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

Annotations already declare readOnlyHint=true, destructiveHint=false and openWorldHint=false, so the safety profile is covered by structured data. The description adds that it returns a recommended design plus rationale, which is useful, but says nothing about how it handles ambiguous questions, whether the recommendation is advisory-only, or how the optional feasibility input alters the output. With annotations doing the heavy lifting, this is adequate but thin.

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 pipe-delimited USE WHEN / ALIASES / RETURNS structure is front-loaded and scannable, and every section serves tool selection or disambiguation. The alias block is long (eight phrases, bilingual), which is functional for matching but is the bulkiest part of the definition.

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?

For a two-parameter, read-only advisory tool with no output schema, the definition supplies the trigger condition, the design space, and the shape of the return value. What is missing is minor: how the optional feasibility input changes the recommendation and what to do when the question is under-specified.

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 both 'pico' and 'feasibility' are already documented in the schema. The description adds no syntax, format, or example guidance for either parameter and never mentions them directly, so the schema carries the full burden. Baseline 3 applies.

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 names the specific resource (study design selection) and enumerates the candidate designs it chooses between (RCT / cohort / case-control / cross-sectional / diagnostic accuracy), which lets an agent distinguish it from analysis-oriented siblings like survival_cox or roc_auc. It does not explicitly differentiate from adjacent planning tools such as pico_refine or sample_size_calculator, keeping it short of a 5.

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 'USE WHEN' clause gives a clear triggering condition: the user has a research question but no design chosen. That is actionable context, but there are no exclusions or named alternatives for the case where the design is already fixed (e.g., 'use sample_size_calculator once the design is decided').

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