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

Annotations already cover the safety profile (readOnlyHint, idempotentHint, destructiveHint=false, openWorldHint=false), so the lower bar applies. The description adds useful context that the result joins clients to their linked data sources, but says nothing about result size, pagination, or what an agency with no clients returns.

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, no filler. The primary action is front-loaded in the first clause and the routing guidance follows immediately.

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?

No output schema exists, so the description carries the burden of describing returns; it names both the client list and the linked-source mapping, which is the essential shape. It could note ordering or scale limits, but for a zero-param read starting point this is close to complete.

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 no parameter semantics to explain and the baseline of 4 applies. The description correctly implies the result is unfiltered (all of this agency's clients).

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 and resource ('List this agency's clients') plus a second facet: which data sources are linked to each. That scope is distinguishable from platform-scoped siblings like meta_list_accounts or ads_list_accounts, though it never names those alternatives directly.

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?

'Start here for any question about a named business rather than a platform' gives an explicit entry-point condition and an implicit exclusion (platform-specific queries go elsewhere). It stops short of naming the specific sibling tool an agent should fall back to for platform questions, but the routing logic is clear.

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