get_most_called_functions

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 doesn't reveal critical traits: whether it's read-only or has side effects, what data source it queries (e.g., static analysis vs. runtime), how it handles ties in frequency, or if there are rate limits. For a tool with zero annotation coverage, 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.

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

The description is a single, efficient sentence with zero waste. It's front-loaded with the core purpose and uses clear language. Every word earns its place, making it easy to parse quickly without unnecessary elaboration.

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 analyzing function calls and the lack of annotations and output schema, the description is incomplete. It doesn't explain what 'most frequently called' means (e.g., based on static analysis, runtime data, or historical usage), the format of the return value, or any prerequisites. For a tool with rich sibling context and no structured output, more detail is needed to be fully helpful.

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 the 'limit' parameter clearly documented. The description doesn't add any parameter-specific details beyond what the schema provides, such as typical use cases for the limit or constraints on its values. With high schema coverage, the baseline score of 3 is appropriate as the description doesn't compensate but also doesn't 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 clearly states the verb 'Get' and the resource 'most frequently called functions', making the purpose evident. It distinguishes from siblings like 'get_function_callees' or 'get_function_callers' by focusing on frequency ranking rather than direct call relationships. However, it doesn't specify the scope (e.g., within a module, project-wide) which could further differentiate it.

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. With many sibling tools like 'get_function_call_graph', 'analyze_function_complexity', and 'get_code_statistics', there's no indication of whether this is for performance analysis, debugging, or code review. It lacks explicit when/when-not instructions or named alternatives.

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