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

No annotations are provided, so the description carries the full burden. It explicitly describes the output content: the scoring methods, normalization details, and usage guidance. The verb 'List' implies a non-destructive, read-only operation, which is appropriate. No side effects or requirements are mentioned, but for a basic informational tool, this is sufficient.

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 sentence that front-loads the verb 'List' and immediately specifies the exact methods and the type of information included. Every word contributes value, and the sentence is well-structured and concise.

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 simplicity—no parameters, no output schema—the description completely specifies what the agent will receive: the three scoring methods with normalization details and when to use each. This is fully sufficient for correct invocation and understanding.

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 tool has zero parameters, and the schema is an empty object. The description redundantly states 'No parameters,' which is harmless but adds no new semantic meaning. According to the baseline for 0 params, a score of 4 is appropriate.

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 'List the scoring methods' with a specific verb and resource, and explicitly names the three methods (weighted_sum, weighted_product, topsis). This distinguishes it from sibling tools like decide_score or decide_compare_two, which likely perform scoring or comparison rather than listing methods.

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 says 'with normalization details and when to use each,' which provides guidance on method selection. However, it does not explicitly state when to use this list tool versus other decision tools, such as decide_score or decide_compare_two. The purpose is clear enough to infer usage, but it lacks an explicit alternative or exclusion statement.

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