zuckerbot_creative_cross_analysis

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

With no annotations provided, the description carries the full burden of behavioral disclosure. It does convey what the call produces (a performance matrix, best/worst combinations, and an actionable insight string), which is useful return-format context. It does not disclose the read-only nature, whether it requires prior creative-attribute data, or how the insight string is generated, leaving some ambiguity about data dependencies.

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 sentences with zero filler: purpose, example, return format. The purpose is front-loaded, the example earns its place by clarifying the abstract 'cross' idea, and the returns sentence completes the agent's mental model. Efficient and well-ordered.

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?

For a read-style analysis tool with 9 parameters, no output schema, and a relatively simple query intent, the description covers the essential contract: what it does, an illustrative usage, and what it returns. The main gaps are lack of explicit relation to cohort/objective_family advanced filter behavior and no statement about read-only safety, but the schema covers the filters and the tool complexity is low enough that this is not critical.

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%, and every one of the 9 parameters already has its own description, so the baseline is 3. The description reinforces that group_by and cross_by are the two dimensions being 'crossed' and that the combination order matters (hook_type × visual_style yields a cell like curiosity + ugc), but it adds no new parameter-level detail beyond the schema.

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 states a specific verb ('cross') and resource ('two creative dimensions') with a clear goal ('find winning combinations'), and the hook_type × visual_style example makes the operation concrete. It distinguishes itself from the sibling zuckerbot_creative_analysis through the word 'cross' implying a two-dimensional comparison, though it never explicitly names the sibling or contrasts itself against it.

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 example implies the intended use — pairing two creative dimensions (e.g., hook_type × visual_style) to surface winning patterns before building creative. However, there is no explicit guidance on when to choose this tool over zuckerbot_creative_analysis, suggest_angles, or get_performance, and no 'when-not-to-use' or prerequisite context (such as needing uploaded creatives or business context).

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