get_user_summary

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 effectively describes the tool's behavior by specifying what data is returned (UserSummary object with detailed fields), its purpose for evaluation, and its efficiency advantage over fetching individual histories. However, it doesn't mention potential limitations like rate limits or authentication needs.

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 well-structured and front-loaded, starting with the core purpose, followed by parameter and return details, and ending with usage guidelines. Every sentence adds value without redundancy, making it efficient and easy to parse.

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 moderate complexity, no annotations, and the presence of an output schema (implied by the Returns section), the description is complete. It covers purpose, parameters, return values, and usage context adequately, leaving no significant gaps for an AI agent to understand and invoke the tool correctly.

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 100%, so the baseline is 3. The description adds value by reiterating the parameter's purpose ('The user's handle') and noting it's case-insensitive, which provides useful context beyond the schema's basic documentation, though it doesn't introduce new parameter details.

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 ('Fetch') and resource ('comprehensive summary of a user's profile'), distinguishing it from siblings like get_user_badges or get_user_topics by emphasizing it provides a holistic overview rather than specific data points.

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 explicitly outlines when to use this tool ('to evaluate credibility, find valuable contributions, understand participation level') and distinguishes it from alternatives by noting it provides 'a quick overview without fetching individual post histories,' which helps differentiate it from more granular sibling tools.

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