meta_ads_split_tests_create

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

With no annotations, the description fully carries the behavioral burden. It explicitly states the tool is mutating and not automatically reversible, and explains how Meta runs the test (compares cells on objectives). However, it does not disclose potential error states or rate limits, leaving some gaps.

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 concise at 4 sentences, front-loaded with the core action and return. It efficiently includes mutation warning and key details. Minor redundancy (e.g., 'Meta runs the test...' could be slightly tighter), but overall well-structured.

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 complexity (8 params, no output schema), the description covers the tool's purpose, return value, prerequisites (ad sets), duration constraints, objectives, and rollback guidance. It also directs to the analysis tool. This provides sufficient context for an agent to use it correctly.

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%, but the description adds substantial meaning: it explains the purpose of objectives (with enum values), cells structure, confidence_level default and range, start_time must be in future, end_time minimum duration, and account_id fallback. This greatly aids parameter understanding beyond the schema.

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 the study_id. It distinguishes itself from sibling tools like meta_ads_split_tests_get (for analysis) and clarifies it does not create ad sets, which is a key differentiation.

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 explicit guidance: it notes cells must reference pre-existing ad sets (prerequisite), explains when to use (to create a test) and when not (for analysis use meta_ads_split_tests_get), and advises recording before-state for rollback. This covers when, when-not, and alternatives.

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