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

With no annotations, the description bears the transparency burden. It discloses the operation as a live read-only listing ('List all... live from Meta') and scopes what is included with concrete source categories. It could add a explicit note about pagination or response shape, but for a simple read endpoint the disclosure is adequate.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

Three short sentences, all informative: primary purpose with examples, UI mapping, and use case. There is no repetition of the title or schema and no filler.

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

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

The description is strong for a tool with no output schema and no annotations: it tells the agent what is returned conceptually and why to call it, while the schema fully covers required parameters and pagination. It doesn't describe exact result fields, but that is a minor gap for a simple list tool.

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

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

Schema coverage is 100%, so every parameter already has a description and the tool description adds no parameter-level detail. Baseline 3 applies because the description doesn't need to compensate for schema gaps.

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

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

The description uses a specific verb ('List') and a specific resource ('data sources connected to a Meta product catalog'), then enumerates the source types (product feeds, Batch API, Shopify/WooCommerce, smart pixel, website crawling). This makes it clearly distinct from sibling catalog tools like get_catalog_details or get_catalog_diagnostics without needing to inspect their schemas.

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

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

'Use to see how a catalog's products get ingested' and the Commerce Manager Data Sources tab reference give clear context for when to call it. It doesn't explicitly state 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.