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pinterest_run_conversion_product_report

Run Pinterest conversion product reports by brand, category, SKU, or SKU group to analyze checkout metrics and ROAS across campaigns.

Instructions

Run Pinterest async conversion product reporting by brand, category, brand+category, SKU, or SKU group via reports/brand_category_sku.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
levelNoCAMPAIGN
limitNo
columnsNo
endDateYes
startDateYes
adGroupIdsNo
reportNameNoPinterest Conversion Product Report
adAccountIdNo
campaignIdsNo
granularityNoTOTAL
productSkuIdsNo
viewWindowDaysNo
clickWindowDaysNo
conversionReportTimeNoTIME_OF_AD_ACTION
conversionProductBreakdownNoPRODUCT_BRAND_AND_CATEGORY
conversionProductAttributionTypeNoDEFAULT
Behavior2/5

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

The description discloses that the report is 'async' and names the API endpoint, which are useful behavioral signals. However, with no annotations and no output schema, it does not explain what the tool returns, whether it merely submits a job that must be polled, what side effects occur, or any rate or data limits.

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?

The description is a single sentence with an active verb up front, no filler, and the key scoping information placed early. Every word contributes to understanding the tool's core action and object.

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

Completeness1/5

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

This is a 16-parameter async report tool with no annotations, no output schema, and no parameter coverage in the schema description. The one-sentence description does not explain required inputs, how to specify an ad account, how results are retrieved, or how this tool fits among the many run_* and validate_report siblings, making it far from complete.

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

Parameters2/5

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

Schema description coverage is 0%, so the description must compensate for the 16 parameters. It adds meaning for the `conversionProductBreakdown` parameter by listing brand, category, brand+category, SKU, and SKU group, but it says nothing about required dates, ad account, filters, windows, granularity, columns, or attribution, leaving most parameters unexplained.

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

Purpose4/5

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

The description states a specific verb ('Run'), a clear resource ('Pinterest async conversion product reporting'), and names the breakdown dimensions plus the API endpoint. It is clearly differentiated from generic reporting by the 'conversion product' focus, though it does not explicitly distinguish itself from sibling report tools like pinterest_run_catalog_report or pinterest_run_targeting_report.

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?

There is no guidance on when to choose this tool over the many sibling report tools, no mention of prerequisites such as an ad account ID, and no exclusions or alternative names. The usage context is only implied by the name and the phrase 'conversion product reporting.'

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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