affiliate_daisycon-advertiser_list_media_partners

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

With no annotations, the description carries the transparency burden. It discloses that the tool returns MediaPartner records with normalised status and describes the result as an outbound roster. However, it omits important behavioral details like pagination behavior, filtering semantics (status/search), authentication requirements, and error cases, leaving gaps in what the agent should expect.

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 and well-structured, front-loading the core action, then providing user-facing examples and tool-pairing guidance. Every sentence contributes value without redundancy or unnecessary detail.

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 tool is moderately complex (6 parameters, no output schema, no annotations). The description gives a solid high-level picture and usage context, but it lacks parameter explanations, output format details, and pagination/status behavior, which are necessary for fully autonomous invocation in varied situations.

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 is 0%, so the description must compensate for parameter meanings. It only implicitly references the 'brand' parameter through 'brand's programme' and gives no explanation of limit, cursor, offset, search, or status. Parameter names are somewhat self-explanatory, but the lack of specificity (e.g., valid status values, how search works) falls short of full compensation.

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 identifies the tool's function: listing media partners (publishers) for a brand's Daisycon advertiser programme. It uses a specific verb ('List') with a specific resource, and distinguishes itself from sibling tools by specifying the Daisycon advertiser context and the media partner entity.

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 provides explicit usage triggers with example user queries ('who is promoting us...', 'which publishers are active...') and suggests pairing with get_programme_performance for deeper analysis. It does not explicitly state when not to use the tool, but the positive use cases and complementary tool reference provide clear guidance.

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