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

Annotations already establish readOnlyHint, idempotentHint, and openWorldHint, covering safety and idempotency. The description adds valuable behavioral context beyond annotations by specifying the exact fields returned (objective, type, status) and the practical follow-up (using campaign IDs for scoped analysis). It does not disclose potential pagination or edge cases, but the annotation coverage keeps the bar lower, making this a strong addition.

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 two tight sentences with zero filler. The primary action and scope are front-loaded, and the second sentence adds a useful scoping hint. Every word earns its place.

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 low-complexity list tool with two parameters and no output schema, the description explains what fields will be returned (objective, type, status) and how the results can be used. It does not mention pagination or size limits, but given the read-only, idempotent, open-world annotations and the simplicity of the operation, the missing details are not critical. The description overall enables correct invocation and interpretation.

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 coverage is 100%: both 'profile' and 'ad_account_id' have descriptive schema entries explaining their sources and defaults (e.g., 'Omit to use the first ad account'). The tool description adds no extra meaning to the parameters themselves. With full schema coverage, the baseline of 3 is appropriate.

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 specifies the exact verb ('List'), the resource ('campaigns in a LinkedIn ad account'), and the returned attributes ('objective, type and status'). This clearly distinguishes it from siblings like list_ad_accounts (accounts vs campaigns) and get_ad_creatives (creatives vs campaigns), even without naming them explicitly.

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 implies a usage context by saying 'Use campaign ids to scope ads analysis to one campaign,' which tells the agent why it might want the output. However, it does not explicitly state when to use this tool versus alternatives, nor does it name any exclusions such as 'use get_ads_performance for metrics' or 'use list_ad_accounts for account-level listing.' The guidance is implied rather than explicit.

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