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meta_ads_catalogs_list

Lists Meta Commerce Catalogs for a Business, returning catalog IDs, names, product counts, verticals, and feed counts to identify the catalog_id needed for managing products or feeds.

Instructions

Lists Meta Commerce Catalogs owned by a Business. Returns id, name, product_count, vertical (commerce / hotels / flights / home_listings / destinations), and feed_count per catalog. Read-only. Use this to find a catalog_id before calling meta_ads_catalogs_get / delete or managing products / feeds underneath.

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.
business_idYesMeta Business ID that owns the catalogs. Catalogs live at the Business level, not the ad-account level — the Business ID is required here.
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 explicitly states 'Read-only,' which is a key behavioral trait, and describes the return payload (id, name, product_count, vertical, feed_count). However, it does not mention pagination, rate limits, permission requirements, or error behavior, which would provide fuller transparency for a list operation.

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 concise, consisting of two sentences. The first sentence states the action and return fields; the second provides usage context. Every word adds value, and the structure is front-loaded with purpose.

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 the simplicity of the tool (2 params, no output schema, no annotations), the description covers the essential aspects: what it lists, what it returns, and when to use it. It could benefit from a mention of pagination or limits, but it is sufficiently complete for a straightforward list operation.

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%, with both parameters documented in detail (e.g., account_id format and fallback, business_id ownership). The tool description adds no additional parameter semantics beyond the schema, so the baseline of 3 applies.

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 verb ('Lists'), the resource ('Meta Commerce Catalogs'), and the scope ('owned by a Business'). It also distinguishes itself from sibling tools by explicitly mentioning its role in finding a catalog_id before calling meta_ads_catalogs_get / delete or managing products/feeds, making its purpose unambiguous.

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

Usage Guidelines5/5

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

The description provides explicit when-to-use guidance: 'Use this to find a catalog_id before calling meta_ads_catalogs_get / delete or managing products / feeds underneath.' It also labels the tool as 'Read-only,' implying it should not be used for mutations. This clearly frames its place among alternatives.

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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