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

Annotations already declare readOnlyHint=true, destructiveHint=false and openWorldHint=false, so safety is covered; the description adds genuinely new behavior — the null-when-uncomputed state and the fact that the compute sibling requires 30+ responses and 2+ numeric questions. It does not add auth or rate-limit context, so not a 5.

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?

Two sentences, front-loaded with the core definition of what the resource is and followed by the return shape and the null/compute escape hatch. No filler, every clause earns its place.

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-shape burden and does so: it spells out segment fields, the null case, and where to go when segments are missing. For a simple two-parameter read tool, nothing an agent needs to call it correctly is missing.

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 only 50%: 'workspace' is fully documented in the schema while 'studyId' has none. The description mentions no parameters at all, so it does not compensate for the undocumented studyId; studyId is self-evident by name, keeping this at the baseline rather than lower.

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+resource ('the stored k-means segmentation over the study's numeric answers') and enumerates what is returned (named segments with size, share, and distinguishing features). It is clearly distinguished from the sibling prism_studies_segments_compute, which it names explicitly.

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 a concrete condition and routes the agent to the alternative: null when nothing is computed yet, and prism_studies_segments_compute is what discovers them (with its 30+ responses / 2+ numeric questions prerequisites). It stops short of an explicit 'use this to read existing segments' statement, but the routing is unambiguous.

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