Frida MCP Server

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

With no annotations provided, the description carries the full burden of behavioral disclosure. It mentions the action ('Call a native function') but lacks critical details: it doesn't specify if this is a read-only or destructive operation, what permissions or session states are required, potential side effects (e.g., crashing the target process), error handling, or return format. For a low-level tool with no annotation coverage, this is a significant gap.

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

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

The description is extremely concise and front-loaded: two sentences that directly state the tool's core functionality and key parameters. There is no wasted language, and every word contributes to understanding the tool's purpose and basic usage.

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

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

Given the tool's complexity (low-level native function calling), lack of annotations, and no output schema, the description is incomplete. It doesn't cover behavioral risks, session dependencies, error scenarios, or output structure, leaving critical gaps for safe and effective use. The high schema coverage helps with parameters but doesn't compensate for missing operational context.

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

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

The description adds minimal value beyond the input schema, which has 80% coverage. It mentions 'Specify return type and argument types,' which aligns with the schema's 'return_type' and 'arg_types' parameters but doesn't provide additional context like type syntax examples or validation rules. With high schema coverage, the baseline is 3, and the description doesn't significantly enhance parameter understanding.

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

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

The description clearly states the tool's purpose: 'Call a native function directly by address or name.' It specifies the verb ('Call') and resource ('native function'), and distinguishes it from siblings like frida_hook_function or frida_trace by focusing on direct invocation rather than interception or tracing. However, it doesn't explicitly differentiate from frida_java_call_method or frida_objc_call_method, which are higher-level language-specific tools.

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

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 doesn't mention prerequisites (e.g., requiring an active Frida session), compare it to siblings like frida_hook_function for hooking instead of calling, or specify scenarios where direct native function calls are appropriate (e.g., low-level debugging vs. high-level scripting).

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.