zuckerbot_creative_analysis

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

With no annotations, the description carries the full burden. It fully discloses the return structure: average metrics per group, trend direction, insight object with recommendations, and optional top/bottom ads. This gives a clear behavioral understanding without hiding side effects (it is read-only). It could mention required permissions or data dependencies, but it is still transparent.

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 three sentences with no redundancy. The first sentence states the purpose and grouping options, the second lists outputs, and the third gives usage guidance. Every sentence earns its place, and the key information is front-loaded.

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?

Given the absence of an output schema, the description adequately explains return values (groups, trends, insights, recommendations). It also mentions optional outputs (include_ads, summary_mode) and grouping attributes. It could clarify defaults (e.g., metric defaults to cpl) but overall provides sufficient context for a tool with 9 parameters.

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 the baseline is 3. The description adds meaning by explaining that group_by uses creative attributes, include_ads returns top 5/bottom 5, and summary_mode returns a condensed narrative. This enhances understanding beyond the schema's parameter descriptions, justifying a score above baseline.

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's purpose: 'Analyse creative performance patterns by grouping ads by hook type, visual style, etc.' It specifies the verb ('Analyse') and resource ('creative performance patterns'), listing seven grouping attributes. However, it does not explicitly distinguish from sibling tools like zuckerbot_creative_cross_analysis, so it loses a point for differentiation.

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 a clear usage context: 'Use this before generating new briefs to inform the creative strategy.' This implies when to use it, but it does not mention when not to use it or suggest alternatives among siblings. Thus, it meets the minimum for clear context but lacks exclusions.

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