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

Annotations already declare readOnlyHint, idempotentHint, and non-destructive behavior, so the safety profile is covered. The description adds genuine context beyond that: how 'agreement' is computed, that similar participant-created category names are grouped, and that participantType=ai resolves to the latest run while human reads completed sessions.

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-loaded with the purpose, then supporting semantics. Every sentence carries information, though the agreement-definition sentence and the return-value enumeration are somewhat long for a tool that already ships an output schema.

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 an output schema present, return values need not be described, yet the description helpfully summarizes them. Combined with annotations covering safety and the participantType semantics, an agent has enough to call this correctly; only permissions/error behavior for non-card-sorting blocks is unstated.

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 carry the load. It fully explains the one non-obvious parameter (participantType default ai, latest run or runId; human reads completed sessions) and implies runId selects a specific run. The remaining three parameters are opaque IDs whose format the description does not elaborate on.

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 opens with a specific verb+resource ('Read results for a Card sorting block') and enumerates the exact payload (categories with agreement, card placements, similarity pairs, participant sorts). No sibling tool returns card-sorting data, so the block-type scoping alone is enough to distinguish it.

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?

Usage is only implied: you call this when you have a card sorting block and want its results. There is no when-to-use/when-not guidance and no routing to alternatives such as get_test_report or get_question_responses. The participantType default/human explanation is parameter behavior rather than tool-selection guidance.

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