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meta_ads_products_get

Fetch a Meta catalog product's full detail to check review_status and rejection reasons when DPA delivery stalls. Diagnose if a product is approved, pending, or rejected to resolve ad issues.

Instructions

Fetches the full detail record for a single catalog product. Returns id, retailer_id, name, description, availability, condition, price, currency, url, image_url, brand, category, review_status (APPROVED / REJECTED / PENDING), and rejection_reasons when applicable. Read-only. Call this when DPA delivery stalls for a specific product to check review_status — rejected products are excluded from ads.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
account_idNoMeta 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.
product_idYesMeta-assigned product_id as returned by meta_ads_products_list (not the retailer_id).
Behavior4/5

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

With no annotations provided, the description carries the full burden. It discloses 'Read-only' behavior, lists enum values for review_status, and explains that rejected products are excluded from ads. It does not mention rate limits or auth needs, but the key behavioral aspects are covered clearly.

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 two sentences, front-loaded with the main purpose and return fields, and the second sentence gives a practical use case. No wasted words; every sentence earns its place.

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

Completeness5/5

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

For a simple get operation with one required parameter and no output schema, the description is comprehensive. It lists all return fields, notes conditional fields, states read-only, and provides a troubleshooting context. This is fully adequate for agent decision-making.

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%, and both parameters have detailed descriptions in the schema. The description does not add parameter-specific details beyond noting that product_id is the Meta-assigned ID and not retailer_id, which is already in the schema. The return field list adds value but not parameter semantics.

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 that it fetches the full detail record for a single catalog product, which is a specific action on a specific resource. It lists the returned fields and differentiates from sibling tools like meta_ads_products_list or meta_ads_products_update by emphasizing 'single' product and 'full detail record'.

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 provides an explicit when-to-use instruction: 'Call this when DPA delivery stalls for a specific product to check review_status.' It gives clear context for use but does not explicitly mention when not to use it or name alternative tools, so it stops short of a 5.

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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