Frida MCP Server

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

No annotations are provided, so the description carries the full burden of behavioral disclosure. It states what the tool does but lacks critical behavioral details: it doesn't mention that this is a read-only operation (safe for enumeration), doesn't describe the return format (e.g., list of class names or objects), and doesn't cover potential side effects like performance impact or session requirements. The description is minimal and misses key operational context.

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—a single sentence that directly states the tool's function. It's front-loaded with the core action and includes relevant platform context. There's no wasted verbiage, making it efficient for quick understanding.

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 (enumeration in a dynamic analysis context), lack of annotations, and no output schema, the description is incomplete. It doesn't cover behavioral aspects like safety, return format, or session dependencies, which are crucial for an AI agent to use it correctly. The minimal description leaves significant gaps in understanding how the tool operates.

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?

Schema description coverage is 50% (only 'pattern' has a description). The description adds no parameter-specific information beyond what's implied by the tool name (e.g., 'session_id' is required for Frida operations). It doesn't explain parameter usage, such as how 'pattern' filters classes or what format 'session_id' should be. With moderate schema coverage, the description provides minimal additional value.

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 with a specific verb ('Enumerate') and resource ('all loaded Objective-C classes'), and specifies the target platforms ('iOS/macOS'). However, it doesn't explicitly differentiate from sibling tools like 'frida_java_enumerate_classes' or 'frida_list_modules', which serve similar enumeration purposes for different targets.

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 sibling tools like 'frida_java_enumerate_classes' for Java classes or 'frida_list_modules' for module enumeration, nor does it specify prerequisites such as needing an active Frida session. Usage context is implied but not explicit.

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