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

Annotations already declare readOnlyHint, idempotentHint and destructiveHint=false, and the description still adds high-value behavioral context: archived/expired audiences silently delivering 0 members, the `below_delivery_minimum` flag against LinkedIn's ~300-member floor, and that this state is only visible here. This goes well beyond the annotation layer.

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?

Dense but front-loaded: purpose first, then the field list, then the CRITICAL warning. Every sentence carries operational weight, though the parenthetical enumeration of audience subtypes is slightly list-heavy for the space it consumes.

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?

Output schema exists so return values need not be re-explained, yet the description still surfaces the exact fields an agent needs (`urn`, `usable_for_targeting`, `below_delivery_minimum`) and the pagination behavior. Nothing required to call or interpret this tool 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?

Only one parameter (account_id) with 0% schema description coverage, but the description's framing as 'a LinkedIn account's matched audiences' makes the required account scope unambiguous, and the sibling field mention (`urn` for update_linkedin_campaign_targeting) clarifies downstream usage. A single self-evident identifier param needs little more.

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 (Lists) and resource (LinkedIn matched audiences), enumerates the audience subtypes it covers, and names the sibling it feeds into (update_linkedin_campaign_targeting). An agent can distinguish it from list_audiences, list_meta_audiences, list_tiktok_audiences and list_microsoft_audiences 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 instructs the agent to check `usable_for_targeting` BEFORE building a retargeting/ABM campaign and explains why (archived/expired audiences resolve to 0 members and stop delivery). This is actionable when-to-use guidance tied to a named downstream workflow.

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