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fuzzmind

fuzzmind-frida-mcp

by fuzzmind

frida_get_module_base

Retrieve the base address of a loaded module by providing a process target and a module name. Supports partial name matching for flexible lookup.

Instructions

Get base address of a module by name (partial match supported).

target: process name or pid (string). module_name: full or partial module name (case-insensitive). Returns the first matching module's name, base address, size, and path.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
targetYes
module_nameYes
Behavior3/5

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

With no annotations, the description carries full burden. It discloses partial match support, case-insensitivity, and return fields (name, base address, size, path). However, it omits important behaviors: what happens if no match (returns null or error?), that only the first match is returned, and any needed permissions or session context.

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 three short sentences, directly stating the purpose and parameter details. No redundancy, and the purpose is front-loaded. Every sentence adds value.

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?

For a simple two-parameter tool with no output schema or annotations, the description covers purpose, parameters, and return value adequately. However, it lacks context about needing an active target (e.g., via frida_connect) and error handling, which could be inferred but not explicit.

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 description coverage is 0%, so the description must add meaning. It does: clarifies that 'target' can be a process name or pid, and 'module_name' supports partial match (case-insensitive). This significantly aids agent understanding beyond the raw schema.

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 verb 'Get' and the resource 'base address of a module', with additional detail on partial match support. It distinguishes itself from sibling tools like frida_enumerate_modules or frida_dump_module by focusing on base address retrieval.

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?

The description provides no guidance on when to use this tool versus alternatives. It does not mention prerequisites (e.g., an active Frida session), nor does it specify when not to use it (e.g., if you need all modules, use frida_enumerate_modules).

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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