meta_ads_pixels_list

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

The description labels the operation as 'Read-only,' which is a key behavioral trait. However, with no annotations provided, the description does not disclose other aspects like pagination behavior, rate limits, or error handling. For a list operation, the 'Read-only' label and returned fields are sufficient but not exhaustive.

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?

The description is concise—three sentences in total—with the most critical information (purpose, return fields, read-only, use cases) front-loaded. There is no redundant or excessive text; every sentence serves a clear function.

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?

Despite no output schema, the description enumerates the returned fields (id, name, code, last_fired_time, is_created_by_business), which is helpful. It also provides context by linking to related tools. However, it omits mentioning any optional filters or sorting, and does not specify if the list is paginated (the schema does include a limit parameter that implies pagination, but the description doesn't explain it). Overall, it is fairly complete for a straightforward 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 description coverage for both parameters (account_id, limit) is 100%, so the description does not need to add parameter details. The description adds no extra semantics beyond the schema, which is the baseline expectation. The use case mention does not enhance parameter understanding.

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 clearly states the tool lists Meta Pixels and enumerates the specific fields returned (id, name, code, last_fired_time, is_created_by_business). It also distinguishes this from sibling tools by mentioning use cases (finding a pixel_id before creating a WEBSITE audience or fetching event statistics), which are specific to other tools like meta_ads_audiences_create and meta_ads_pixels_stats.

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?

The description explicitly states when to use this tool: 'Use this to find a pixel_id before creating a WEBSITE audience or fetching event statistics.' It does not specify when not to use or provide alternative tools, but the context provided is clear and directive.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.