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fuzzmind

fuzzmind-frida-mcp

by fuzzmind

frida_device_input

Inject raw base64-decoded input into a spawned target process for dynamic analysis and application security research.

Instructions

Send raw base64-decoded input bytes to a spawned target.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
targetYes
data_base64Yes
device_idNo
Behavior2/5

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

With no annotations, the description must disclose behavioral traits. It mentions base64-decoding and the 'spawned' requirement, but fails to explain side effects, permissions, error conditions, or how the input is delivered (e.g., stdin or other mechanism). This is insufficient for a mutation-like operation.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is a single, clear sentence—very concise. However, its brevity sacrifices necessary detail, making it less effective than a slightly longer, structured explanation. It earns its place but could be expanded.

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

Completeness2/5

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

Given the tool's complexity (3 params, no output schema, no annotations) and the large sibling set, the description is far from complete. It lacks details on parameter values, target identification, device scoping, and return behavior, making it inadequate for an agent to reliably use the tool.

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

Parameters1/5

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

Schema description coverage is 0% and the description adds no parameter-level details. It does not explain what 'target', 'data_base64', or 'device_id' represent, their format, constraints, or how they relate to the tool's operation. This is a critical gap for correct invocation.

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 action ('send'), the resource ('raw base64-decoded input bytes'), and the context ('to a spawned target'). It succinctly distinguishes this tool from siblings like frida_write_memory or frida_inject_library by specifying the input type and the requirement for the target to be spawned.

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?

No guidance is provided on when to use this tool versus alternatives, nor any conditions or prerequisites. The description lacks exclusions or context about suitable scenarios, leaving the agent without decision support.

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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