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

Annotations already declare readOnly/openWorld=false, so the safety profile is covered; the description adds real value beyond them by disclosing result ordering ('newest first'), the returned fields, and that draft studies carry no interviewer link until published. It doesn't say whether results are paginated or capped.

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?

Three sentences, front-loaded with the core action and scope, then trigger examples, then the semantic nuance about draft vs published links. Dense but each sentence adds information; the middle sentence is slightly padded with two example phrasings.

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?

With no output schema, the description carries the return-value burden and does so by enumerating returned fields and ordering. What's missing is volume/pagination behavior and whether the list is limited, which matters for an unbounded list tool.

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 takes zero parameters and the schema is empty, so there is nothing for the description to disambiguate. Baseline for a 0-param tool 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?

States a specific verb and resource ('Lists the user's research studies'), names the data source (Frank account), and distinguishes itself from single-record siblings by noting it is the way to find a research ID before looking up interviews. An agent can select this over get_research or list_interviews without opening any schema.

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?

Gives concrete trigger phrases ('what are my researches') and an explicit downstream workflow (find a research ID, then look up its interviews). It doesn't state an explicit when-not or name get_research as the single-record alternative, so it stops short of full routing guidance.

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