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

Annotations already cover the safety profile (readOnlyHint=true, destructiveHint=false, openWorldHint=false), so the description only needs to add context. It does: the scope is organization-wide, the result set includes people, AI agents and teams, and the returned identifiers are the exact ones the mutation tools accept — meaningful return-shape disclosure in the absence of an output schema. It omits pagination/result-size behavior.

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 with no filler and a front-loaded subject, but the first sentence is malformed ('Everyone in this organization a to-do can be assigned to ... and its teams'), which forces a re-read to parse the relationship between people and teams. Efficiency is good; readability is not.

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?

For a zero-parameter, read-only list tool with no output schema, the description supplies the essentials an agent needs: organizational scope, the entity types returned, and how the identifiers are consumed downstream. Minor gaps remain around whether inactive people are included and result size, but nothing blocks correct invocation.

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, so there is nothing for the description to disambiguate; baseline 4 applies. The description does not need to explain any inputs, and it does not waste words doing so.

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 names a specific resource (everyone in the organization plus teams and AI agents) and its role as the source of assignee identifiers. It ties itself to specific siblings (add_todo, update_todo), which distinguishes it from list_todos, list_rocks and the other list_* tools. The garbled opening clause ('Everyone in this organization a to-do can be assigned to') costs it a perfect score.

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?

'Use it to put each action item on the person who owns it' plus the explicit mention that add_todo and update_todo consume the identifiers gives a clear context of use: call this before assigning a to-do. No explicit exclusions or when-not guidance are offered, so it falls short of a 5.

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