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by qalvinahmad

Petal Ads report

petal_report
Read-onlyIdempotent

Query Huawei Petal Ads reporting API to retrieve monetization data such as earnings, ad requests, impressions, and rates. Supports grouping by country, app, placement, or ad type, with filters and pagination.

Instructions

Query the Huawei Petal Ads Publisher Service Reporting API with full control over grouping, filtering, ordering, and pagination. Returns monetization data (earnings, ad requests, impressions, clicks, match/show/click rates).

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
rawNoReturn the raw API JSON instead of a formatted table
pageNoPage number (default 1)
app_idsNoFilter to specific Petal Ads app IDs
ad_typesNoFilter to specific ad formats
currencyNoReport currency: CNY, USD, or EUR (default USD)
end_dateNoEnd date in YYYY-MM-DD (defaults to start_date)
group_byNoBreakdown dimensions, e.g. STAT_BREAK_DOWNS_APP_ID
countriesNoFilter to country codes, e.g. ["ID", "US"]
page_sizeNoRows per page (default 50, max 1000)
order_typeNoOrder direction
start_dateYesStart date in YYYY-MM-DD
order_fieldNoField to order by
placement_idsNoFilter to specific ad placement IDs
time_granularityNoTime granularity (default STAT_TIME_GRANULARITY_DAILY)
Behavior4/5

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

Annotations indicate readOnlyHint=true, idempotentHint=true, and destructiveHint=false. The description consistently describes a query operation (query, returns). It adds context about the API and metrics returned, which is useful beyond the annotations.

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 sentences front-load the purpose and capabilities. No redundant information. Every word adds value.

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?

Given 14 parameters with full schema descriptions and annotations indicating read-only behavior, the description covers the tool's purpose and output. It could mention pagination or rate limits, but the parameters (page, page_size) address pagination implicitly. Minor gap for completeness.

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 coverage is 100% with all parameters described. The description provides a high-level overview but does not add new meaning beyond the schema. Baseline 3 is appropriate as the schema carries the detail.

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 the tool queries the Huawei Petal Ads reporting API with control over grouping, filtering, ordering, and pagination. It specifies the resource (reports), action (query), and expected return values (monetization data including earnings, impressions, clicks, rates). This distinguishes it from siblings like petal_apps_performance and petal_revenue_summary.

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

Usage Guidelines2/5

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

No guidance on when to use this tool versus alternatives such as petal_apps_performance or petal_revenue_summary. The description implies full control but does not explicitly state contexts where this tool is preferred or when not to use it.

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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