set_function_prototype

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. 'Set' implies a mutation operation, but the description does not specify whether this change is reversible, requires specific permissions, affects other parts of the system, or has side effects (e.g., breaking existing calls). It lacks details on error conditions, rate limits, or response format, leaving significant gaps in understanding the tool's behavior.

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 a single, direct sentence with zero wasted words. It is front-loaded and efficiently conveys the core action without unnecessary elaboration, making it easy to parse quickly. This is an example of optimal conciseness for a simple tool.

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 complexity of a mutation tool with no annotations and no output schema, the description is incomplete. It does not explain what a prototype is, what the tool returns, potential errors, or how it interacts with other tools (e.g., 'get_function_by_address'). For a tool that modifies function data, more context is needed to ensure safe and correct usage by an agent.

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 input schema has 100% description coverage, with clear titles and descriptions for both parameters ('function_address' and 'prototype'). The description does not add any meaning beyond the schema, such as explaining the format of the address or prototype syntax. Since the schema is well-documented, a baseline score of 3 is appropriate, as the description does not compensate but also does not detract.

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 'Set a function's prototype' clearly states the action (set) and target (function prototype), which is adequate. However, it lacks specificity about what a 'prototype' entails in this context (e.g., function signature, parameters, return type) and does not distinguish this tool from potential siblings like 'rename_function' or 'set_global_variable_type', which also modify function-related data. It avoids tautology but remains vague.

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 does not mention prerequisites (e.g., needing a valid function address), exclusions, or related tools like 'get_function_by_address' for verification. Without such context, an agent must infer usage from the tool name alone, which is insufficient for effective selection.

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