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

Annotations already mark the operation read-only and idempotent. The description adds valuable behavior: the response is split into two groups, duplicate names resolve to the team influencer by default, and the useful fields are name, influencerId, and sessionId. No contradiction with annotations.

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 sentences, each earning its place: scope/grouping, downstream usage, and duplicate-name resolution. The key purpose is front-loaded, and the disambiguation rule is placed at the end.

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?

Given a zero-parameter read-only tool with no output schema, the description covers everything needed to invoke and use the result: the grouping, the field names to consume, and the ambiguity rule. There is no missing prerequisite, alternative, or side effect the agent would need.

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 has zero parameters, and the schema fully documents that with 100% coverage, so there is no parameter burden for the description to carry. Nothing more is needed.

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 the exact resource ('every identity connected to this workspace') and a specific verb ('List'), then defines the two groups returned (team influencers and the user's own LinkedIn accounts). This clearly distinguishes it from sibling list tools such as list_teams or list_brand_profiles.

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 clear downstream context: the returned name, influencerId, or sessionId are meant to be passed as the `profile` argument of other tools, and team influencers are the usual target for content plans. It does not explicitly name alternative tools or exclusion conditions, so it stops short of full when/when-not guidance.

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