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

Annotations already cover read-only and non-destructive behavior, so the bar is lower. The description adds valuable non-obvious context: it does not consume billing, empty queries list all accounts, and results are limited to a specific shape. This goes beyond what the annotations alone provide.

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?

The description is compact, front-loads the core purpose, and every sentence adds useful information: scope, empty-query behavior, safety/billing, return format, and the next step. No filler or redundancy is present.

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 the single optional parameter, annotations, and the included output format, the description is fully adequate for an agent to select and invoke the tool correctly. It even provides cross-tool guidance to `fetch`, making the workflow 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?

Schema description coverage is 0%, so the description must carry parameter meaning. It effectively explains the sole `query` parameter by stating that matching accounts are returned and that an empty query lists all connected accounts. This is sufficient for the single optional parameter.

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 clearly states a specific verb ('Searches') and resource ('connected ad accounts' from Google, Meta, LinkedIn) and defines the return as matching accounts. It is unambiguous about what the tool does, though it does not explicitly distinguish itself from sibling tools like list_accounts or search_tools.

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?

The description provides clear context for when to use the tool: search or list connected ad accounts, including the empty-query behavior. It also routes the agent to `fetch` for details, but it does not explicitly state when not to use this tool or name alternatives such as list_accounts.

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