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create_async_report

Generate large-scale Meta Ads insight reports asynchronously. Submit fields, breakdowns, and date presets to obtain a report_run_id for polling results.

Instructions

Create an async insight report for large data queries. Returns a report_run_id to poll with get_async_report.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
fieldsNoComma-separated insight fieldsimpressions,clicks,spend,reach,frequency,cpc,cpm,ctr,actions,cost_per_action_type
breakdownsNoBreakdown dimensions: age,gender,country,region,placement,device_platform
date_presetNoDate preset: TODAY,YESTERDAY,LAST_7D,LAST_14D,LAST_30D,THIS_MONTH,LAST_MONTH,THIS_QUARTER,LAST_QUARTER,THIS_YEAR,LAST_YEAR
time_rangeNoJSON string {since,until} in YYYY-MM-DD format
time_incrementNoTime granularity: all_days, 1, 7, monthly
filteringNoJSON string for filtering
levelNoAggregation level: campaign, adset, ad
Behavior3/5

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

With no annotations provided, the description carries the full burden. It conveys the async nature and the need to poll, but does not disclose auth requirements, rate limits, or whether it is destructive (likely not). This is adequate but not comprehensive.

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?

Two short, front-loaded sentences with no extraneous information. Every word earns its place.

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?

The description covers the purpose and return value, and references the polling sibling. Given 7 well-described parameters and no output schema, it is fairly complete. Minor gap: lacks mention of any constraints or limits.

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

Parameters3/5

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 itself does not add any additional parameter semantics beyond what the schema already provides. The schema descriptions are good, so no deduction.

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?

The description clearly states it creates an async insight report for large data queries, and specifies it returns a report_run_id for polling via get_async_report. This distinguishes it from other sibling tools that may be synchronous or for other purposes.

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?

The description indicates the tool is for large data queries, implying it is for heavy workloads. It explicitly mentions polling with get_async_report, providing a clear usage flow. However, it does not explicitly contrast with synchronous insight tools like get_ad_insights, leaving some ambiguity about when to use this vs. those.

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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