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1shin-7
by 1shin-7

frida_inject_library_file

Inject native library files (.so/.dylib) into running processes by PID, specifying an entrypoint function and data argument to enable dynamic instrumentation on target devices.

Instructions

Inject a native library file (.so/.dylib) into a process.

Args: pid: Target process PID. path: Absolute path to the library on the device. entrypoint: Name of the entry function in the library. data: String argument passed to the entrypoint. device_id: Target device. Uses default if omitted.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
pidYes
dataYes
pathYes
device_idNo
entrypointYes

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Behavior2/5

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

With no annotations provided, the description bears the full responsibility for behavioral disclosure. It only states the injection action and parameter meanings, omitting side effects, prerequisites (e.g., permissions, process state), or potential risks such as process crashes. For a system-level injection tool, this is a significant gap in transparency.

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 highly concise, consisting of a single-sentence summary followed by a compact, well-formatted argument list. Every element provides necessary information without redundancy. The structure is easy to scan and effectively front-loads the core purpose.

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?

The existence of an output schema reduces the need to describe return values, and parameter coverage is solid. However, the description lacks essential context for a complex operation: it does not specify when to use this over sibling tools, what errors might occur, or what happens to the process after injection. This leaves the agent with gaps in understanding the full scope of the tool.

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

Parameters5/5

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

The description thoroughly explains all five parameters in the 'Args' section, adding meaning beyond the bare schema types. For example, 'path' is clarified as an absolute path on the device, 'data' as a string argument passed to the entrypoint, and 'device_id' as optional with a default. This is especially valuable given the schema has 0% description coverage for parameters.

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 tool's action: 'Inject a native library file (.so/.dylib) into a process.' This uses a specific verb and resource, and the word 'file' distinguishes it from the sibling tool frida_inject_library_blob. The purpose is unambiguous and well-aligned with the tool name.

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 description implies the primary use case (injecting a library from a path) but does not explicitly mention when to use this tool over alternatives like frida_inject_library_blob or frida_inject. There is no exclusionary guidance or alternative comparison, so the agent is left to infer from the name and context.

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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