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

Annotations already establish read-only, idempotent, and non-destructive behavior. The description adds useful context about actor scoping and the compact output nature, which goes beyond the annotation fields and helps the agent predict what the call will return.

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, front-loaded sentence with no filler. Every phrase contributes meaning: action, resource, actor scope, and output shape.

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 simple, optional-parameter listing tool, this may be minimally usable without further detail. Still, the lack of any parameter descriptions and the absence of an output schema leave meaningful gaps about filtering behavior and the exact structure of the returned data.

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 0%, so the description must compensate for the undocumented limit, status, and symbol parameters. It only vaguely references 'scope fields' and 'compact counts,' which does not clearly explain what each parameter controls or how they should be used.

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 a specific action (list), a concrete resource (case studies), and a distinguishing scope ('for the configured actor user'). It also hints at the returned shape ('compact counts and scope fields'), which separates it from sibling tools like ata_load_case_study.

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 makes it clear that this tool is for listing case studies, so the basic use case is implied. However, it does not explicitly say when to prefer this over related tools such as ata_list_resources or ata_load_case_study, nor does it state any exclusions.

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