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 the full burden. It honestly discloses that the tool is mutating, not automatically reversible, and recommends recording before-state with mureo_state_action_log_append. It also explains Meta's test execution and comparison behavior, going well beyond a simple mutation warning.

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 compact but information-dense, opening with the core purpose and then adding necessary caveats and follow-up guidance. Every sentence earns its place, and the structure flows logically from what → side-effects → prerequisites → next steps.

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's complexity (8 params, 5 required, no output schema), the description fully compensates: it covers creation, return value, side effects, rollback, execution semantics, prerequisites, and post-conclusion workflow. The schema handles parameter specifics, so the description is complete for an agent.

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?

The schema already covers all parameters (100% coverage), but the description adds valuable semantic context: even traffic splitting across cells, the requirement for pre-existing ad sets, and the meaning of confidence_level in terms of spend/duration. This goes beyond the baseline schema-driven 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 opens with a specific verb and resource ('Creates a new Split Test') and clearly states the return value (study_id). It distinguishes itself from sibling tools like meta_ads_split_tests_get/list/end by focusing on creation.

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?

Provides explicit usage context: cells must reference pre-existing ad sets, and analysis after conclusion should use meta_ads_split_tests_get. This gives clear when-to-use guidance and points to the appropriate alternative.

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