meta_ad_insights

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

With no annotations, the description carries the full burden. It discloses one key behavioral trait: data is conditional on running ads. However, it does not mention authentication requirements, rate limits, or what happens if no ads exist (e.g., empty response). This is moderate transparency.

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 one short sentence plus a caveat, which is concise and front-loaded with the essential info. Every word earns its place. Slightly more structure (e.g., bullet points) could improve readability but not necessary.

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 no output schema, the description should hint at the return format (e.g., array of objects, nested structure). It does not, leaving the agent guessing. Also, with many sibling tools, more context on when to use this specific one would improve completeness.

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 75%, so the schema already documents most parameters. The description lists metrics but does not add meaning beyond the field defaults. For example, it does not explain how level affects the response. Baseline 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 clearly states it returns ad account insights with specific metrics (impressions, clicks, spend, etc.), which distinguishes it from sibling tools like meta_page_insights or meta_list_campaigns. However, it could be more explicit about the level parameter allowing campaign/adset/ad granularity, not just account-level.

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 only usage guidance is that data is returned only if Meta ads are run. No mention of when to use this tool versus alternatives like meta_graph or meta_list_campaigns. The description lacks context on prerequisites or typical scenarios.

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