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

Annotations already declare readOnly, non-destructive, closed-world, so safety is covered. The description adds real value beyond them by describing aggregate content (response counts, theme counts, desk-research presence) and a scope caveat that interviews are now study-level. It omits pagination/limits, which is a minor gap for a list tool.

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?

Front-loads the returned content before the caveat and the usage directive, so an agent gets the gist on the first clause. Two nested parentheses make it slightly dense, but nothing is wasted.

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 burden of explaining return shape and does so concretely (studies, response counts, theme counts, desk-research flag). Combined with rich read-only annotations, it is nearly complete; only pagination and result limits are unaddressed.

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 coverage is 100%, so subjectId, subjectType, and workspace are fully documented in the schema itself. The description only implies the subject is a Prism node, matching the enum, and adds nothing on workspace scoping. Baseline 3 is appropriate when the schema does the heavy lifting.

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 resource and scope ('Cross-instrument findings for one subject') and enumerates the payload an agent gets — attached feedback studies with response and theme counts plus desk-research existence. It also disambiguates from a sibling by name ('Interviews are study-level now — read them per study with prism_interviews_list').

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 explicit when-to-use ('THE PLACE TO LOOK before proposing new research: cite what already exists') and routes one class of question away to prism_interviews_list. Both the selection condition and an alternative are spelled out rather than inferred.

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