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meta_ads_split_tests_create

Create a split test in Meta Ads to compare ad sets on objectives like cost per result, conversions, reach, CPC, or CPM. Configure cells, duration, and confidence level to determine a winner.

Instructions

Creates a new Split Test. Returns the new study_id. Mutating, reversible via rollback_apply (rollback ends the test immediately without declaring a winner). Meta runs the test for the configured duration, then compares cells on the chosen objective (COST_PER_RESULT / CONVERSIONS / REACH / CPC / CPM). Cells must reference pre-existing ad sets; this tool does not create ad sets. For test analysis post-conclusion use meta_ads_split_tests_get.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
account_idYesMeta Ads account ID in the format 'act_XXXXXXXXXX' (e.g. 'act_1234567890'). Optional — falls back to META_ADS_ACCOUNT_ID from the configured credentials. The leading 'act_' prefix is required.
nameYesTest name shown in Experiments. Should describe the hypothesis being tested.
cellsYesTest cells (2 or more). Each cell has {name, adsets: [ad_set_id, ...]}. Meta splits traffic evenly across cells.
objectivesYesMetrics Meta will use to rank cells. Each entry is {type: COST_PER_RESULT | CONVERSIONS | REACH | CPC | CPM}. Multiple objectives produce multi-dimensional results.
start_timeYesTest start in ISO 8601 (e.g. '2026-04-25T00:00:00+0900'). Must be in the future when the test is created.
end_timeYesTest end in ISO 8601. Meta requires at least 4 days between start_time and end_time for statistical significance.
confidence_levelNoStatistical confidence threshold for declaring a winner. Default 95 (95%). Higher values need more spend / longer duration to conclude.
descriptionNoFree-text description of the hypothesis. Internal — not shown to end users.
Behavior4/5

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

Describes mutability ('reversible via rollback_apply'), test mechanism (duration, objective comparison), and cell requirements. Lacks permission or rate limit info, but with no annotations, it covers key behavioral aspects well.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

Five sentences, front-loaded with action and return value. Each sentence adds unique, useful information without redundancy.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness4/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Covers main purpose, return, mutability, prerequisites, and test mechanics. Lacks error handling or rate limits, but for a creation tool with no output schema, it is fairly complete.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters4/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 100% with good descriptions. Description adds value by explaining cell prerequisites, rollback behavior, and default confidence level, which are not in the schema.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

Clearly states 'Creates a new Split Test' and returns 'study_id'. Distinguishes from siblings by mentioning rollback_apply and referencing meta_ads_split_tests_get for analysis.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines4/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

Provides clear prerequisites ('cells must reference pre-existing ad sets') and post-analysis guidance ('use meta_ads_split_tests_get'). Could be more explicit about when to use versus other split test tools, but still good context.

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

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