meta_ads_split_tests_create

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

No annotations are provided, so the description carries full burden. It discloses that the tool is mutating, reversible via rollback_apply (with behavior explanation), and describes Meta's runtime behavior (compares cells on chosen objective after configured duration). This provides sufficient transparency for an agent to understand side effects.

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 four sentences with no fluff. The first sentence immediately states the action and return value. Subsequent sentences are each informative and front-loaded. Every sentence earns its place without redundancy.

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 and 8 parameters (6 required), the description covers creation process, behavioral context, reversibility, and links to a sibling tool. It lacks explicit mention of error handling or return format beyond study_id, but for a creation tool with clear parameters, this is sufficiently 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 100%, so baseline is 3. The description goes beyond the schema by adding context: cells require pre-existing ad sets, Meta splits traffic evenly; objectives produce multi-dimensional results; start_time must be future; end_time requires at least 4 days; confidence_level default 95 with trade-offs. This adds meaningful value for parameter understanding.

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 creates a new Split Test and returns its study_id. It distinguishes the tool from related siblings like meta_ads_split_tests_get (for post-conclusion analysis) and mentions it does not create ad sets. The verb 'Creates' and resource 'Split Test' are specific and unambiguous.

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?

Explicitly provides when-to-use (creating a split test) and when-not-to-use (for analysis, use meta_ads_split_tests_get). It also specifies prerequisites (cells must reference pre-existing ad sets) and notes reversibility via rollback_apply. This gives clear guidance on selecting this tool over alternatives.

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