) are already fully documented in the schema. The description adds no parameter-level detail such as filter matching semantics against namespaces or what happens when max_classes truncates results, so the baseline 3 applies.

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

Purpose4/5

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

The description names a specific verb ("Extract") and resource ("class names from a .NET DLL"), so an agent knows exactly what it produces. It doesn't differentiate itself from close siblings like list_types or analyze_dll_structure, which likely also enumerate types from assemblies, so it falls short of a 5.

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

Usage Guidelines3/5

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

The phrase "Works with very large files" implicitly signals when this tool is preferable (huge DLLs where stream-based parsing matters), but there is no explicit when-to-use, when-not-to-use, or named alternative such as list_types or analyze_dll_structure. Usage is implied rather than stated.

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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