analyze_campaign_ads

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

No annotations are provided, so the description carries the full burden. It mentions that the tool 'Returns performance scores and recommendations,' which gives some behavioral insight. However, it lacks critical details: whether this is a read-only operation, if it triggers background processing, potential rate limits, authentication requirements, or error conditions. For a tool with 4 required parameters and no annotation coverage, this is insufficient.

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 highly concise and front-loaded: the first sentence states the core purpose and output, while the second provides essential usage notes. Every sentence adds value without redundancy. At 3 sentences total, it's appropriately sized for the tool's complexity.

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 tool has an output schema (which covers return values), the description doesn't need to explain outputs. However, with 4 required parameters, 0% schema coverage, and no annotations, the description should do more to compensate. It provides basic purpose and some parameter guidance but lacks behavioral transparency and complete parameter semantics, making it minimally adequate but with clear gaps.

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 compensate. It adds meaning for campaign_id ('comes from list_campaigns') and date parameters ('Dates in YYYY-MM-DD format'), which covers 3 of 4 parameters. However, account_id is entirely undocumented in both schema and description, leaving a significant gap. The description provides partial but incomplete parameter semantics.

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 the tool's purpose: 'Run AI analysis on all ads in a campaign. Returns performance scores and recommendations.' This specifies the verb ('Run AI analysis'), resource ('all ads in a campaign'), and output type. However, it doesn't explicitly differentiate from siblings like analyze_account_ads or analyze_single_ad, which would require a 5.

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 some usage context: 'campaign_id comes from list_campaigns' implies a prerequisite tool and 'Dates in YYYY-MM-DD format' specifies date formatting. However, it doesn't explicitly state when to use this tool versus alternatives like analyze_account_ads or analyze_single_ad, nor does it mention exclusions or specific scenarios. This is implied guidance rather than explicit.

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