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

Annotations already carry readOnlyHint/destructiveHint/openWorldHint, so the safety profile is covered. The description adds genuine behavioral context the annotations do not: result ordering (newest first), that all study origins are included, and the shape of each returned row. It stops short of describing volume/pagination behavior, so it is strong but not exhaustive.

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 tightly packed sentences: scope and returned fields front-loaded, then the routing sentence. No filler, and every clause carries selecting information.

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?

There is no output schema, so the description usefully enumerates what each row contains (title, question count, response count, state, owning field/node/series). Combined with the sibling routing, an agent has everything needed to select and call it correctly.

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?

With a single parameter at 100% schema description coverage, the schema already explains the workspace slug, default-workspace behavior, and API-key exception. The description adds nothing about the parameter, so the baseline 3 is correct.

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?

Specific verb+resource+scope: lists ALL studies in the workspace regardless of origin (standalone, canvas-node, series waves), and even names the concrete fields returned. It draws an explicit boundary against prism_studies_list (per-node view) and prism_research_digest (findings view), so an agent can distinguish it 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?

Explicitly frames itself as the starting point for 'which studies do we have?' and routes onward: prism_studies_list for per-node, prism_research_digest for findings, prism_studies_get to read one. Both the when-to-use condition and the alternatives are stated outright.

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